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Oliver Bruce Linton

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography of Economics:
  1. Dong, C. & Gao, J. & Linton, O. & Peng, B., 2020. "On Time Trend of COVID-19: A Panel Data Study," Cambridge Working Papers in Economics 2065, Faculty of Economics, University of Cambridge.

    Mentioned in:

    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Modelling > Statistical Modelling

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Lena Boneva & Oliver Linton & Michael Vogt, 2016. "The Effect of Fragmentation in Trading on Market Quality in the UK Equity Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 192-213, January.

    Mentioned in:

    1. The Effect of Fragmentation in Trading on Market Quality in the UK Equity Market (Journal of Applied Econometrics 2016) in ReplicationWiki ()
  2. Keith Vorkink & Douglas J. Hodgson & Oliver Linton, 2002. "Testing the capital asset pricing model efficiently under elliptical symmetry: a semiparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 617-639.

    Mentioned in:

    1. Testing the capital asset pricing model efficiently under elliptical symmetry: a semiparametric approach (Journal of Applied Econometrics 2002) in ReplicationWiki ()

Working papers

  1. Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüß, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Menac, 2024. "Nonstandard errors," LSE Research Online Documents on Economics 123002, London School of Economics and Political Science, LSE Library.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad‐Díaz & Menachem (Meni) Abudy , 2024. "Nonstandard Errors," Journal of Finance, American Finance Association, vol. 79(3), pages 2339-2390, June.
    • Utz Weitzel & Michael Razen & Sebastian Neussüs & Michael Kirchler & Magnus Johannesson & Juergen Huber & Felix Holzmeister & Anna Dreber & Albert J. Menkveld & Javier Gil-Bazo, 2021. "Non-Standard Errors," Working Papers 1303, Barcelona School of Economics.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," IWH Discussion Papers 11/2021, Halle Institute for Economic Research (IWH).
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian T. Brownlees & Javier Gil-Baz, 2021. "Non-standard errors," Economics Working Papers 1807, Department of Economics and Business, Universitat Pompeu Fabra.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Mena, 2021. "Non-Standard Errors," Working Papers 2021:17, Lund University, Department of Economics.
    • Albert J. et al. Menkveld, 2021. "Non-Standard Errors," CESifo Working Paper Series 9453, CESifo.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Post-Print halshs-03500882, HAL.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neus ss & Michael Razen & Utz Weitzel & Edwin Baidoo & Michael Fr mmel & et al, 2021. "Non-Standard Errors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1032, Ghent University, Faculty of Economics and Business Administration.
    • Francesco Franzoni & Roxana Mihet & Markus Leippold & Per Ostberg & Olivier Scaillet & Norman Schürhoff & Oksana Bashchenko & Nicola Mano & Michele Pelli, 2022. "Non-Standard Errors," Swiss Finance Institute Research Paper Series 22-09, Swiss Finance Institute.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Cambridge Working Papers in Economics 2182, Faculty of Economics, University of Cambridge.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Hasse, Jean-Baptiste & e.a.,, 2023. "Non-Standard Errors," LIDAM Reprints LFIN 2023002, Université catholique de Louvain, Louvain Finance (LFIN).
    • Moinas, Sophie & Declerck, Fany & Menkveld, Albert J. & Dreber, Anna, 2023. "Non-Standard Errors," TSE Working Papers 23-1451, Toulouse School of Economics (TSE).
    • Albert Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad-Díaz & Tobias Adrian & Yacine Ai, 2024. "Nonstandard Errors," Post-Print hal-04676112, HAL.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," SAFE Working Paper Series 327, Leibniz Institute for Financial Research SAFE.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Dí­az & Menachem Abudy & Tobi, 2021. "Non-Standard Errors," Working Papers 2021-31, Faculty of Economics and Statistics, Universität Innsbruck.
    • Gerardo Ferrara & Simon Jurkatis, 2021. "Non-standard errors," Bank of England working papers 955, Bank of England.
    • Albert Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad-Díaz & Tobias Adrian & Yacine Ai, 2024. "Nonstandard Errors," Post-Print hal-05077550, HAL.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03500882, HAL.
    • Albert Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad-Díaz & Tobias Adrian & Yacine Ai, 2024. "Nonstandard Errors," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-05077550, HAL.
    • Ciril Bosch-Rosa & Bernhard Kassner, 2023. "Non-Standard Errors," Rationality and Competition Discussion Paper Series 385, CRC TRR 190 Rationality and Competition.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Janeway Institute Working Papers 2112, Faculty of Economics, University of Cambridge.
    • Wolff, Christian & Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüess, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-Standard Errors," CEPR Discussion Papers 16751, C.E.P.R. Discussion Papers.
    • Albert J. Menkveld & Anna Dreber & Félix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard, 2021. "Non-Standard Errors," Documents de travail du Centre d'Economie de la Sorbonne 21033, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

    Cited by:

    1. Guillaume Coqueret, 2023. "Forking paths in financial economics," Papers 2401.08606, arXiv.org.
    2. Nick Huntington-Klein & Claus C. Portner & Ian McCarthy & The Many Economists Collaborative on Researcher Variation, 2025. "The Sources of Researcher Variation in Economics," NBER Working Papers 33729, National Bureau of Economic Research, Inc.
    3. Fišar, Miloš & Greiner, Ben & Huber, Christoph & Katok, Elena & Ozkes, Ali & Collaboration, Management Science Reproducibility, 2023. "Reproducibility in Management Science," OSF Preprints mydzv, Center for Open Science.
    4. Christoph Huber & Christian König-Kersting & Matteo M. Marini, 2022. "Experimenting with Financial Professionals," Working Papers 2022-07, Faculty of Economics and Statistics, Universität Innsbruck, revised Jun 2024.
    5. Anna Dreber & Magnus Johannesson, 2025. "A framework for evaluating reproducibility and replicability in economics," Economic Inquiry, Western Economic Association International, vol. 63(2), pages 338-356, April.
    6. van Dolder, Dennie & Vandenbroucke, Jurgen, 2024. "Behavioral risk profiling: Measuring loss aversion of individual investors," Journal of Banking & Finance, Elsevier, vol. 168(C).
    7. Christophe Pérignon & Olivier Akmansoy & Christophe Hurlin & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johanneson & Michael Kirchler & Albert Menkveld & Michael Razen & Utz Weitzel, 2022. "Reproducibility of Empirical Results: Evidence from 1,000 Tests in Finance," Working Papers hal-03810013, HAL.
    8. Soebhag, Amar & Van Vliet, Bart & Verwijmeren, Patrick, 2024. "Non-standard errors in asset pricing: Mind your sorts," Journal of Empirical Finance, Elsevier, vol. 78(C).
    9. Breznau, Nate & Rinke, Eike Mark & Wuttke, Alexander & Nguyen, Hung H. V. & Adem, Muna & Adriaans, Jule & Alvarez-Benjumea, Amalia & Andersen, Henrik K. & Auer, Daniel & Azevedo, Flavio & Bahnsen, Oke, 2022. "Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 119(44), pages 1-8.
    10. Stephen A. Gorman & Frank J. Fabozzi, 2023. "Alternative risk premium: specification noise," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 459-473, October.

  2. Jia Chen & Degui Li & Yuning Li & Oliver Linton, 2023. "Estimating Time-Varying Networks for High-Dimensional Time Series," Papers 2302.02476, arXiv.org.

    Cited by:

    1. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Inference of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers 5/23, Monash University, Department of Econometrics and Business Statistics.
    2. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2025. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Working Papers 202526, University of Macau, Faculty of Business Administration.
    3. Jialing Han & Yu-Ning Li, 2025. "Approximate Factor Model with S-vine Copula Structure," Papers 2508.11619, arXiv.org.
    4. Karsten Reichold & Ulrike Schneider, 2025. "Beyond the Oracle Property: Adaptive LASSO in Cointegrating Regressions," Papers 2510.07204, arXiv.org.

  3. Hong, Y. & Linton, O. B. & McCabe, B. & Sun, J. & Wang, S., 2023. "Kolmogorov-Smirnov Type Testing for Structural Breaks: A New Adjusted-Range Based Self-Normalization Approach," Cambridge Working Papers in Economics 2367, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Yannick Hoga & Christian Schulz, 2025. "Self-Normalized Inference in (Quantile, Expected Shortfall) Regressions for Time Series," Papers 2502.10065, arXiv.org, revised Jun 2025.
    2. Christis Katsouris, 2023. "Limit Theory under Network Dependence and Nonstationarity," Papers 2308.01418, arXiv.org, revised Aug 2023.
    3. Sun, Jiajing & Zhu, Meiting & Linton, Oliver, 2025. "Adjusted-range-based self-normalized autocorrelation tests," Economics Letters, Elsevier, vol. 251(C).

  4. Vogt, M. & Walsh, C. & Linton, O., 2022. "CCE Estimation of High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics 2242, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Kaicheng Chen, 2025. "Inference in High-Dimensional Panel Models: Two-Way Dependence and Unobserved Heterogeneity," Papers 2504.18772, arXiv.org.
    2. Beyhum, Jad & Striaukas, Jonas, 2024. "Testing for sparse idiosyncratic components in factor-augmented regression models," Journal of Econometrics, Elsevier, vol. 244(1).
    3. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2024. "Robust Estimation and Inference for High-Dimensional Panel Data Models," Papers 2405.07420, arXiv.org, revised Feb 2025.

  5. Hafner, Christian & Linton, Oliver & Wang, Linqi, 2022. "Dynamic Autoregressive Liquidity (DArLiQ)," LIDAM Discussion Papers ISBA 2022009, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Jean-Loup Dupret & Donatien Hainaut, 2025. "A fractional Hawkes process for illiquidity modeling," Mathematics and Financial Economics, Springer, volume 19, number 6, December.
    2. Bachmair, K., 2023. "The Effects of the LIBOR Scandal on Volatility and Liquidity in LIBOR Futures Markets," Cambridge Working Papers in Economics 2303, Faculty of Economics, University of Cambridge.

  6. Linton, O. B. & Tang, H. & Wu, J., 2022. "A Structural Dynamic Factor Model for Daily Global Stock Market Returns," Cambridge Working Papers in Economics 2237, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Matteo Barigozzi, 2023. "Quasi Maximum Likelihood Estimation of High-Dimensional Factor Models: A Critical Review," Papers 2303.11777, arXiv.org, revised May 2024.

  7. Cheng, T. & Dong, C. & Gao, J. & Linton, O., 2022. "GMM Estimation for High-Dimensional Panel Data Models," Cambridge Working Papers in Economics 2245, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Linton, O. B. & Rücker, M. & Vogt, M. & Walsh, C., 2024. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Janeway Institute Working Papers 2429, Faculty of Economics, University of Cambridge.
    2. Maximilian Ruecker & Michael Vogt & Oliver Linton & Christopher Walsh, 2022. "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Papers 2206.12152, arXiv.org, revised Aug 2025.

  8. Liang Jiang & Oliver B. Linton & Haihan Tang & Yichong Zhang, 2022. "Improving Estimation Efficiency via Regression-Adjustment in Covariate-Adaptive Randomizations with Imperfect Compliance," Papers 2201.13004, arXiv.org, revised Jun 2023.

    Cited by:

    1. Jiang, Liang & Li, Liyao & Miao, Ke & Zhang, Yichong, 2025. "Adjustments with many regressors under covariate-adaptive randomizations," Journal of Econometrics, Elsevier, vol. 249(PB).

  9. Linton, O. B. & Xu, E., 2022. "Auditing the Auditors: An evaluation of the REF2021 Output Results," Cambridge Working Papers in Economics 2266, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Hudson, Robert, 2024. "Responding to incentives or gaming the system? How UK business academics respond to the Academic Journal Guide," Research Policy, Elsevier, vol. 53(9).
    2. Paolo Fantozzi & Valerio Ficcadenti & Maurizio Naldi, 2025. "The university research assessment dilemma: a decision support system for the next evaluation campaigns," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(3), pages 1617-1658, March.
    3. Morgan-Thomas, Anna & Tsoukas, Serafeim & Dudau, Adina & Gąska, Paweł, 2024. "Beyond declarations: Metrics, rankings and responsible assessment," Research Policy, Elsevier, vol. 53(10).

  10. Li, M. Z. & Linton, O., 2021. "Robust Estimation of Integrated and Spot Volatility," Cambridge Working Papers in Economics 2115, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Minseog Oh & Donggyu Kim, 2021. "Effect of the U.S.--China Trade War on Stock Markets: A Financial Contagion Perspective," Papers 2111.09655, arXiv.org.

  11. Linton, O. & Tang, H., 2020. "Estimation of the Kronecker Covariance Model by Quadratic Form," Cambridge Working Papers in Economics 2050, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Yuefeng Han & Rong Chen & Cun-Hui Zhang, 2020. "Rank Determination in Tensor Factor Model," Papers 2011.07131, arXiv.org, revised May 2022.
    2. Bhimasankaram Pochiraju & Sridhar Seshadri & Dimitrios D. Thomakos & Konstantinos Nikolopoulos, 2020. "Non-Negativity of a Quadratic form with Applications to Panel Data Estimation, Forecasting and Optimization," Stats, MDPI, vol. 3(3), pages 1-18, July.

  12. Anderson, G. & Linton, O. & Pittau, M G. & Whang, Y-J. & Zelli, R., 2020. "On Unit Free Assessment of The Extent of Multilateral Distributional Variation," Cambridge Working Papers in Economics 20123, Faculty of Economics, University of Cambridge.

    Cited by:

    1. C.J. O’Donnell, 2025. "Accounting for Environmental Variables and Bad Outputs in DEA," CEPA Working Papers Series WP032025, School of Economics, University of Queensland, Australia.
    2. Gordon Anderson & Maria Grazia Pittau & Roberto Zelli, 2020. "Measuring the progress of equality of educational opportunity in absence of cardinal comparability," METRON, Springer;Sapienza Università di Roma, vol. 78(2), pages 155-174, August.
    3. Anderson, Gordon & Fu, Rui & Leo, Teng Wah, 2022. "Health, loneliness and the ageing process in the absence of cardinal measure: Rendering intangibles tangible," The Journal of the Economics of Ageing, Elsevier, vol. 22(C).

  13. Lee, K. & Linton, O. & Whang, Y-J., 2020. "Testing for Time Stochastic Dominance," Cambridge Working Papers in Economics 20121, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Kyungho Lee & Yoon-Jae Whang, 2023. "PySDTest: a Python/Stata Package for Stochastic Dominance Tests," Papers 2307.10694, arXiv.org, revised Aug 2024.

  14. Ge, S. & Li, S. & Linton, O., 2020. "A Dynamic Network of Arbitrage Characteristics," Cambridge Working Papers in Economics 2060, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Valenti, Daniele & Bastianin, Andrea & Manera, Matteo, 2022. "A weekly structural VAR model of the US crude oil market," FEEM Working Papers 324040, Fondazione Eni Enrico Mattei (FEEM).
    2. Adrian Fernandez-Perez & Ana-Maria Fuertes & Joelle Miffre, 2021. "The Risk Premia of Energy Futures," Post-Print hal-03312959, HAL.
    3. Johannes Rude Jensen & Mohsen Pourpouneh & Kurt Nielsen & Omri Ross, 2021. "The Homogenous Properties of Automated Market Makers," Papers 2105.02782, arXiv.org.
    4. Stanislav Anatolyev & Sergei Seleznev & Veronika Selezneva, 2021. "How does the financial market update beliefs about the real economy? Evidence from the oil market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 938-961, November.
    5. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.
    6. Hongyi Liu, 2025. "Deep Learning for Conditional Asset Pricing Models," Papers 2509.04812, arXiv.org.

  15. Hafner, Christian & Linton, Oliver & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," LIDAM Reprints ISBA 2020028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Hafner, Christian M. & Wang, Linqi, 2023. "A dynamic conditional score model for the log correlation matrix," Journal of Econometrics, Elsevier, vol. 237(2).
    2. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    3. Chen, Xin & Yang, Dan & Xu, Yan & Xia, Yin & Wang, Dong & Shen, Haipeng, 2023. "Testing and support recovery of correlation structures for matrix-valued observations with an application to stock market data," Journal of Econometrics, Elsevier, vol. 232(2), pages 544-564.
    4. Yuefeng Han & Rong Chen & Cun-Hui Zhang, 2020. "Rank Determination in Tensor Factor Model," Papers 2011.07131, arXiv.org, revised May 2022.
    5. Cai, Zhanrui & Li, Changcheng & Wen, Jiawei & Yang, Songshan, 2024. "Asset splitting algorithm for ultrahigh dimensional portfolio selection and its theoretical property," Journal of Econometrics, Elsevier, vol. 239(2).

  16. Chaohua Dong & Jiti Gao & Oliver Linton & Bin Peng, 2020. "On the Time Trend of COVID-19: A Panel Data Study," Papers 2006.11060, arXiv.org, revised Jun 2020.

    Cited by:

    1. Giovanni Angelini & Giuseppe Cavaliere & Enzo D'Innocenzo & Luca De Angelis, 2022. "Time-Varying Poisson Autoregression," Papers 2207.11003, arXiv.org.

  17. Linton, O. & Seo, M. & Whang, Y-J., 2020. "Testing Stochastic Dominance with Many Conditioning Variables," Cambridge Working Papers in Economics 2004, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Zongwu Cai & Ying Fang & Ming Lin & Yaqian Wu, 2024. "Estimating Counterfactual Distribution Functions via Optimal Distribution Balancing with Applications," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202415, University of Kansas, Department of Economics.

  18. Bonsoo Koo & Davide La Vecchia & Oliver Linton, 2020. "Estimation of a Nonparametric Model for Bond Prices from Cross-Section and Time Series Information," Monash Econometrics and Business Statistics Working Papers 4/20, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. David T. Frazier & Bonsoo Koo, 2020. "Indirect Inference for Locally Stationary Models," Monash Econometrics and Business Statistics Working Papers 30/20, Monash University, Department of Econometrics and Business Statistics.
    2. Frazier, David T. & Koo, Bonsoo, 2021. "Indirect inference for locally stationary models," Journal of Econometrics, Elsevier, vol. 223(1), pages 1-27.

  19. Li, S. & Linton, O., 2020. "When will the Covid-19 pandemic peak?," Cambridge Working Papers in Economics 2025, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Andrew Atkeson & Karen Kopecky & Tao Zha, 2020. "Estimating and Forecasting Disease Scenarios for COVID-19 with an SIR Model," NBER Working Papers 27335, National Bureau of Economic Research, Inc.
    2. Shaw, Norman & Eschenbrenner, Brenda & Baier, Daniel, 2022. "Online shopping continuance after COVID-19: A comparison of Canada, Germany and the United States," Journal of Retailing and Consumer Services, Elsevier, vol. 69(C).
    3. Marcelo Medeiros & Alexandre Street & Davi Vallad~ao & Gabriel Vasconcelos & Eduardo Zilberman, 2020. "Short-Term Covid-19 Forecast for Latecomers," Papers 2004.07977, arXiv.org, revised Sep 2021.
    4. Chaohua Dong & Jiti Gao & Oliver Linton & Bin Peng, 2020. "On the Time Trend of COVID-19: A Panel Data Study," Papers 2006.11060, arXiv.org, revised Jun 2020.
    5. Ricardo Martínez & Juan D Moreno Ternero, 2021. "Pandemic performance," ThE Papers 21/09, Department of Economic Theory and Economic History of the University of Granada..
    6. Laura Coroneo & Fabrizio Iacone & Alessia Paccagnini & Paulo Santos Monteiro, 2021. "Testing the predictive accuracy of COVID-19 forecasts," CAMA Working Papers 2021-52, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    7. Andrew Atkeson, 2020. "On Using SIR Models to Model Disease Scenarios for COVID-19," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 41(01), pages 1-35, June.
    8. Alexander Chudik & M. Hashem Pesaran & Alessandro Rebucci, 2020. "Voluntary and Mandatory Social Distancing: Evidence on COVID-19 Exposure Rates from Chinese Provinces and Selected Countries," NBER Working Papers 27039, National Bureau of Economic Research, Inc.
    9. Sokbae (Simon) Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2020. "Sparse HP filter: Finding kinks in the COVID-19 contact rate," CeMMAP working papers CWP32/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Difang Huang & Ying Liang & Boyao Wu & Yanyi Ye, 2025. "Estimating the impact of social distance policy in mitigating COVID-19 spread with factor-based imputation approach," Empirical Economics, Springer, vol. 68(2), pages 585-601, February.
    11. Augusto Cerqua & Roberta Di Stefano & Marco Letta & Sara Miccoli, 2020. "Local mortality estimates during the COVID-19 pandemic in Italy," Working Papers 14/20, Sapienza University of Rome, DISS.
    12. Monika Małgorzata Wojcieszak-Zbierska & Anna Jęczmyk & Jan Zawadka & Jarosław Uglis, 2020. "Agritourism in the Era of the Coronavirus (COVID-19): A Rapid Assessment from Poland," Agriculture, MDPI, vol. 10(9), pages 1-19, September.
    13. Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.
    14. Bårdsen, Gunnar & Nymoen, Ragnar, 2025. "Dynamic time series modelling and forecasting of COVID-19 in Norway," International Journal of Forecasting, Elsevier, vol. 41(1), pages 251-269.
    15. Christian M. Hafner, 2020. "The Spread of the Covid-19 Pandemic in Time and Space," IJERPH, MDPI, vol. 17(11), pages 1-13, May.
    16. Andrei Zubarev & Maria Kirillova, 2022. "Modeling COVID-19 spread in the Russian Federation using global VAR approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 117-138.
    17. Ho, Paul & Lubik, Thomas A. & Matthes, Christian, 2023. "How to go viral: A COVID-19 model with endogenously time-varying parameters," Journal of Econometrics, Elsevier, vol. 232(1), pages 70-86.
    18. Julliard, Christian & Shi, Ran & Yuan, Kathy, 2020. "The spread of COVID-19 in London: network effects and optimal lockdowns," LSE Research Online Documents on Economics 118864, London School of Economics and Political Science, LSE Library.
    19. Difang Huang & Ying Liang & Boyao Wu & Yanyi Ye, 2024. "Estimating the Impact of Social Distance Policy in Mitigating COVID-19 Spread with Factor-Based Imputation Approach," Papers 2405.12180, arXiv.org.
    20. Gunnar BÃ¥rdsen & Ragnar Nymoen, 2023. "Dynamic time series modelling and forecasting of COVID-19 in Norway," Working Paper Series 19623, Department of Economics, Norwegian University of Science and Technology.
    21. Lokman Gunduz & Ahmet Faruk Aysan & Rifgi Bugra Bagci & Hatice Karahan, 2024. "Explosive Behavior in COVID-19 and Policy Responses: Lessons Learned for Public Health Management," SAGE Open, , vol. 14(1), pages 21582440231, March.
    22. Fernández-Villaverde, Jesús & Jones, Charles I., 2022. "Estimating and simulating a SIRD Model of COVID-19 for many countries, states, and cities," Journal of Economic Dynamics and Control, Elsevier, vol. 140(C).
    23. Giovanni Angelini & Giuseppe Cavaliere & Enzo D'Innocenzo & Luca De Angelis, 2022. "Time-Varying Poisson Autoregression," Papers 2207.11003, arXiv.org.
    24. Ricardo Martínez & Juan D. Moreno-Ternero, 2022. "An axiomatic approach towards pandemic performance indicators," Working Papers 22.10, Universidad Pablo de Olavide, Department of Economics.
    25. Bårdsen, Gunnar & Nymoen, Ragnar, 2023. "Dynamic time series modelling and forecasting of COVID-19 in Norway," Memorandum 3/2023, Oslo University, Department of Economics.
    26. Paul Ho, 2021. "Forecasting in the Absence of Precedent," Working Paper 21-10, Federal Reserve Bank of Richmond.
    27. David Meintrup & Martina Nowak-Machen & Stefan Borgmann, 2021. "Nine Months of COVID-19 Pandemic in Europe: A Comparative Time Series Analysis of Cases and Fatalities in 35 Countries," IJERPH, MDPI, vol. 18(12), pages 1-17, June.
    28. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
    29. Ba Chu & Shafiullah Qureshi, 2020. "Predicting the COVID-19 Pandemic in Canada and the US," Carleton Economic Papers 20-05, Carleton University, Department of Economics, revised 30 Jul 2020.
    30. Belhadi, Amine & Kamble, Sachin & Jabbour, Charbel Jose Chiappetta & Gunasekaran, Angappa & Ndubisi, Nelson Oly & Venkatesh, Mani, 2021. "Manufacturing and service supply chain resilience to the COVID-19 outbreak: Lessons learned from the automobile and airline industries," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    31. Aman Ullah & Tao Wang & Weixin Yao, 2022. "Nonlinear modal regression for dependent data with application for predicting COVID‐19," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 1424-1453, July.

  20. Lena Boneva & David Elliott & Iryna Kaminska & Oliver Linton & Nick McLaren & Ben Morley, 2019. "The impact of corporate QE on liquidity: evidence from the UK," Bank of England working papers 782, Bank of England.

    Cited by:

    1. Andrew Bailey & Jonathan Bridges & Richard Harrison & Josh Jones & Aakash Mankodi, 2020. "The central bank balance sheet as a policy tool: past, present and future," Bank of England working papers 899, Bank of England.
    2. Stefania D’Amico & Iryna Kaminska, 2019. "Credit easing versus quantitative easing: evidence from corporate and government bond purchase programs," Bank of England working papers 825, Bank of England.
    3. Andrew Bailey & Jonathan Bridges & Richard Harrison & Josh Jones & Aakash Mankodi, 2025. "The Central Bank Balance Sheet As a Policy Tool: Lessons From the Bank of England's Experience," Journal of Financial Services Research, Springer;Western Finance Association, vol. 67(1), pages 5-30, April.
    4. Boneva, Lena & Islami, Mevlud & Schlepper, Kathi, 2024. "Liquidity in the German corporate bond market: Has the CSPP made a difference?," Journal of International Money and Finance, Elsevier, vol. 147(C).
    5. Joost Bats, 2020. "Corporates dependence on banks: The impact of ECB corporate sector purchases," Working Papers 667, DNB.
    6. Patrick Aldridge & David Cimon & Rishi Vala, 2023. "Central Bank Crisis Interventions: A Review of the Recent Literature on Potential Costs," Discussion Papers 2023-30, Bank of Canada.
    7. Christensen, Jens H.E. & Gillan, James M., 2022. "Does quantitative easing affect market liquidity?," Journal of Banking & Finance, Elsevier, vol. 134(C).
    8. Domenech Palacios, Mar, 2025. "Firms’ risk and monetary transmission: revisiting the excess bond premium," Working Paper Series 3118, European Central Bank.

  21. Linton, O. & Shiu, J-L., 2019. "Semiparametric Nonlinear Panel Data Models with Measurement Error," Cambridge Working Papers in Economics 1906, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Schennach, Susanne M., 2020. "Mismeasured and unobserved variables," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 487-565, Elsevier.

  22. Cheng, T. & Gao, J. & Linton, O., 2019. "Nonparametric Predictive Regressions for Stock Return Prediction," Cambridge Working Papers in Economics 1932, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.
    2. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2019. "Machine Learning for Forecasting Excess Stock Returns The Five-Year-View," Graz Economics Papers 2019-06, University of Graz, Department of Economics.

  23. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Hiroyuki Kawakatsu, 2020. "Recovering Yield Curves from Dynamic Term Structure Models with Time-Varying Factors," Stats, MDPI, vol. 3(3), pages 1-46, August.

  24. Linton, O. & Xiao, Z., 2019. "Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity," Cambridge Working Papers in Economics 1907, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
    2. Hwang, Eunju & Hong, Won-Tak, 2021. "A multivariate HAR-RV model with heteroscedastic errors and its WLS estimation," Economics Letters, Elsevier, vol. 203(C).
    3. Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.
    4. Sai Yuan & Xiongfeng Pan & Mengna Li, 2023. "The nonlinear influence of innovation efficiency on carbon and haze co-control: the threshold effect of environmental decentralization," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(12), pages 14283-14307, December.
    5. Cui, Qiurong & Xu, Yuqing & Zhang, Zhengjun & Chan, Vincent, 2021. "Max-linear regression models with regularization," Journal of Econometrics, Elsevier, vol. 222(1), pages 579-600.

  25. Ma, S. & Linton, O. & Gao, J., 2019. "Estimation and Inference in Semiparametric Quantile Factor Models," Cambridge Working Papers in Economics 1933, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Wei, Jie & Chen, Hui, 2020. "Determining the number of factors in approximate factor models by twice K-fold cross validation," Economics Letters, Elsevier, vol. 191(C).
    2. Jie Wei & Yonghui Zhang, 2023. "Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?," Papers 2305.05934, arXiv.org, revised Nov 2024.
    3. Dolado, Juan J & Chen, Liang & Gonzalo, Jesus, 2018. "Quantile Factor Models," CEPR Discussion Papers 12716, C.E.P.R. Discussion Papers.
    4. Yang, Shuquan & Ling, Nengxiang, 2023. "Robust projected principal component analysis for large-dimensional semiparametric factor modeling," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    5. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Quantile Random-Coefficient Regression with Interactive Fixed Effects: Heterogeneous Group-Level Policy Evaluation," Papers 2208.03632, arXiv.org, revised Nov 2024.
    6. Liang Chen & Juan Jose Dolado & Jesus Gonzalo & Haozi Pan, 2023. "Estimation of Characteristics-based Quantile Factor Models," Papers 2304.13206, arXiv.org.
    7. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    8. Cheng, T. & Dong, C. & Gao, J. & Linton, O., 2022. "GMM Estimation for High-Dimensional Panel Data Models," Cambridge Working Papers in Economics 2245, Faculty of Economics, University of Cambridge.
    9. Dimitris Korobilis & Maximilian Schröder, 2023. "Monitoring multicountry macroeconomic risk," Working Papers No 06/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    10. Korobilis, Dimitris & Schröder, Maximilian, 2025. "Monitoring multi-country macroeconomic risk: A quantile factor-augmented vector autoregressive (QFAVAR) approach," Journal of Econometrics, Elsevier, vol. 249(PC).
    11. Dong, Ruipeng & Li, Daoji & Zheng, Zemin, 2021. "Parallel integrative learning for large-scale multi-response regression with incomplete outcomes," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
    12. Belloni, Alexandre & Chen, Mingli & Madrid Padilla, Oscar Hernan & Wang, Zixuan (Kevin), 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," The Warwick Economics Research Paper Series (TWERPS) 1230, University of Warwick, Department of Economics.
    13. Zhu, Zhoufan & Zhang, Ningning & Zhu, Ke, 2024. "Big portfolio selection by graph-based conditional moments method," Journal of Empirical Finance, Elsevier, vol. 78(C).
    14. Jozef Barunik & Matej Nevrla, 2022. "Beyond Volatility: Common Factors in Idiosyncratic Quantile Risks," Papers 2208.14267, arXiv.org, revised Aug 2025.
    15. Ruofan Xu & Jiti Gao & Tatsushi Oka & Yoon-Jae Whang, 2022. "Estimation of Heterogeneous Treatment Effects Using Quantile Regression with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 13/22, Monash University, Department of Econometrics and Business Statistics.
    16. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.

  26. Merrick Li, Z. & Linton, O., 2019. "A ReMeDI for Microstructure Noise," Cambridge Working Papers in Economics 1908, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Andersen, Torben G. & Riva, Raul & Thyrsgaard, Martin & Todorov, Viktor, 2023. "Intraday cross-sectional distributions of systematic risk," Journal of Econometrics, Elsevier, vol. 235(2), pages 1394-1418.
    2. Jianqing Fan & Donggyu Kim & Minseok Shin & Yazhen Wang, 2024. "Factor and Idiosyncratic VAR-Ito Volatility Models for Heavy-Tailed High-Frequency Financial Data," Working Papers 202415, University of California at Riverside, Department of Economics.
    3. Bollerslev, Tim & Li, Jia & Li, Qiyuan, 2024. "Optimal nonparametric range-based volatility estimation," Journal of Econometrics, Elsevier, vol. 238(1).
    4. Ge, S. & Li, S. & Linton, O. B. & Liu, W. & Su, W., 2024. "Should We Augment Large Covariance Matrix Estimation with Auxiliary Network Information?," Cambridge Working Papers in Economics 2427, Faculty of Economics, University of Cambridge.
    5. Carsten H. Chong & Viktor Todorov, 2024. "A nonparametric test for rough volatility," Papers 2407.10659, arXiv.org.
    6. Bilel Sanhaji & Julien Chevallier, 2023. "Tracking ‘Pure’ Systematic Risk with Realized Betas for Bitcoin and Ethereum," Post-Print hal-04218488, HAL.
    7. Torben G. Andersen & Yingwen Tan & Viktor Todorov & Zhiyuan Zhang, 2025. "Testing mean stationarity of intraday volatility curves," Quantitative Economics, Econometric Society, vol. 16(3), pages 1059-1091, July.
    8. Cui, Wenhao & Hu, Jie & Wang, Jiandong, 2024. "Nonparametric estimation for high-frequency data incorporating trading information," Journal of Econometrics, Elsevier, vol. 240(1).
    9. I. Kalaitzoglou, 2025. "Cleaning the carbon market! Market transparency and market efficiency in the EU ETS," Post-Print hal-05133749, HAL.
    10. Donggyu Kim & Xinyu Song & Yazhen Wang, 2020. "Unified Discrete-Time Factor Stochastic Volatility and Continuous-Time Ito Models for Combining Inference Based on Low-Frequency and High-Frequency," Papers 2006.12039, arXiv.org.
    11. Aleksey Kolokolov & Giulia Livieri & Davide Pirino, 2022. "Testing for Endogeneity of Irregular Sampling Schemes," CEIS Research Paper 547, Tor Vergata University, CEIS, revised 19 Dec 2022.
    12. Iordanis Angelos Kalaitzoglou, 2025. "Cleaning the carbon market! Market transparency and market efficiency in the EU ETS," Annals of Operations Research, Springer, vol. 347(1), pages 501-533, April.
    13. Nabil Bouamara & Kris Boudt & S'ebastien Laurent & Christopher J. Neely, 2023. "Sluggish news reactions: A combinatorial approach for synchronizing stock jumps," Papers 2309.15705, arXiv.org.
    14. Markus Bibinger & Nikolaus Hautsch & Alexander Ristig, 2024. "Jump detection in high-frequency order prices," Papers 2403.00819, arXiv.org, revised Aug 2025.
    15. Chang, Jinyuan & Hu, Qiao & Liu, Cheng & Tang, Cheng Yong, 2024. "Optimal covariance matrix estimation for high-dimensional noise in high-frequency data," Journal of Econometrics, Elsevier, vol. 239(2).
    16. Andersen, Torben G. & Li, Yingying & Todorov, Viktor & Zhou, Bo, 2023. "Volatility measurement with pockets of extreme return persistence," Journal of Econometrics, Elsevier, vol. 237(2).
    17. Xiao, Xijuan & Yamamoto, Ryuichi, 2024. "Realized volatility, price informativeness, and tick size: A market microstructure approach," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 410-426.

  27. Chen, J. & Li, D. & Linton, O., 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Cambridge Working Papers in Economics 1876, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Bu, R. & Li, D. & Linton, O. & Wang, H., 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Janeway Institute Working Papers 2208, Faculty of Economics, University of Cambridge.
    2. Xuan, Liang & Jiti, Gao & xiaodong, Gong, 2021. "Semiparametric Spatial Autoregressive Panel Data Model with Fixed Effects and Time-Varying Coefficients," MPRA Paper 108497, University Library of Munich, Germany, revised 30 May 2021.
    3. Ge, S. & Li, S. & Linton, O. B. & Liu, W. & Su, W., 2024. "Should We Augment Large Covariance Matrix Estimation with Auxiliary Network Information?," Cambridge Working Papers in Economics 2427, Faculty of Economics, University of Cambridge.
    4. Jiti Gao & Bin Peng & Yayi Yan, 2024. "Higher-Order Expansions and Inference for Panel Data Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 119(548), pages 2760-2771, October.
    5. Fan, Qingliang & Wu, Ruike & Yang, Yanrong & Zhong, Wei, 2024. "Time-varying minimum variance portfolio," Journal of Econometrics, Elsevier, vol. 239(2).
    6. Xuan Liang & Jiti Gao & Xiaodong Gong, 2019. "Time-Varying Coefficient Spatial Autoregressive Panel Data Model with Fixed Effects," Monash Econometrics and Business Statistics Working Papers 26/19, Monash University, Department of Econometrics and Business Statistics.
    7. Chen, J. & Li, Y. & Linton, O. B., 2025. "Estimation of Large Dynamic Precision Matrices with a Latent Semiparametric Structure," Janeway Institute Working Papers 2514, Faculty of Economics, University of Cambridge.
    8. Wang, Hanchao & Peng, Bin & Li, Degui & Leng, Chenlei, 2021. "Nonparametric estimation of large covariance matrices with conditional sparsity," Journal of Econometrics, Elsevier, vol. 223(1), pages 53-72.
    9. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    10. Chenlei Leng & Degui Li & Hanlin Shang & Yingcun Xia, 2024. "Covariance Function Estimation for High-Dimensional Functional Time Series with Dual Factor Structures," Papers 2401.05784, arXiv.org, revised Jan 2024.
    11. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    12. Zhang, Xiaomeng & Zhang, Xinyu, 2023. "Optimal model averaging based on forward-validation," Journal of Econometrics, Elsevier, vol. 237(2).
    13. Jiti Gao & Bin Peng & Yayi Yan, 2022. "A Simple Bootstrap Method for Panel Data Inferences," Monash Econometrics and Business Statistics Working Papers 7/22, Monash University, Department of Econometrics and Business Statistics.

  28. Hong, S-Y. & Linton, O., 2018. "Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff," Cambridge Working Papers in Economics 1877, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Trifonov, Juri & Potanin, Bogdan, 2024. "GARCH-M model with an asymmetric risk premium: Distinguishing between ‘good’ and ‘bad’ volatility periods," International Review of Financial Analysis, Elsevier, vol. 91(C).
    2. Ben Célestin Kouassi & Ouagnina Hili & Edoh Katchekpele, 2025. "On change point detection in regression function using nonparametric autoregressive processes," Indian Journal of Pure and Applied Mathematics, Springer, vol. 56(1), pages 191-209, March.
    3. da Silva, Murilo & Sriram, T.N. & Ke, Yuan, 2023. "Dimension reduction in time series under the presence of conditional heteroscedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).
    4. Juri Trifonov, 2023. "Modeling the risk premium in the Russian stock market considering the asymmetry effect," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 71, pages 5-19.
    5. Antell, Jan & Vaihekoski, Mika, 2023. "Countercyclical and time-varying reward to risk and the equity premium," Research in International Business and Finance, Elsevier, vol. 66(C).

  29. Dong, C. & Gao, J. & Linton, O., 2018. "High Dimensional Semiparametric Moment Restriction Models," Cambridge Working Papers in Economics 1881, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP69/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    3. Pu, Dan & Fang, Kuangnan & Lan, Wei & Yu, Jihai & Zhang, Qingzhao, 2024. "Multivariate spatiotemporal models with low rank coefficient matrix," Journal of Econometrics, Elsevier, vol. 246(1).
    4. Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "Chaohua Dong, Jiti Gao and Oliver Linton’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 707-708, July.
    5. Cheng, T. & Dong, C. & Gao, J. & Linton, O., 2022. "GMM Estimation for High-Dimensional Panel Data Models," Cambridge Working Papers in Economics 2245, Faculty of Economics, University of Cambridge.
    6. Liyuan Cui & Guanhao Feng & Yongmiao Hong, 2024. "Regularized Gmm For Time‐Varying Models With Applications To Asset Pricing," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(2), pages 851-883, May.
    7. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.

  30. James Brugler & Oliver Linton & Joseph Noss & Lucas Pedace, 2018. "The cross-sectional spillovers of single stock circuit breakers," Bank of England working papers 759, Bank of England.

    Cited by:

    1. Kyong Shik Eom & Kyung Yoon Kwon & Sung Chae La & Jong-Ho Park, 2022. "Dynamic and Static Volatility Interruptions: Evidence from the Korean Stock Markets," JRFM, MDPI, vol. 15(3), pages 1-19, February.
    2. Shan Lu & Jichang Zhao & Huiwen Wang, 2019. "The emergence of critical stocks in market crash," Papers 1908.07244, arXiv.org.
    3. Wong, Kin Ming & Kong, Xiao Wei & Li, Min, 2020. "The magnet effect of circuit breakers and its interactions with price limits," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).

  31. Michael Vogt & Oliver Linton, 2018. "Multiscale clustering of nonparametric regression curves," CeMMAP working papers CWP08/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2024. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 1026-1040, July.
    2. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Inference of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers 5/23, Monash University, Department of Econometrics and Business Statistics.
    3. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2025. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Working Papers 202526, University of Macau, Faculty of Business Administration.
    4. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.
    5. Dong Hwan Oh & Andrew J. Patton, 2021. "Dynamic Factor Copula Models with Estimated Cluster Assignments," Finance and Economics Discussion Series 2021-029r1, Board of Governors of the Federal Reserve System (U.S.), revised 06 May 2022.
    6. Jia Chen, 2018. "Estimating Latent Group Structure in Time-Varying Coefficient Panel Data Models," Discussion Papers 18/15, Department of Economics, University of York.
    7. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    8. Oh, Dong Hwan & Patton, Andrew J., 2023. "Dynamic factor copula models with estimated cluster assignments," Journal of Econometrics, Elsevier, vol. 237(2).
    9. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    10. Pionati, Alessandro, 2025. "Latent grouped structures in panel data: a review," MPRA Paper 123954, University Library of Munich, Germany.

  32. Linton, O. & Whang, Y-J. & Yen, Y., 2018. "The Lower Regression Function and Testing Expectation Dependence Dominance Hypotheses," Cambridge Working Papers in Economics 1880, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Denuit, Michel & Trufin, Julien & Verdebout, Thomas, 2021. "Testing for more positive expectation dependence with application to model comparison," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 163-172.
    2. Denuit, Michel & Trufin, Julien & Verdebout, Thomas, 2021. "Testing for more positive expectation dependence with application to model comparison," LIDAM Discussion Papers ISBA 2021021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  33. Chunrong Ai & Oliver Linton & Zheng Zhang, 2018. "A simple and efficient estimation method for models with nonignorable missing data," CeMMAP working papers CWP02/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Lei Wang & Wei Ma, 2021. "Improved empirical likelihood inference and variable selection for generalized linear models with longitudinal nonignorable dropouts," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 623-647, June.
    2. Zhang, Ting & Wang, Lei, 2020. "Smoothed empirical likelihood inference and variable selection for quantile regression with nonignorable missing response," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).

  34. Tingting Cheng & Jiti Gao & Oliver Linton, 2018. "Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction," CeMMAP working papers CWP03/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Forecasting benchmarks of long-term stock returns via machine learning," Annals of Operations Research, Springer, vol. 297(1), pages 221-240, February.

  35. Jiti Gao & Oliver Linton & Bin Peng, 2018. "Inference on a semiparametric model with global power law and local nonparametric trends," CeMMAP working papers CWP05/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Chaohua Dong & Jiti Gao & Oliver Linton & Bin Peng, 2020. "On the Time Trend of COVID-19: A Panel Data Study," Papers 2006.11060, arXiv.org, revised Jun 2020.
    2. Chen, Zhihong & Xia, Huizhu, 2020. "Trend instrumental variable regression with an application to the US New Keynesian Phillips Curve," Economic Modelling, Elsevier, vol. 93(C), pages 595-604.
    3. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.

  36. Shujie Ma & Oliver Linton & Jiti Gao, 2018. "Estimation in semiparametric quantile factor models," CeMMAP working papers CWP07/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Katal, Ali & Mortezazadeh, Mohammad & Wang, Liangzhu (Leon), 2019. "Modeling building resilience against extreme weather by integrated CityFFD and CityBEM simulations," Applied Energy, Elsevier, vol. 250(C), pages 1402-1417.
    2. Canfield, Martha & Norton, Sam & Downs, Johnny & PMM Wijlaars, Linda & Gilchrist, Gail, 2023. "Risk factors for involvement in care proceedings for mothers receiving treatment for substance use: A cohort study using linked and administrative data in South London," Children and Youth Services Review, Elsevier, vol. 155(C).

  37. Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2018. "A Unified Framework for Efficient Estimation of General Treatment Models," Papers 1808.04936, arXiv.org, revised Aug 2018.

    Cited by:

    1. Jiang, Qingshan & Xu, Li & Huang, Can, 2022. "Covariates distributions balancing for continuous treatment," Economics Letters, Elsevier, vol. 217(C).
    2. Chen, Xiaohong & Liu, Ying & Ma, Shujie & Zhang, Zheng, 2024. "Causal inference of general treatment effects using neural networks with a diverging number of confounders," Journal of Econometrics, Elsevier, vol. 238(1).
    3. Wei Huang & Oliver Linton & Zheng Zhang, 2022. "A Unified Framework for Specification Tests of Continuous Treatment Effect Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1817-1830, October.
    4. Chunrong Ai & Yue Fang & Haitian Xie, 2024. "Data-driven Policy Learning for Continuous Treatments," Papers 2402.02535, arXiv.org, revised Nov 2024.
    5. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    6. Zeqi Wu & Meilin Wang & Wei Huang & Zheng Zhang, 2025. "A New and Efficient Debiased Estimation of General Treatment Models by Balanced Neural Networks Weighting," Papers 2507.04044, arXiv.org.
    7. Yukitoshi Matsushita & Taisuke Otsu & Keisuke Takahata, 2022. "Estimating density ratio of marginals to joint: Applications to causal inference," STICERD - Econometrics Paper Series 619, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    8. Xiaohong Chen & Haitian Xie, 2025. "Local Overidentification and Efficiency Gains in Modern Causal Inference and Data Combination," Papers 2510.16683, arXiv.org.
    9. Lin Liu & Chang Li, 2023. "New $\sqrt{n}$-consistent, numerically stable higher-order influence function estimators," Papers 2302.08097, arXiv.org.

  38. Linton, O. & Mahmoodzadeh, S., 2018. "Implications of High-Frequency Trading for Security Markets," Cambridge Working Papers in Economics 1802, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Ran, Ling, 2025. "Blockchain-Integrated AI Strategies for Cross-Border High-Frequency Trading: Optimizing Liquidity and Reducing Transaction Costs," OSF Preprints knz94_v1, Center for Open Science.
    2. Papavassiliou, Vassilios G. & Kinateder, Harald, 2021. "Information shares and market quality before and during the European sovereign debt crisis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    3. Marszk, Adam & Lechman, Ewa, 2021. "Reshaping financial systems: The role of ICT in the diffusion of financial innovations – Recent evidence from European countries," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    4. Sánchez Serrano Antonio, 2020. "High-Frequency Trading and Systemic Risk: A Structured Review of Findings and Policies," Review of Economics, De Gruyter, vol. 71(3), pages 169-195, December.
    5. Gianluca Piero Maria Virgilio, 2019. "High-frequency trading: a literature review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 183-208, June.
    6. Leone, Vitor & Kwabi, Frank, 2019. "High frequency trading, price discovery and market efficiency in the FTSE100," Economics Letters, Elsevier, vol. 181(C), pages 174-177.
    7. Oualid Bada & Alois Kneip & Dominik Liebl & Tim Mensinger & James Gualtieri & Robin C. Sickles, 2021. "A Wavelet Method for Panel Models with Jump Discontinuities in the Parameters," Papers 2109.10950, arXiv.org.
    8. Farzan Yahya & Muhammad Waqas & Muhammad Hussain & Abdul Haseeb Tahir, 2024. "The heterogeneous effect of technology and macroeconomic policies on financial market development," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(2), pages 1131-1146, April.
    9. Ramos, Henrique Pinto & Perlin, Marcelo Scherer, 2020. "Does algorithmic trading harm liquidity? Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    10. Garg, Karan, 2021. "Machines and Markets : Assessing the Impact of Algorithmic Trading on Financial Market Efficiency," Warwick-Monash Economics Student Papers 11, Warwick Monash Economics Student Papers.

  39. Lena Boneva (Körber) & Oliver Linton, 2017. "A discrete choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance," CeMMAP working papers 02/17, Institute for Fiscal Studies.

    Cited by:

    1. Francesco Bartolucci & Claudia Pigini & Francesco Valentini, 2024. "MCMC conditional maximum likelihood for the two-way fixed-effects logit," Econometric Reviews, Taylor & Francis Journals, vol. 43(6), pages 379-404, July.
    2. Andrea Zaghini, 2017. "The CSPP at work: yield heterogeneity and the portfolio rebalancing channel," Temi di discussione (Economic working papers) 1157, Bank of Italy, Economic Research and International Relations Area.
    3. Gao, J. & Linton, O. & Peng, B., 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Janeway Institute Working Papers 2215, Faculty of Economics, University of Cambridge.
    4. Óscar Arce & Ricardo Gimeno & Sergio Mayordomo, 2017. "Making room for the needy: the credit-reallocation effects of the ECB’s corporate QE," Working Papers 1743, Banco de España.
    5. Chen, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021. "Nonlinear factor models for network and panel data," Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
    6. Eberhardt, Markus, 2018. "(At Least) Four Theories for Sovereign Default," CEPR Discussion Papers 13084, C.E.P.R. Discussion Papers.
    7. Wang, Peng & Wang, Xi, 2025. "Adjusted principal component estimation for binary factor model," MPRA Paper 123844, University Library of Munich, Germany.
    8. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    9. Rodolphe Desbordes & Markus Eberhardt & Mario Larch, 2025. "A democratic dividend in trade? Evidence from a flexible empirical implementation," Discussion Papers 2025-02, University of Nottingham, GEP.
    10. Liang Chen & Minyuan Zhang, 2023. "Common Correlated Effects Estimation of Nonlinear Panel Data Models," Papers 2304.13199, arXiv.org.
    11. Jie Wei & Yonghui Zhang, 2022. "Panel Probit Models with Time‐Varying Individual Effects: Reestimating the Effects of Fertility on Female Labour Participation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 799-829, August.
    12. Qu Feng, 2019. "Common Factors and Common Breaks in Panels: An Empirical Investigation," Economic Growth Centre Working Paper Series 1905, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    13. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    14. De Vos, Ignace & Stauskas, Ovidijus, 2024. "Cross-section bootstrap for CCE regressions," Journal of Econometrics, Elsevier, vol. 240(1).
    15. Ando, Tomohiro & Bai, Jushan & Li, Kunpeng, 2022. "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 230(1), pages 20-38.
    16. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    17. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
    18. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    19. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    20. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    21. Ye, Xiaoqing & Xu, Juan & Wu, Xiangjun, 2018. "Estimation of an unbalanced panel data Tobit model with interactive effects," Journal of choice modelling, Elsevier, vol. 28(C), pages 108-123.
    22. Mugnier, Martin & Wang, Ao, 2024. "Fixed Effects Nonlinear Panel Models with Heterogeneous Slopes : Identification and Consistency," The Warwick Economics Research Paper Series (TWERPS) 1531, University of Warwick, Department of Economics.
    23. Nicola Borri & Denis Chetverikov & Yukun Liu & Aleh Tsyvinski, 2024. "One Factor to Bind the Cross-Section of Returns," NBER Working Papers 32365, National Bureau of Economic Research, Inc.
    24. Mugnier, Martin & Wang, Ao, 2022. "Identification and (Fast) Estimation of Large Nonlinear Panel Models with Two-Way Fixed Effects," The Warwick Economics Research Paper Series (TWERPS) 1422, University of Warwick, Department of Economics.
    25. Mr. Markus Eberhardt & Mr. Andrea F Presbitero, 2018. "Commodity Price Movements and Banking Crises," IMF Working Papers 2018/153, International Monetary Fund.
    26. Abidi, Nordine & Miquel-Flores, Ixart, 2018. "Who benefits from the corporate QE? A regression discontinuity design approach," Working Paper Series 2145, European Central Bank.
    27. Rachel Cho & Rodolphe Desbordes & Markus Eberhardt, 2022. "The causal effects of the darker side of financial development," Discussion Papers 2022-04, University of Nottingham, GEP.
    28. Rodolphe Desbordes & Markus Eberhardt, 2019. "Gravity," Discussion Papers 2019-02, University of Nottingham, GEP.
    29. Lee, Yoonseok & Sul, Donggyu, 2023. "Depth-weighted means of noisy data: An application to estimating the average effect in heterogeneous panels," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
    30. Chen, Jia & Shin, Yongcheol & Zheng, Chaowen, 2022. "Estimation and inference in heterogeneous spatial panels with a multifactor error structure," Journal of Econometrics, Elsevier, vol. 229(1), pages 55-79.

  40. Auld, T. & Linton, O., 2017. "The Behaviour of Betting and Currency Markets on the Night of the EU Referendum," Cambridge Working Papers in Economics 1750, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Erdinc Akyildirim & Oguzhan Cepni & Shaen Corbet & Gazi Salah Uddin, 2023. "Forecasting mid-price movement of Bitcoin futures using machine learning," Annals of Operations Research, Springer, vol. 330(1), pages 553-584, November.
    2. Wiśniowski, Arkadiusz & Bijak, Jakub & Forster, Jonathan J. & Smith, Peter W.F., 2019. "Hierarchical model for forecasting the outcomes of binary referenda," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 90-103.
    3. P. Manasse & G. Moramarco & G. Trigilia, 2020. "Exchange Rates and Political Uncertainty: The Brexit Case," Working Papers wp1141, Dipartimento Scienze Economiche, Universita' di Bologna.
    4. Wael Bousselmi & Patrick Sentis & Marc Willinger, 2018. "Impact of the Brexit vote announcement on long-run market performance," CEE-M Working Papers hal-01954920, CEE-M, Universtiy of Montpellier, CNRS, INRA, Montpellier SupAgro.
    5. Facundo Albornoz & Jake Bradley & Silvia Sonderegger, 2020. "The Brexit referendum and the rise in hate crime; conforming to the new norm," Discussion Papers 2020-12, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    6. Facundo Albornoz & Jake Bradley & Silvia Sonderegger, 2022. "Updating the Social Norm: the Case of Hate Crime after the Brexit Referendum," Working Papers 203, Red Nacional de Investigadores en Economía (RedNIE).
    7. Manamba Epaphra & Khatibu Kazungu, 2021. "Efficiency of Tanzania's foreign exchange market," African Development Review, African Development Bank, vol. 33(2), pages 368-381, June.
    8. Auld, T., 2022. "Betting and financial markets are cointegrated on election night," Cambridge Working Papers in Economics 2263, Faculty of Economics, University of Cambridge.

  41. Joseph Noss & Lucas Pedace & Ondrej Tobek & Oliver Linton & Liam Crowley-Reidy, 2017. "The October 2016 sterling flash episode: when liquidity disappeared from one of the world’s most liquid markets," Bank of England working papers 687, Bank of England.

    Cited by:

    1. Oliver Linton & Soheil Mahmoodzadeh, 2018. "Implications of High-Frequency Trading for Security Markets," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 237-259, August.
    2. David‐Jan Jansen, 2021. "The International Spillovers of the 2010 U.S. Flash Crash," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(6), pages 1573-1586, September.
    3. Wenqian Huang & Peter O'Neill & Angelo Ranaldo & Shihao Yu, 2023. "HFTs and Dealer Banks: Liquidity and Price Discovery in FX Trading," Swiss Finance Institute Research Paper Series 23-48, Swiss Finance Institute.
    4. Antoine Bouveret & Martin Haferkorn & Gaetano Marseglia & Onofrio Panzarino, 2022. "Flash crashes on sovereign bond markets – EU evidence," Mercati, infrastrutture, sistemi di pagamento (Markets, Infrastructures, Payment Systems) 20, Bank of Italy, Directorate General for Markets and Payment System.

  42. Chaohua Dong & Oliver Linton, 2017. "Additive nonparametric models with time variable and both stationary and nonstationary regressions," CeMMAP working papers 59/17, Institute for Fiscal Studies.

    Cited by:

    1. Ruiqi Liu & Ben Boukai & Zuofeng Shang, 2019. "Statistical Inference on Partially Linear Panel Model under Unobserved Linearity," Papers 1911.08830, arXiv.org.
    2. Dong, Chaohua & Chen, Rong & Xiao, Zhijie & Liu, Weiyi, 2024. "Functional quantile autoregression," Journal of Econometrics, Elsevier, vol. 244(2).
    3. Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP69/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2023. "Robust M-Estimation for Additive Single-Index Cointegrating Time Series Models," Monash Econometrics and Business Statistics Working Papers 2/23, Monash University, Department of Econometrics and Business Statistics.
    5. Feng, Guohua & Gao, Jiti & Peng, Bin, 2022. "An integrated panel data approach to modelling economic growth," Journal of Econometrics, Elsevier, vol. 228(2), pages 379-397.
    6. Batten, Jonathan A. & Mo, Di & Pourkhanali, Armin, 2024. "Can inflation predict energy price volatility?," Energy Economics, Elsevier, vol. 129(C).
    7. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.
    8. Peng, Bin & Su, Liangjun & Westerlund, Joakim & Yang, Yanrong, 2025. "Interactive Effects Panel Data Models With General Factors And Regressors," Econometric Theory, Cambridge University Press, vol. 41(2), pages 472-488, April.
    9. Chaohua Dong & Jiti Gao & Bin Peng & Yayi Yan, 2023. "Estimation of Semiparametric Multi-Index Models Using Deep Neural Networks," Monash Econometrics and Business Statistics Working Papers 21/23, Monash University, Department of Econometrics and Business Statistics.
    10. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Monash Econometrics and Business Statistics Working Papers 18/21, Monash University, Department of Econometrics and Business Statistics.
    11. Pourkhanali, Armin & Tafakori, Laleh & Bee, Marco, 2023. "Forecasting Value-at-Risk using functional volatility incorporating an exogenous effect," International Review of Financial Analysis, Elsevier, vol. 89(C).
    12. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," LSE Research Online Documents on Economics 103830, London School of Economics and Political Science, LSE Library.
    13. Guohua Feng & Jiti Gao & Bin Peng, 2019. "An Integrated Panel Data Approach to Modelling Economic Growth," Monash Econometrics and Business Statistics Working Papers 6/19, Monash University, Department of Econometrics and Business Statistics.
    14. Bin Ping & Liangju Su & Yanrong Yang & Joakim Westerlund, 2023. "Interactive-effects panel-data models with general factors and regressors," French Stata Users' Group Meetings 2023 14, Stata Users Group.
    15. Chaohua Dong & Jiti Gao & Bin Peng, 2018. "Varying-coefficient panel data models with partially observed factor structure," Monash Econometrics and Business Statistics Working Papers 1/18, Monash University, Department of Econometrics and Business Statistics.
    16. Li, Haiqi & Zhang, Jing & Zheng, Chaowen, 2025. "Functional-coefficient quantile cointegrating regression with stationary covariates," Statistics & Probability Letters, Elsevier, vol. 219(C).
    17. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    18. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Papers 2111.02023, arXiv.org.
    19. Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.
    20. Cheng, T. & Dong, C. & Gao, J. & Linton, O., 2022. "GMM Estimation for High-Dimensional Panel Data Models," Cambridge Working Papers in Economics 2245, Faculty of Economics, University of Cambridge.
    21. Tingting Cheng & Jiti Gao & Oliver Linton & Yayi Yan, 2025. "Nonparametric predictive regression for stock return prediction," Econometric Reviews, Taylor & Francis Journals, vol. 44(10), pages 1462-1493, November.
    22. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    23. Qiying Wang & Peter C. B. Phillips, 2024. "A General Limit Theory for Nonlinear Functionals of Nonstationary Time Series," Cowles Foundation Discussion Papers 2337R1, Cowles Foundation for Research in Economics, Yale University.
    24. Chaohua Dong & Jiti Gao & Bin Peng & Yayi Yan, 2023. "Estimation and Inference for a Class of Generalized Hierarchical Models," Papers 2311.02789, arXiv.org, revised Apr 2024.
    25. Lin, Yingqian & Tu, Yundong, 2024. "Functional coefficient cointegration models with Box–Cox transformation," Economics Letters, Elsevier, vol. 234(C).
    26. Zhang, Huiming & Qian, Siji & Ma, Zhen, 2024. "An analysis of the market efficiency of the Chinese copper futures based on intertemporal and intermarket arbitrages," International Review of Financial Analysis, Elsevier, vol. 94(C).
    27. Tu, Yundong & Wang, Ying, 2022. "Spurious functional-coefficient regression models and robust inference with marginal integration," Journal of Econometrics, Elsevier, vol. 229(2), pages 396-421.
    28. Peng, Zhen & Dong, Chaohua, 2022. "Augmented cointegrating linear models with possibly strongly correlated stationary and nonstationary regressors," Finance Research Letters, Elsevier, vol. 47(PB).
    29. Ayman Mnasri & Zouhair Mrabet & Mouyad Alsamara, 2023. "A new quadratic asymmetric error correction model: does size matter?," Empirical Economics, Springer, vol. 65(1), pages 33-64, July.
    30. Tingting Cheng & Jiti Gao & Oliver Linton, 2019. "Nonparametric Predictive Regressions for Stock Return Prediction," Monash Econometrics and Business Statistics Working Papers 4/19, Monash University, Department of Econometrics and Business Statistics.
    31. Tu, Yundong & Liang, Han-Ying & Wang, Qiying, 2022. "Nonparametric inference for quantile cointegrations with stationary covariates," Journal of Econometrics, Elsevier, vol. 230(2), pages 453-482.

  43. Hafner, C. & Linton, O., 2016. "An Almost Closed Form Estimator for the EGARCH model," LIDAM Discussion Papers ISBA 2016036, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. CORNUEJOLS, Gérard & WOLSEY, Laurence & YILDIZ, Sercan, 2013. "Sufficiency of cut-generating functions," LIDAM Discussion Papers CORE 2013027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Chiara Canta & Marie-Louise Leroux, 2016. "Public and Private Hospitals, Congestion, and Redistribution," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 18(1), pages 42-66, February.
    3. Bocart, Fabian Y.R.P. & Hafner, Christian, 2015. "Fair Revaluation of Wine as an Investment," LIDAM Reprints ISBA 2015040, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. GOERTZ, Johanna & MANIQUET, François, 2013. "Large elections with multiple alternatives: a Condorcet Jury Theorem and inefficient equilibria," LIDAM Discussion Papers CORE 2013023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. M. Angeles Carnero Fernández & Ana Pérez Espartero, 2018. "Outliers and misleading leverage effect in asymmetric GARCH-type models," Working Papers. Serie AD 2018-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    6. Demos Antonis & Kyriakopoulou Dimitra, 2019. "Finite-Sample Theory and Bias Correction of Maximum Likelihood Estimators in the EGARCH Model," Journal of Time Series Econometrics, De Gruyter, vol. 11(1), pages 1-20, January.
    7. Hafner, Christian & Kyriakopoulou, Dimitra, 2020. "Exponential-Type GARCH Models With Linear-in-Variance Risk Premium," LIDAM Reprints ISBA 2020029, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Xu, Yongdeng, 2024. "Extended multivariate EGARCH model: A model for zero†return and negative spillovers," Cardiff Economics Working Papers E2024/24, Cardiff University, Cardiff Business School, Economics Section.
    9. Ahsan, Md. Nazmul & Dufour, Jean-Marie, 2021. "Simple estimators and inference for higher-order stochastic volatility models," Journal of Econometrics, Elsevier, vol. 224(1), pages 181-197.
    10. MLINAR, Tanja B. & CHEVALIER, Philippe, 2013. "Pooling in manufacturing: do opposites attract?," LIDAM Discussion Papers CORE 2013040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. NESTEROV, Yurii, 2013. "Universal gradient methods for convex optimization problems," LIDAM Discussion Papers CORE 2013026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Prono Todd, 2018. "Closed-form estimators for finite-order ARCH models as simple and competitive alternatives to QMLE," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-25, December.
    13. Yongdeng Xu, 2025. "Extended Multivariate EGARCH Model: A Model for Zero‐Return and Negative Spillovers," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(4), pages 1266-1279, July.

  44. Linton, O. & Wu, J., 2016. "A coupled component GARCH model for intraday and overnight volatility," Cambridge Working Papers in Economics 1671, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    2. Oliver Linton & Soheil Mahmoodzadeh, 2018. "Implications of High-Frequency Trading for Security Markets," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 237-259, August.
    3. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    4. Anne Opschoor & André Lucas, 2019. "Observation-driven Models for Realized Variances and Overnight Returns," Tinbergen Institute Discussion Papers 19-052/IV, Tinbergen Institute.

  45. Seok Young Hong & Oliver Linton, 2016. "Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in finite order," CeMMAP working papers 53/16, Institute for Fiscal Studies.

    Cited by:

    1. Yuliana Linke & Igor Borisov & Pavel Ruzankin & Vladimir Kutsenko & Elena Yarovaya & Svetlana Shalnova, 2022. "Universal Local Linear Kernel Estimators in Nonparametric Regression," Mathematics, MDPI, vol. 10(15), pages 1-28, July.
    2. Eric Auerbach, 2019. "Identification and Estimation of a Partially Linear Regression Model using Network Data," Papers 1903.09679, arXiv.org, revised Jun 2021.

  46. Xiaohong Chen & Oliver Linton & Stefan Schneeberger & Yanping Yi, 2016. "Simple Nonparametric Estimators for the Bid-Ask Spread in the Roll Model," CeMMAP working papers 12/16, Institute for Fiscal Studies.

    Cited by:

    1. Li, Zhiyong & Lambe, Brendan & Adegbite, Emmanuel, 2018. "New bid-ask spread estimators from daily high and low prices," International Review of Financial Analysis, Elsevier, vol. 60(C), pages 69-86.

  47. Jia Chen & Degui Li & Oliver Linton & Zudi Lu, 2015. "Semiparametric dynamic portfolio choice with multiple conditioning variables," CeMMAP working papers 07/15, Institute for Fiscal Studies.

    Cited by:

    1. Peng, Rong & Lu, Zudi, 2024. "Semiparametric Averaging of Nonlinear Marginal Logistic Regressions and Forecasting for Time Series Classification," Econometrics and Statistics, Elsevier, vol. 31(C), pages 19-37.
    2. De Gooijer, Jan G. & Zerom, Dawit, 2019. "Semiparametric quantile averaging in the presence of high-dimensional predictors," International Journal of Forecasting, Elsevier, vol. 35(3), pages 891-909.
    3. Jia Chen & Degui Li & Oliver Linton, 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Discussion Papers 18/14, Department of Economics, University of York.
    4. Jia Chen & Degui Li & Oliver Linton & Zudi Lu, 2015. "Semiparametric model averaging of ultra-high dimensional time series," CeMMAP working papers 62/15, Institute for Fiscal Studies.
    5. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    6. Chen, J. & Li, Y. & Linton, O. B., 2025. "Estimation of Large Dynamic Precision Matrices with a Latent Semiparametric Structure," Janeway Institute Working Papers 2514, Faculty of Economics, University of Cambridge.
    7. Jingwen Tu & Hu Yang & Chaohui Guo & Jing Lv, 2021. "Model averaging marginal regression for high dimensional conditional quantile prediction," Statistical Papers, Springer, vol. 62(6), pages 2661-2689, December.

  48. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2015. "An investigation into multivariate variance ratio statistics and their application to stock market predictability," CeMMAP working papers 13/15, Institute for Fiscal Studies.

    Cited by:

    1. Atanda Mustapha Saidi, 2017. "Working Paper 273 - Stock (Mis)pricing and investment dynamics in Africa," Working Paper Series 2390, African Development Bank.
    2. O'Callaghan, Patrick, 2016. "Measuring utility without mixing apples and oranges and eliciting beliefs about stock prices," MPRA Paper 69363, University Library of Munich, Germany.

  49. Michael Vogt & Oliver Linton, 2015. "Classification of nonparametric regression functions in heterogeneous panels," CeMMAP working papers 06/15, Institute for Fiscal Studies.

    Cited by:

    1. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2017. "Discretizing unobserved heterogeneity," IFS Working Papers W17/03, Institute for Fiscal Studies.
    2. Hafner, Christian & Walders, Fabian, 2017. "Heterogeneous Liquidity Effects in Corporate Bond Spreads," LIDAM Reprints ISBA 2017037, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Jiti Gao & Kai Xia, 2017. "Heterogeneous panel data models with cross-sectional dependence," Monash Econometrics and Business Statistics Working Papers 16/17, Monash University, Department of Econometrics and Business Statistics.

  50. Juan Carlos Escanciano & Stefan Hoderlein & Arthur Lewbel & Oliver Linton & Sorawoot Srisuma, 2015. "Nonparametric Euler equation identification and estimation," CeMMAP working papers 61/15, Institute for Fiscal Studies.

    Cited by:

    1. Bruneel-Zupanc, Christophe Alain, 2021. "Discrete-Continuous Dynamic Choice Models: Identification and Conditional Choice Probability Estimation," TSE Working Papers 21-1185, Toulouse School of Economics (TSE).
    2. Andreas Tryphonides, 2023. "Online Appendix to "Identifying Preferences when Households are Financially Constrained"," Online Appendices 21-242, Review of Economic Dynamics.
    3. Xiaohong Chen & Victor Chernozhukov & Sokbae (Simon) Lee & Whitney K. Newey, 2011. "Local identification of nonparametric and semiparametric models," CeMMAP working papers 17/11, Institute for Fiscal Studies.
    4. Giovanni Gallipoli & Brant Abbott, 2017. ""Permanent Income" Inequality," 2017 Meeting Papers 1033, Society for Economic Dynamics.
    5. Striani, Fabrizio, 2023. "Life-cycle consumption and life insurance: Empirical evidence from Italian Survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).
    6. Timothy M. Christensen, 2014. "Nonparametric identification of positive eigenfunctions," CeMMAP working papers CWP37/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Sadegh Eshaghnia & James J. Heckman & Rasmus Landersø & Rafeh Qureshi, 2022. "Intergenerational Transmission of Family Influence," NBER Working Papers 30412, National Bureau of Economic Research, Inc.
    8. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2023. "Minimax Instrumental Variable Regression and $L_2$ Convergence Guarantees without Identification or Closedness," Papers 2302.05404, arXiv.org.
    9. Kalouptsidi, Myrto & Scott, Paul T. & Souza-Rodrigues, Eduardo, 2018. "Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models," CEPR Discussion Papers 13240, C.E.P.R. Discussion Papers.
    10. Andreas Tryphonides, 2020. "Identifying Preferences when Households are Financially Constrained," Papers 2005.02010, arXiv.org, revised Feb 2023.
    11. Cui, Liyuan & Hong, Yongmiao & Li, Yingxing, 2021. "Solving Euler equations via two-stage nonparametric penalized splines," Journal of Econometrics, Elsevier, vol. 222(2), pages 1024-1056.
    12. Dalderop, Jeroen, 2023. "Semiparametric estimation of latent variable asset pricing models," Journal of Econometrics, Elsevier, vol. 236(1).
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    14. Victor H. Aguiar & Nail Kashaev, 2018. "Stochastic Revealed Preferences with Measurement Error," Papers 1810.05287, arXiv.org, revised Sep 2020.
    15. Myrto Kalouptsidi & Paul T. Scott & Eduardo Souza-Rodrigues, 2018. "Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models," NBER Working Papers 25134, National Bureau of Economic Research, Inc.

  51. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2014. "Multivariate variance ratio statistics," CeMMAP working papers 29/14, Institute for Fiscal Studies.

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    1. Periklis Kougoulis & John C. Nankervis & Jerry Coakley, 2006. "Generalized variance ratio tests in the presence of statistical dependence," Computing in Economics and Finance 2006 180, Society for Computational Economics.

  52. James Brugler & Oliver Linton, 2014. "Single stock circuit breakers on the London Stock Exchange: do they improve subsequent market quality?," CeMMAP working papers CWP07/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Sandrine Jacob Leal & Mauro Napoletano, 2016. "Market Stability vs. Market Resilience: Regulatory Policies Experiments in an Agent-Based Model with Low- and High-Frequency Trading," Working Papers hal-01512781, HAL.
    2. Sifat, Imtiaz Mohammad & Mohamad, Azhar, 2018. "Trading aggression when price limit hits are imminent: NARDL based intraday investigation of magnet effect," Journal of Behavioral and Experimental Finance, Elsevier, vol. 20(C), pages 1-8.
    3. Sifat, Imtiaz Mohammad & Mohamad, Azhar, 2020. "A survey on the magnet effect of circuit breakers in financial markets," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 138-151.
    4. Laly, Floris & Petitjean, Mikael, 2021. "Mini flash crashes: Review, taxonomy and policy responses," LIDAM Reprints LFIN 2021017, Université catholique de Louvain, Louvain Finance (LFIN).
    5. James Brugler, 2015. "Into the light: dark pool trading and intraday market quality on the primary exchange," Bank of England working papers 545, Bank of England.
    6. Kun Li, 2019. "Do Circuit Breakers Impede Trading Behavior? A Study In Chinese Financial Market," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(05), pages 1-18, December.
    7. Imtiaz Mohammad Sifat & Azhar Mohamad, 2019. "Circuit breakers as market stability levers: A survey of research, praxis, and challenges," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(3), pages 1130-1169, July.

  53. Heejoon Han & Oliver Linton & Tatsushi Oka & Yoon-Jae Whang, 2014. "The cross-quantilogram: measuring quantile dependence and testing directional predictability between time series," CeMMAP working papers 06/14, Institute for Fiscal Studies.

    Cited by:

    1. Lyócsa, Štefan & Výrost, Tomáš & Baumöhl, Eduard, 2019. "Return spillovers around the globe: A network approach," Economic Modelling, Elsevier, vol. 77(C), pages 133-146.
    2. Guo, Dong & Zhou, Peng, 2021. "Green bonds as hedging assets before and after COVID: A comparative study between the US and China," Energy Economics, Elsevier, vol. 104(C).
    3. Dai, Zhifeng & Zhu, Junxin & Zhang, Xinhua, 2022. "Time-frequency connectedness and cross-quantile dependence between crude oil, Chinese commodity market, stock market and investor sentiment," Energy Economics, Elsevier, vol. 114(C).
    4. Narayan, Shivani & Kumar, Dilip, 2024. "Unveiling interconnectedness and risk spillover among cryptocurrencies and other asset classes," Global Finance Journal, Elsevier, vol. 62(C).
    5. Yousaf, Imran & Youssef, Manel & Goodell, John W., 2022. "Quantile connectedness between sentiment and financial markets: Evidence from the S&P 500 twitter sentiment index," International Review of Financial Analysis, Elsevier, vol. 83(C).
    6. Islam, Md. Saiful & Islam, Md. Monirul & Rehman, Anis Ur & Alam, Md. Fakhre & Tarique, Md., 2024. "Mineral production amidst the economy of uncertainty: Response of metallic and non-metallic minerals to geopolitical turmoil in Saudi Arabia," Resources Policy, Elsevier, vol. 90(C).
    7. Elie Bouri & Rangan Gupta & Chi Keung Marco Lau & David Roubaud & Shixuan Wang, 2017. "Bitcoin and Global Financial Stress: A Copula-Based Approach to Dependence and Causality-in-Quantiles," Working Papers 201750, University of Pretoria, Department of Economics.
    8. Jozef Barun'ik & Tobias Kley, 2015. "Quantile Coherency: A General Measure for Dependence between Cyclical Economic Variables," Papers 1510.06946, arXiv.org, revised Dec 2018.
    9. Ayedi Ahmed & Marjène Gana & Stéphane Goutte & Khaled Guesmi, 2023. "Managing Portfolio Risk During the BREXIT Crisis: A Cross-Quantilogram Analysis of Stock Markets and Commodities Across European Countries, the US, and BRICS," Working Papers halshs-04068651, HAL.
    10. Baumöhl, Eduard & Lyócsa, Štefan, 2017. "Directional predictability from stock market sector indices to gold: A cross-quantilogram analysis," Finance Research Letters, Elsevier, vol. 23(C), pages 152-164.
    11. Chandrarin, Grahita & Sohag, Kazi & Cahyaningsih, Diyah Sukanti & Yuniawan, Dani & Herdhayinta, Heyvon, 2022. "The response of exchange rate to coal price, palm oil price, and inflation in Indonesia: Tail dependence analysis," Resources Policy, Elsevier, vol. 77(C).
    12. Arif, Muhammad & Naeem, Muhammad Abubakr & Farid, Saqib & Nepal, Rabindra & Jamasb, Tooraj, 2022. "Diversifier or more? Hedge and safe haven properties of green bonds during COVID-19," Energy Policy, Elsevier, vol. 168(C).
    13. Valdivia Coria, Joab Dan, 2022. "Apalancamiento, ciclo financiero y económico [Leverage, financial and business cycles]," MPRA Paper 116849, University Library of Munich, Germany.
    14. Iqbal, Najaf & Bouri, Elie & Ozkan, Oktay, 2025. "The advantages of CBOE credit VIXs for corporate bond investors in North America: A sectoral analysis," Research in International Business and Finance, Elsevier, vol. 73(PA).
    15. Ngo Thai Hung & Vo Xuan Vinh, 2023. "Asymmetric impact of the COVID-19 pandemic on foreign exchange markets: Evidence from an extreme quantile approach," Economics and Business Letters, Oviedo University Press, vol. 12(1), pages 20-32.
    16. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Spillovers from the United States to Latin American and G7 stock markets: A VAR quantile analysis," Emerging Markets Review, Elsevier, vol. 31(C), pages 32-46.
    17. Balsalobre-Lorente, Daniel & Sinha, Avik & Murshed, Muntasir, 2023. "Russia-Ukraine conflict sentiments and energy market returns in G7 countries: Discovering the unexplored dynamics," Energy Economics, Elsevier, vol. 125(C).
    18. Ali, Sajid & Bouri, Elie & Czudaj, Robert Lukas & Shahzad, Syed Jawad Hussain, 2020. "Revisiting the valuable roles of commodities for international stock markets," Resources Policy, Elsevier, vol. 66(C).
    19. Bampinas, Georgios & Panagiotidis, Theodore & Politsidis, Panagiotis N., 2023. "Sovereign bond and CDS market contagion: A story from the Eurozone crisis," Journal of International Money and Finance, Elsevier, vol. 137(C).
    20. Dong, Chaohua & Chen, Rong & Xiao, Zhijie & Liu, Weiyi, 2024. "Functional quantile autoregression," Journal of Econometrics, Elsevier, vol. 244(2).
    21. Daniel Danau, 2018. "Prudence and preference for flexibility gain," Working Papers hal-01806743, HAL.
    22. Syed Jawad Hussain Shahzad & Naveed Raza & David Roubaud & Jose Arreola Hernandez & Stelios Bekiros, 2019. "Gold as Safe Haven for G-7 Stocks and Bonds: A Revisit," Post-Print hal-02352004, HAL.
    23. Salah Uddin, Gazi & Lucey, Brian & Rahman, Md Lutfur & Stenvall, David, 2024. "Quantile coherency across bonds, commodities, currencies, and equities," Journal of Commodity Markets, Elsevier, vol. 33(C).
    24. Corbet, Shaen & Katsiampa, Paraskevi & Lau, Chi Keung Marco, 2020. "Measuring quantile dependence and testing directional predictability between Bitcoin, altcoins and traditional financial assets," International Review of Financial Analysis, Elsevier, vol. 71(C).
    25. Zhang, Dongna & Chen, Xihui Haviour & Lau, Chi Keung Marco & Xu, Bing, 2023. "Implications of cryptocurrency energy usage on climate change," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    26. Elie Bouri & Rangan Gupta & Chi Keung Marco Lau & David Roubaud, 2019. "Risk Aversion and Bitcoin Returns in Normal, Bull, and Bear Markets," Working Papers 201927, University of Pretoria, Department of Economics.
    27. Rabbani, Mustafa Raza & Hassan, M. Kabir & Billah, Syed Mabruk & Shaik, Muneer & Halim, Zairihan Abdul, 2025. "Religion vs. ethics: Tail dependence between Sukuk, green bond, Islamic Fintech, and fourth industrial revolution assets," Pacific-Basin Finance Journal, Elsevier, vol. 90(C).
    28. Sohag, Kazi & Sokhanvar, Amin & Belyaeva, Zhanna & Mirnezami, Seyed Reza, 2022. "Hydrocarbon prices shocks, fiscal stability and consolidation: Evidence from Russian Federation," Resources Policy, Elsevier, vol. 76(C).
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    30. Abakah, Emmanuel Joel Aikins & Nasreen, Samia & Tiwari, Aviral Kumar & Lee, Chien-Chiang, 2023. "U.S. leveraged loan and debt markets: Implications for optimal portfolio and hedging," International Review of Financial Analysis, Elsevier, vol. 87(C).
    31. Okhrin, Yarema & Uddin, Gazi Salah & Yahya, Muhammad, 2023. "Nonlinear and asymmetric interconnectedness of crude oil with financial and commodity markets," Energy Economics, Elsevier, vol. 125(C).
    32. Yang, Xiaoming & Islam, Md. Monirul & Mentel, Grzegorz & Ahmad, Ashfaq & Vasa, László, 2024. "Synergistic dynamics unveiled: Interplay between rare earth prices, clean energy innovations, and tech companies' market resilience amidst the Covid-19 pandemic and Russia-Ukraine conflict," Resources Policy, Elsevier, vol. 89(C).
    33. Lyócsa, Štefan & Výrost, Tomáš & Plíhal, Tomáš, 2021. "A tale of tails : New evidence on the growth-return nexus," Finance Research Letters, Elsevier, vol. 38(C).
    34. Christian Urom & Gideon Ndubuisi & Hela Mzoughi & Khaled Guesmi, 2024. "Exploring the coherency and predictability between the stocks of artificial intelligence and energy corporations," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-31, December.
    35. Stelios Bekiros & Syed Jawad Hussain Shahzad & Jose Arreola-Hernandez & Mobeen Ur Rehman, 2018. "Directional predictability and time-varying spillovers between stock markets and economic cycles," Post-Print hal-01996787, HAL.
    36. Karim, Sitara & Naeem, Muhammad Abubakr & Shafiullah, Muhammad & Lucey, Brian M. & Ashraf, Sania, 2023. "Asymmetric relationship between climate policy uncertainty and energy metals: Evidence from cross-quantilogram," Finance Research Letters, Elsevier, vol. 54(C).
    37. Foglia, Matteo & Addi, Abdelhamid & Angelini, Eliana, 2022. "The Eurozone banking sector in the time of COVID-19: Measuring volatility connectedness," Global Finance Journal, Elsevier, vol. 51(C).
    38. Shahbaz, Muhammad & Trabelsi, Nader & Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Jiao, Zhilun, 2021. "Relationship between green investments, energy markets, and stock markets in the aftermath of the global financial crisis," Energy Economics, Elsevier, vol. 104(C).
    39. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Adekoya, Oluwasegun B. & Hammoudeh, Shawkat, 2023. "What do we know about the price spillover between green bonds and Islamic stocks and stock market indices?," Global Finance Journal, Elsevier, vol. 55(C).
    40. Shaiara Husain & Kazi Sohag & Yanrui Wu, 2022. "The Response of Green Energy and Technology Investment to Climate Policy Uncertainty: An Application of Twin Transition Strategy," Economics Discussion / Working Papers 22-16, The University of Western Australia, Department of Economics.
    41. Satish Kumar & Rabeh Khalfaoui & Aviral Kumar Tiwari, 2021. "Does geopolitical risk improve the directional predictability from oil to stock returns? Evidence from oil-exporting and oil-importing countries," Post-Print hal-03797578, HAL.
    42. Ahad, Muhammad & Imran, Zulfiqar Ali & Shahzad, Khurram, 2024. "Safe haven between European ESG and energy sector under Russian-Ukraine war: Role of sustainable investments for portfolio diversification," Energy Economics, Elsevier, vol. 138(C).
    43. Pedini, Luca & Severini, Sabrina, 2022. "Exploring the hedge, diversifier and safe haven properties of ESG investments: A cross-quantilogram analysis," MPRA Paper 112339, University Library of Munich, Germany.
    44. Davis, Richard & Drees, Holger & Segers, Johan & Warchol, Michal, 2018. "Inference on the tail process with application to financial time series modelling," LIDAM Discussion Papers ISBA 2018002, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    45. Raggad, Bechir, 2023. "Can implied volatility predict returns on oil market? Evidence from Cross-Quantilogram Approach," Resources Policy, Elsevier, vol. 80(C).
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    221. Urom, Christian & Mzoughi, Hela & Ndubuisi, Gideon & Guesmi, Khaled, 2022. "Directional predictability and time-frequency spillovers among clean energy sectors and oil price uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 326-341.
    222. Joaqui-Barandica, Orlando & Oviedo-Gómez, Andres & Manotas-Duque, Diego F., 2023. "Directional predictability between interest rates and the Stoxx 600 Banks index: A quantile approach," Finance Research Letters, Elsevier, vol. 58(PA).
    223. Bouri, Elie & Kachacha, Imad & Roubaud, David, 2020. "Oil market conditions and sovereign risk in MENA oil exporters and importers," Energy Policy, Elsevier, vol. 137(C).
    224. Sohag, Kazi & Sokolova, Yulia & Vilamová, Šárka & Blueschke, Dmitri, 2023. "Volatility transmission from critical minerals prices to green investments," Resources Policy, Elsevier, vol. 82(C).
    225. valdivia coria, joab dan, 2025. "Efectos no lineales del cambio climático y restricción de divisas en la inflación de alimentos [Non-linear effects of climate change and foreign exchange constraints on food inflation]," MPRA Paper 124883, University Library of Munich, Germany.
    226. Muhammad Ali Faisal & Murat Donduran, 2025. "A Two-Stage Analysis of Interaction Between Stock and Exchange Rate Markets: Evidence from Turkey," Annals of Data Science, Springer, vol. 12(1), pages 171-198, February.
    227. Abeeb Olaniran & David Gabauer & Rangan Gupta & Onur Polat, 2025. "Predicting the Conditional Distribution of Risk Aversion The Role of Climate Risks in a Cross-Quantilogram Framework," Working Papers 202524, University of Pretoria, Department of Economics.
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    230. Scarcioffolo, Alexandre R. & Etienne, Xiaoli, 2021. "Testing directional predictability between energy prices: A quantile-based analysis," Resources Policy, Elsevier, vol. 74(C).
    231. Walid Mensi & Mariya Gubareva & Hee-Un Ko & Xuan Vinh Vo & Sang Hoon Kang, 2023. "Tail spillover effects between cryptocurrencies and uncertainty in the gold, oil, and stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
    232. Elie Bouri & Syed Jawad Hussain Shahzad, 2022. "Network Topology of Dynamic Credit Default Swap Curves of Energy Firms and the Role of Oil Shocks," The Energy Journal, , vol. 43(1_suppl), pages 1-26, June.
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    240. Naeem, Muhammad Abubakr & Sadorsky, Perry & Karim, Sitara, 2023. "Sailing across climate-friendly bonds and clean energy stocks: An asymmetric analysis with the Gulf Cooperation Council Stock markets," Energy Economics, Elsevier, vol. 126(C).
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    250. Tian, Tingting & Lai, Kee-hung & Wong, Christina W.Y., 2022. "Connectedness mechanisms in the “Carbon-Commodity-Finance” system: Investment and management policy implications for emerging economies," Energy Policy, Elsevier, vol. 169(C).
    251. Shahzad, Syed Jawad Hussain & Rahman, Md Lutfur & Lucey, Brian M. & Uddin, Gazi Salah, 2021. "Re-examining the real option characteristics of gold for gold mining companies," Resources Policy, Elsevier, vol. 70(C).
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    253. Naeem, Muhammad Abubakr & Mbarki, Imen & Shahzad, Syed Jawad Hussain, 2021. "Predictive role of online investor sentiment for cryptocurrency market: Evidence from happiness and fears," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 496-514.
    254. Huang, Jionghao & Li, Ziruo & Xia, Xiaohua, 2021. "Network diffusion of international oil volatility risk in China's stock market: Quantile interconnectedness modelling and shock decomposition analysis," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 1-39.
    255. Qing, Lingli & Alnafrah, Ibrahim & Dagestani, Abd Alwahed, 2025. "Environmental attention in cryptocurrency markets: A catalyst for clean energy investments," International Review of Economics & Finance, Elsevier, vol. 99(C).
    256. Ji Ho Kwon, 2021. "On the factors of Bitcoin’s value at risk," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
    257. Dragos HURU & Ioana MANAFI & Ionut PANDELICA & Marilena Carmen UZLAU, 2022. "Nonlinear Dependencies between Green Bonds and General Financial Market Indices," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 169-181, December.
    258. Wei, Yu & Hu, Rui & Zhang, Jiahao & Wang, Qian, 2024. "Does the carbon market signal the market efficiency of clean and dirty cryptocurrencies? An analysis of quantile directional dependence," Finance Research Letters, Elsevier, vol. 67(PB).
    259. Lei, Heng & Xue, Minggao & Liu, Huiling & Ye, Jing, 2023. "Precious metal as a safe haven for global ESG stocks: Portfolio implications for socially responsible investing," Resources Policy, Elsevier, vol. 80(C).
    260. Islam, Md. Monirul & Shahbaz, Muhammad & Samargandi, Nahla, 2024. "The nexus between Russian uranium exports and US nuclear-energy consumption: Do the spillover effects of geopolitical risks matter?," Energy, Elsevier, vol. 293(C).
    261. Bouri, Elie & Lien, Donald & Roubaud, David & Shahzad, Syed Jawad Hussain, 2018. "Directional predictability of implied volatility: From crude oil to developed and emerging stock markets," Finance Research Letters, Elsevier, vol. 27(C), pages 65-79.
    262. Wang, Yu & Cheung, Adrian (Wai Kong) & Yan, Wanlin & Wang, Bin, 2024. "Green bond and green stock in China: The role of economic and climate policy uncertainty," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    263. Adewuyi, Adeolu O. & Awodumi, Olabanji B. & Abodunde, Temitope T., 2019. "Analysing the gold-stock nexus using VARMA-BEKK-AGARCH and Quantile regression models: New evidence from South Africa and Nigeria," Resources Policy, Elsevier, vol. 61(C), pages 348-362.
    264. Nahla Samargandi & Kazi Sohag, 2022. "Oil Price Shocks to Foreign Assets and Liabilities in Saudi Arabia under Pegged Exchange Rate," Mathematics, MDPI, vol. 10(24), pages 1-15, December.
    265. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Shao, Xuefeng & Le, TN-Lan & Gyamfi, Matthew Ntow, 2023. "Financial technology stocks, green financial assets, and energy markets: A quantile causality and dependence analysis," Energy Economics, Elsevier, vol. 118(C).
    266. Thobekile Qabhobho & Anokye M. Adam & Emmanuel Asafo-Adjei, 2023. "Do Local and International Shocks Matter in the Interconnectedness amid Exchange Rates and Energy Commodities? Insights into BRICS Economies," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 666-678, November.
    267. Liu, Min & Liu, Hongfei & Ping, Weiying, 2025. "Dynamic spillovers between Shanghai crude oil futures and China's green markets: Evidence from quantile-on-quantile connectedness approach," Economic Analysis and Policy, Elsevier, vol. 85(C), pages 78-93.
    268. Tao, Miaomiao & Poletti, Stephen & Sheng, Mingyue Selena & Wen, Le, 2024. "Nexus between carbon, stock, and energy markets in New Zealand: An analysis of causal domains," Energy, Elsevier, vol. 299(C).
    269. Naeem, Muhammad Abubakr & Karim, Sitara & Abrar, Afsheen & Yarovaya, Larisa & Shah, Adil Ahmad, 2023. "Non-linear relationship between oil and cryptocurrencies: Evidence from returns and shocks," International Review of Financial Analysis, Elsevier, vol. 89(C).
    270. Stenvall, David & Hedström, Axel & Yoshino, Naoyuki & Uddin, Gazi Salah & Taghizadeh-Hesary, Farhad, 2022. "Nonlinear tail dependence between the housing and energy markets," Energy Economics, Elsevier, vol. 106(C).
    271. Urom, Christian & Abid, Ilyes & Guesmi, Khaled & Chevallier, Julien, 2020. "Quantile spillovers and dependence between Bitcoin, equities and strategic commodities," Economic Modelling, Elsevier, vol. 93(C), pages 230-258.
    272. Ye, Wuyi & Li, Mingge & Wu, Yuehua, 2022. "A novel estimation of time-varying quantile correlation for financial contagion detection," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    273. Syed Jawad Hussain Shahzad & Elie Bouri & Mobeen Ur Rehman & David Roubaud, 2022. "The hedge asset for BRICS stock markets: Bitcoin, gold or VIX," The World Economy, Wiley Blackwell, vol. 45(1), pages 292-316, January.
    274. Chishti, Muhammad Zubair & Xia, Xiqiang & Du, Anna Min & Özkan, Oktay, 2025. "Digital financial inclusion, the belt and road initiative, and the Paris agreement: Impacts on energy transition grid costs," Finance Research Letters, Elsevier, vol. 72(C).
    275. Hoque, Mohammad Enamul & Billah, Mabruk & Alam, Md Rafayet & Tiwari, Aviral Kumar, 2024. "Gold-backed cryptocurrencies: A hedging tool against categorical and regional financial stress," Global Finance Journal, Elsevier, vol. 60(C).
    276. Alomari, Mohammad & Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Extreme return spillovers and connectedness between crude oil and precious metals futures markets: Implications for portfolio management," Resources Policy, Elsevier, vol. 79(C).
    277. Hartley, Robert Paul & Lamarche, Carlos & Ziliak, James P., 2023. "Bootstrapping quantile correlations with an application for income status across generations," Economics Letters, Elsevier, vol. 228(C).
    278. Montes-Rojas, Gabriel, 2017. "Reduced form vector directional quantiles," Journal of Multivariate Analysis, Elsevier, vol. 158(C), pages 20-30.
    279. Zhu, Huiming & Xing, Zhanming & Ren, Yinghua & Chen, Yiwen & Hau, Liya, 2023. "Frequency domain causality and quantile connectedness between investor sentiment and cryptocurrency returns," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 1035-1051.
    280. Cai, Yifei & Zhang, Yahua & Xu, Yuchao, 2025. "Assessing the influence of unplanned oil supply outages on airline stock connectedness," Energy Economics, Elsevier, vol. 141(C).
    281. Ji-Eun Choi & Dong Wan Shin, 2022. "Quantile correlation coefficient: a new tail dependence measure," Statistical Papers, Springer, vol. 63(4), pages 1075-1104, August.
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    284. Jing Wan & Shen Zhang & Xu Feng, 2024. "How does the stock market affect the interest rate corridor system in China?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1820-1833, April.
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    287. Changyu Liu & Muhammad Abubakr Naeem & Mobeen Ur Rehman & Saqib Farid & Syed Jawad Hussain Shahzad, 2020. "Oil as Hedge, Safe-Haven, and Diversifier for Conventional Currencies," Energies, MDPI, vol. 13(17), pages 1-19, August.
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  54. Bonsoo Koo & Oliver Linton, 2013. "Let's get LADE: robust estimation of semiparametric multiplicative volatility models," CeMMAP working papers 11/13, Institute for Fiscal Studies.

    Cited by:

    1. Niklas Ahlgren & Alexander Back & Timo Terasvirta, 2024. "A new GARCH model with a deterministic time-varying intercept," Papers 2410.03239, arXiv.org, revised Oct 2024.
    2. David T. Frazier & Bonsoo Koo, 2020. "Indirect Inference for Locally Stationary Models," Monash Econometrics and Business Statistics Working Papers 30/20, Monash University, Department of Econometrics and Business Statistics.
    3. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    4. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.

  55. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "The effect of fragmentation in trading on market quality in the UK equity market," CeMMAP working papers 42/13, Institute for Fiscal Studies.

    Cited by:

    1. Michael Vogt & Oliver Linton, 2015. "Classification of nonparametric regression functions in heterogeneous panels," CeMMAP working papers 06/15, Institute for Fiscal Studies.
    2. Aghanya, Daniel & Agarwal, Vineet & Poshakwale, Sunil, 2020. "Market in Financial Instruments Directive (MiFID), stock price informativeness and liquidity," Journal of Banking & Finance, Elsevier, vol. 113(C).
    3. Daniel Chen & Darrell Duffie, 2021. "Market Fragmentation," American Economic Review, American Economic Association, vol. 111(7), pages 2247-2274, July.
    4. Sinem Hacıoğlu Hoke & George Kapetanios, 2021. "Common correlated effect cross‐sectional dependence corrections for nonlinear conditional mean panel models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 125-150, January.
    5. Paulo Pereira Silva, 2018. "Fragmentation and Market Quality: The Case of European Markets," De Economist, Springer, vol. 166(2), pages 179-206, June.
    6. Suchismita Mishra & Le Zhao, 2021. "Order Routing Decisions for a Fragmented Market: A Review," JRFM, MDPI, vol. 14(11), pages 1-32, November.
    7. James Brugler, 2015. "Into the light: dark pool trading and intraday market quality on the primary exchange," Bank of England working papers 545, Bank of England.
    8. Bernales, Alejandro & Ladley, Daniel & Litos, Evangelos & Valenzuela, Marcela, 2021. "Dark trading and alternative execution priority rules," LSE Research Online Documents on Economics 118866, London School of Economics and Political Science, LSE Library.
    9. Oualid Bada & Alois Kneip & Dominik Liebl & Tim Mensinger & James Gualtieri & Robin C. Sickles, 2021. "A Wavelet Method for Panel Models with Jump Discontinuities in the Parameters," Papers 2109.10950, arXiv.org.
    10. Vogt, Michael & Linton, Oliver, 2020. "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, vol. 216(1), pages 305-325.
    11. Ye, Xiaoqing & Xu, Juan & Wu, Xiangjun, 2018. "Estimation of an unbalanced panel data Tobit model with interactive effects," Journal of choice modelling, Elsevier, vol. 28(C), pages 108-123.
    12. Costa, Geraldo Jr. & Trujillo-Barrera, Andres & Pennings, Joost M.E., 2018. "Concentration and Liquidity Costs in Emerging Commodity Exchanges," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 43(3), September.
    13. Lausen, Jens & Clapham, Benjamin & Gomber, Peter & Bender, Micha, 2022. "Drivers and effects of stock market fragmentation - Insights on SME stocks," SAFE Working Paper Series 367, Leibniz Institute for Financial Research SAFE.
    14. Anna Pomeranets & Daniel G. Weaver, 2024. "Forced consolidation," Review of Quantitative Finance and Accounting, Springer, vol. 62(2), pages 579-601, February.

  56. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "A semiparametric model for heterogeneous panel data with fixed effects," CeMMAP working papers 02/13, Institute for Fiscal Studies.

    Cited by:

    1. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "The effect of fragmentation in trading on market quality in the UK equity market," CeMMAP working papers 42/13, Institute for Fiscal Studies.
    2. Timothy Neal, 2016. "Multidimensional Parameter Heterogeneity in Panel Data Models," Discussion Papers 2016-15, School of Economics, The University of New South Wales.
    3. Sinem Hacıoğlu Hoke & George Kapetanios, 2021. "Common correlated effect cross‐sectional dependence corrections for nonlinear conditional mean panel models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 125-150, January.
    4. Jia Chen & Degui Li & Yingcun Xia, 2015. "New Semiparametric Estimation Procedure for Functional Coefficient Longitudinal Data Models," Discussion Papers 15/17, Department of Economics, University of York.
    5. Lee, Jungyoon & Robinson, Peter M., 2015. "Panel nonparametric regression with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 346-362.
    6. Jia Chen & Degui Li & Oliver Linton & Zudi Lu, 2015. "Semiparametric model averaging of ultra-high dimensional time series," CeMMAP working papers 62/15, Institute for Fiscal Studies.
    7. Chen, Bin & Huang, Liquan, 2018. "Nonparametric testing for smooth structural changes in panel data models," Journal of Econometrics, Elsevier, vol. 202(2), pages 245-267.
    8. Myrto Kasioumi & Thanasis Stengos, 2020. "The Environmental Kuznets Curve with Recycling: A Partially Linear Semiparametric Approach," JRFM, MDPI, vol. 13(11), pages 1-26, November.
    9. Vogt, Michael & Linton, Oliver, 2020. "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, vol. 216(1), pages 305-325.
    10. Badi Baltagi & Georges Bresson & Jean-Michel Etienne, 2020. "Growth Empirics: A Bayesian Semiparametric Model with Random Coefficients for a Panel of OECD Countries," Center for Policy Research Working Papers 229, Center for Policy Research, Maxwell School, Syracuse University.
    11. Jia Chen, 2018. "Estimating Latent Group Structure in Time-Varying Coefficient Panel Data Models," Discussion Papers 18/15, Department of Economics, University of York.
    12. Archer Gong Zhang & Jiahua Chen, 2023. "Optimal Estimation under a Semiparametric Density Ratio Model," Papers 2309.09103, arXiv.org.
    13. Lee, Jungyoon & Robinson, Peter, 2015. "Panel nonparametric regression with fixed effects," LSE Research Online Documents on Economics 61431, London School of Economics and Political Science, LSE Library.
    14. Jiti Gao & Kai Xia, 2017. "Heterogeneous panel data models with cross-sectional dependence," Monash Econometrics and Business Statistics Working Papers 16/17, Monash University, Department of Econometrics and Business Statistics.
    15. Gao, Jiti & Xia, Kai & Zhu, Huanjun, 2020. "Heterogeneous panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 219(2), pages 329-353.
    16. Chen, Jia & Li, Degui & Xia, Yingcun, 2019. "Estimation of a rank-reduced functional-coefficient panel data model with serial correlation," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 456-479.

  57. Hafner C. & Linton, O., 2013. "An Almost Closed Form Estimator for the EGARCH," LIDAM Discussion Papers ISBA 2013010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. CORNUEJOLS, Gérard & WOLSEY, Laurence & YILDIZ, Sercan, 2013. "Sufficiency of cut-generating functions," LIDAM Discussion Papers CORE 2013027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Chiara Canta & Marie-Louise Leroux, 2016. "Public and Private Hospitals, Congestion, and Redistribution," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 18(1), pages 42-66, February.
    3. Bocart, Fabian Y.R.P. & Hafner, Christian, 2015. "Fair Revaluation of Wine as an Investment," LIDAM Reprints ISBA 2015040, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. GOERTZ, Johanna & MANIQUET, François, 2013. "Large elections with multiple alternatives: a Condorcet Jury Theorem and inefficient equilibria," LIDAM Discussion Papers CORE 2013023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Hafner, Christian M. & Linton, Oliver, 2017. "An Almost Closed Form Estimator For The Egarch Model," Econometric Theory, Cambridge University Press, vol. 33(4), pages 1013-1038, August.
    6. MLINAR, Tanja B. & CHEVALIER, Philippe, 2013. "Pooling in manufacturing: do opposites attract?," LIDAM Discussion Papers CORE 2013040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. NESTEROV, Yurii, 2013. "Universal gradient methods for convex optimization problems," LIDAM Discussion Papers CORE 2013026, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

  58. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2013. "A nonparametric test of a strong leverage hypothesis," CeMMAP working papers 28/13, Institute for Fiscal Studies.

    Cited by:

    1. Ekaterina Smetanina, 2017. "Real-Time GARCH," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 561-601.
    2. Horpestad, Jone B. & Lyócsa, Štefan & Molnár, Peter & Olsen, Torbjørn B., 2019. "Asymmetric volatility in equity markets around the world," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 540-554.
    3. Li, Tong & Oka, Tatsushi, 2015. "Set identification of the censored quantile regression model for short panels with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 363-377.
    4. M. MALLIKARJUNA & R. Prabhakara RAO, 2019. "Volatility experience of major world stock markets," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(621), W), pages 35-52, Winter.
    5. Muhammad Surajo Sanusi, 2017. "Investigating the sources of Black’s leverage effect in oil and gas stocks," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1318812-131, January.
    6. Yen, Yu-Min & Yen, Tso-Jung, 2021. "Testing forecast accuracy of expectiles and quantiles with the extremal consistent loss functions," International Journal of Forecasting, Elsevier, vol. 37(2), pages 733-758.

  59. Oliver Linton & Qiying Wang, 2013. "Non-parametric transformation regression with non-stationary data," CeMMAP working papers 16/13, Institute for Fiscal Studies.

    Cited by:

    1. Chaohua Dong & Oliver Linton, 2017. "Additive nonparametric models with time variable and both stationary and nonstationary regressions," CeMMAP working papers 59/17, Institute for Fiscal Studies.
    2. Linton, O. & Xiao, Z., 2019. "Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity," Cambridge Working Papers in Economics 1907, Faculty of Economics, University of Cambridge.
    3. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.
    4. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," LSE Research Online Documents on Economics 103830, London School of Economics and Political Science, LSE Library.
    5. Yuliana Linke & Igor Borisov & Pavel Ruzankin & Vladimir Kutsenko & Elena Yarovaya & Svetlana Shalnova, 2024. "Multivariate Universal Local Linear Kernel Estimators in Nonparametric Regression: Uniform Consistency," Mathematics, MDPI, vol. 12(12), pages 1-23, June.
    6. Wang, Qiying & Wu, Dongsheng & Zhu, Ke, 2018. "Model checks for nonlinear cointegrating regression," Journal of Econometrics, Elsevier, vol. 207(2), pages 261-284.
    7. Yuliana Linke & Igor Borisov & Pavel Ruzankin & Vladimir Kutsenko & Elena Yarovaya & Svetlana Shalnova, 2022. "Universal Local Linear Kernel Estimators in Nonparametric Regression," Mathematics, MDPI, vol. 10(15), pages 1-28, July.
    8. Ayman Mnasri & Zouhair Mrabet & Mouyad Alsamara, 2023. "A new quadratic asymmetric error correction model: does size matter?," Empirical Economics, Springer, vol. 65(1), pages 33-64, July.

  60. Heather Battey & Oliver Linton, 2013. "Nonparametric estimation of multivariate elliptic densities via finite mixture sieves," CeMMAP working papers 15/13, Institute for Fiscal Studies.

    Cited by:

    1. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    2. Linton, O. & Wu, J., 2016. "A coupled component GARCH model for intraday and overnight volatility," Cambridge Working Papers in Economics 1671, Faculty of Economics, University of Cambridge.
    3. Eckhard Liebscher & Wolf-Dieter Richter, 2016. "Estimation of Star-Shaped Distributions," Risks, MDPI, vol. 4(4), pages 1-37, November.
    4. Francq, C. & Jiménez-Gamero, M.D. & Meintanis, S.G., 2017. "Tests for conditional ellipticity in multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 196(2), pages 305-319.

  61. Xiaohong Chen & David Jacho-Chávez & Oliver Linton, 2012. "Averaging of moment condition estimators," CeMMAP working papers 26/12, Institute for Fiscal Studies.

    Cited by:

    1. Martins, Luis F. & Gabriel, Vasco J., 2014. "Linear instrumental variables model averaging estimation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 709-724.

  62. Park, Sujin & Linton, Oliver, 2012. "Estimating the quadratic covariation matrix for an asynchronously observed continuous time signal masked by additive noise," LSE Research Online Documents on Economics 119050, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Bibinger, Markus & Winkelmann, Lars, 2013. "Econometrics of co-jumps in high-frequency data with noise," SFB 649 Discussion Papers 2013-021, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Bibinger, Markus & Winkelmann, Lars, 2015. "Econometrics of co-jumps in high-frequency data with noise," Journal of Econometrics, Elsevier, vol. 184(2), pages 361-378.
    3. Hounyo, Ulrich, 2017. "Bootstrapping integrated covariance matrix estimators in noisy jump–diffusion models with non-synchronous trading," Journal of Econometrics, Elsevier, vol. 197(1), pages 130-152.
    4. Ulrich Hounyo, 2014. "Bootstrapping integrated covariance matrix estimators in noisy jump-diffusion models with non-synchronous trading," CREATES Research Papers 2014-35, Department of Economics and Business Economics, Aarhus University.
    5. Bibinger, Markus & Mykland, Per A., 2013. "Inference for multi-dimensional high-frequency data: Equivalence of methods, central limit theorems, and an application to conditional independence testing," SFB 649 Discussion Papers 2013-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    6. Stefano Peluso & Fulvio Corsi & Antonietta Mira, 2015. "A Bayesian High-Frequency Estimator of the Multivariate Covariance of Noisy and Asynchronous Returns," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 665-697.
    7. Maria Elvira Mancino & Maria Cristina Recchioni, 2015. "Fourier Spot Volatility Estimator: Asymptotic Normality and Efficiency with Liquid and Illiquid High-Frequency Data," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-33, September.

  63. Oliver Linton & Michael Vogt, 2012. "Nonparametric estimation of a periodic sequence in the presence of a smooth trend," CeMMAP working papers 23/12, Institute for Fiscal Studies.

    Cited by:

    1. Michael Vogt & Oliver Linton, 2015. "Classification of nonparametric regression functions in heterogeneous panels," CeMMAP working papers 06/15, Institute for Fiscal Studies.
    2. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    3. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
    4. Seok Young Hong & Oliver Linton & Hui Jun Zhang, 2014. "Multivariate Variance Ratio Statistics," Cambridge Working Papers in Economics 1459, Faculty of Economics, University of Cambridge.
    5. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    6. Liu, Jialuo & Chu, Tingjin & Zhu, Jun & Wang, Haonan, 2021. "Semiparametric method and theory for continuously indexed spatio-temporal processes," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
    7. Vogt, Michael & Linton, Oliver, 2020. "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, vol. 216(1), pages 305-325.
    8. Kai Yang & Peihua Qiu, 2022. "A three-step local smoothing approach for estimating the mean and covariance functions of spatio-temporal Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(1), pages 49-68, February.
    9. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.
    10. Marina Khismatullina & Michael Vogt, 2022. "Multiscale Comparison of Nonparametric Trend Curves," Papers 2209.10841, arXiv.org.

  64. Degui Li & Oliver Linton & Zudi Lu, 2012. "A flexible semiparametric model for time series," CeMMAP working papers 28/12, Institute for Fiscal Studies.

    Cited by:

    1. Francisco Azuero & Jorge Armando Rodr�guez, 2016. "Preservación ambiental de la Amazonia colombiana: retos para la política fiscal," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 35(Especial ), pages 281-313.

  65. Oliver Linton & Yoon-Jae Whang, 2012. "Testing for the stochastic dominance efficiency of a given portfolio," CeMMAP working papers 27/12, Institute for Fiscal Studies.

    Cited by:

    1. Sree Vinutha Venkataraman & S. V. D. Nageswara Rao, 2023. "Stochastic dominance algorithms with application to mutual fund performance evaluation," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 681-698, January.
    2. Stelios Arvanitis & O. Scaillet & Nikolas Topaloglou, 2020. "Spanning analysis of stock market anomalies under Prospect Stochastic Dominance," Swiss Finance Institute Research Paper Series 20-18, Swiss Finance Institute.
    3. Stelios Arvanitis & Mark Hallam & Thierry Post & Nikolas Topaloglou, 2019. "Stochastic Spanning," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(4), pages 573-585, October.
    4. Stelios Arvanitis & O. Scaillet & Nikolas Topaloglou, 2018. "Spanning Tests for Markowitz Stochastic Dominance," Swiss Finance Institute Research Paper Series 18-08, Swiss Finance Institute.
    5. Thierry Post & Iňaki Rodríguez Longarela, 2021. "Risk Arbitrage Opportunities for Stock Index Options," Operations Research, INFORMS, vol. 69(1), pages 100-113, January.
    6. Teng Wah Leo, 2017. "On the asymptotic distribution of (generalized) Lorenz transvariation measures," METRON, Springer;Sapienza Università di Roma, vol. 75(2), pages 195-213, August.
    7. Duc Khuong Nguyen & Nikolas Topaloglou & Thomas Walther, 2020. "Asset Classes and Portfolio Diversification: Evidence from a Stochastic Spanning Approach," Working Papers 2020-009, Department of Research, Ipag Business School.
    8. Thierry Post & Yi Fang & Miloš Kopa, 2015. "Linear Tests for Decreasing Absolute Risk Aversion Stochastic Dominance," Management Science, INFORMS, vol. 61(7), pages 1615-1629, July.
    9. Mehmet Pinar, 2015. "Measuring world governance: revisiting the institutions hypothesis," Empirical Economics, Springer, vol. 48(2), pages 747-778, March.
    10. Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios, 2018. "Portfolio optimization based on stochastic dominance and empirical likelihood," Journal of Econometrics, Elsevier, vol. 206(1), pages 167-186.
    11. Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2020. "On the construction of a feasible range of multidimensional poverty under benchmark weight uncertainty," European Journal of Operational Research, Elsevier, vol. 281(2), pages 415-427.
    12. Stelios Arvanitis, 2015. "Saddle-Type Functionals for Continuous Processes with Applications to Tests for Stochastic Spanning," Working Papers 201509, Athens University Of Economics and Business, Department of Economics.
    13. Thierry Post & Valerio Potì, 2017. "Portfolio Analysis Using Stochastic Dominance, Relative Entropy, and Empirical Likelihood," Management Science, INFORMS, vol. 63(1), pages 153-165, January.
    14. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2022. "Stochastic dominance spanning and augmenting the human development index with institutional quality," Annals of Operations Research, Springer, vol. 315(1), pages 341-369, August.
    15. D. Torre & F. Mendivil & M. Rocca, 2024. "Modeling portfolio efficiency using stochastic optimization with incomplete information and partial uncertainty," Annals of Operations Research, Springer, vol. 334(1), pages 241-263, March.
    16. Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios, 2019. "Robust optimization of forecast combinations," International Journal of Forecasting, Elsevier, vol. 35(3), pages 910-926.
    17. Giovanni Bernardo & Irene Brunetti & Mehmet Pinar & Thanasis Stengos, 2021. "Measuring the presence of organized crime across Italian provinces: a sensitivity analysis," European Journal of Law and Economics, Springer, vol. 51(1), pages 31-95, February.
    18. Kolokolova, Olga & Le Courtois, Olivier & Xu, Xia, 2022. "Is the index efficient? A worldwide tour with stochastic dominance," Journal of Financial Markets, Elsevier, vol. 59(PB).
    19. Stelios Arvanitis & Thierry Post & Nikolas Topaloglou, 2021. "Stochastic Bounds for Reference Sets in Portfolio Analysis," Management Science, INFORMS, vol. 67(12), pages 7737-7754, December.
    20. Charles Beach, 2023. "Quantile Tool Box Measures for Empirical Analysis and for Testing Distributional Comparisons in Direct Distribution-Free Fashion," Working Paper 1508, Economics Department, Queen's University.
    21. Liesiö, Juuso & Xu, Peng & Kuosmanen, Timo, 2020. "Portfolio diversification based on stochastic dominance under incomplete probability information," European Journal of Operational Research, Elsevier, vol. 286(2), pages 755-768.
    22. Liesiö, Juuso & Kallio, Markku & Argyris, Nikolaos, 2023. "Incomplete risk-preference information in portfolio decision analysis," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1084-1098.

  66. Linton, Oliver & Mammen, Enno & Nielsen, Jens Perch & Van Keilegom, Ingrid, 2011. "Nonparametric regression with filtered data," LIDAM Reprints ISBA 2011008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    Cited by:

    1. Stephan M. Bischofberger, 2020. "In-Sample Hazard Forecasting Based on Survival Models with Operational Time," Risks, MDPI, vol. 8(1), pages 1-17, January.
    2. Linton, O. & Xiao, Z., 2019. "Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity," Cambridge Working Papers in Economics 1907, Faculty of Economics, University of Cambridge.
    3. Effraimidis, Georgios, 2016. "Nonparametric Identification of a Time-Varying Frailty Model," DaCHE discussion papers 2016:6, University of Southern Denmark, Dache - Danish Centre for Health Economics.
    4. Sujica, Aleksandar & Van Keilegom, Ingrid, 2018. "The copula-graphic estimator in censored nonparametric location-scale regression models," Econometrics and Statistics, Elsevier, vol. 7(C), pages 89-114.
    5. Gámiz Pérez, M. Luz & Martínez Miranda, María Dolores & Nielsen, Jens Perch, 2013. "Smoothing survival densities in practice," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 368-382.

  67. Efang Kong & Oliver Linton & Yingcun Xia, 2011. "Global Bahadur representation for nonparametric censored regression quantiles and its applications," CeMMAP working papers CWP33/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Eliana Christou & Michael G. Akritas, 2019. "Single index quantile regression for censored data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 655-678, December.
    2. Sungwon Lee & Joon H. Ro, 2020. "Nonparametric Tests for Conditional Quantile Independence with Duration Outcomes," Working Papers 2013, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    3. Matias D. Cattaneo & Yingjie Feng & Boris Shigida, 2024. "Uniform Estimation and Inference for Nonparametric Partitioning-Based M-Estimators," Papers 2409.05715, arXiv.org, revised Aug 2025.
    4. Marcelo Fernandes & Emmanuel Guerre & Eduardo Horta, 2021. "Smoothing Quantile Regressions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 338-357, January.

  68. Degui Li & Zudi Lu & Oliver Linton, 2011. "Local Linear Fitting Under Near Epoch Dependence: Uniform consistency with Convergence Rates," Monash Econometrics and Business Statistics Working Papers 16/11, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.
    2. Jia Chen & Degui Li & Oliver Linton & Zudi Lu, 2015. "Semiparametric dynamic portfolio choice with multiple conditioning variables," CeMMAP working papers CWP07/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Degui Li & Oliver Linton & Zudi Lu, 2012. "A flexible semiparametric model for time series," CeMMAP working papers CWP28/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Yang, Lixiong & Lee, Chingnun & Shie, Fu Shuen, 2014. "How close a relationship does a capital market have with other markets? A reexamination based on the equal variance test," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 198-226.
    5. Jia Chen & Degui Li & Oliver Linton & Zudi Lu, 2015. "Semiparametric model averaging of ultra-high dimensional time series," CeMMAP working papers 62/15, Institute for Fiscal Studies.
    6. Wang, Hanchao & Peng, Bin & Li, Degui & Leng, Chenlei, 2021. "Nonparametric estimation of large covariance matrices with conditional sparsity," Journal of Econometrics, Elsevier, vol. 223(1), pages 53-72.
    7. Lee, Jiyon, 2015. "A semiparametric single index model with heterogeneous impacts on an unobserved variable," Journal of Econometrics, Elsevier, vol. 184(1), pages 13-36.
    8. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.
    9. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    10. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    11. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).
    12. James A. Duffy, 2015. "Uniform Convergence Rates over Maximal Domains in Structural Nonparametric Cointegrating Regression," Economics Papers 2015-W03, Economics Group, Nuffield College, University of Oxford.
    13. Kurisu, Daisuke, 2019. "On nonparametric inference for spatial regression models under domain expanding and infill asymptotics," Statistics & Probability Letters, Elsevier, vol. 154(C), pages 1-1.
    14. Botosaru, Irene & Sasaki, Yuya, 2018. "Nonparametric heteroskedasticity in persistent panel processes: An application to earnings dynamics," Journal of Econometrics, Elsevier, vol. 203(2), pages 283-296.

  69. Bonsoo Koo & Oliver Linton, 2010. "Semiparametric Estimation of Locally Stationary Diffusion Models," STICERD - Econometrics Paper Series 551, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
    2. Michael Vogt, 2012. "Nonparametric regression for locally stationary time series," CeMMAP working papers CWP22/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Aslanidis, Nektarios & Casas, Isabel, 2013. "Nonparametric correlation models for portfolio allocation," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2268-2283.

  70. Alev Atak & Oliver Linton & Zhijie Xiao, 2010. "A Semiparametric Panel Model for unbalanced data with Application to Climate Change in the United Kingdom," Boston College Working Papers in Economics 762, Boston College Department of Economics.

    Cited by:

    1. Annegues, Ana Claudia & Rodrigues de Oliveira, Victor & Souza, Wallace Patrick Santos de Farias, 2017. "Thoughts on the inequality of opportunities: new evidence," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), April.
    2. Zhu, Xiaoqian & Xie, Yongjia & Li, Jianping & Wu, Dengsheng, 2015. "Change point detection for subprime crisis in American banking: From the perspective of risk dependence," International Review of Economics & Finance, Elsevier, vol. 38(C), pages 18-28.
    3. Chen, Zhihong & Xia, Huizhu, 2020. "Trend instrumental variable regression with an application to the US New Keynesian Phillips Curve," Economic Modelling, Elsevier, vol. 93(C), pages 595-604.
    4. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "A semiparametric model for heterogeneous panel data with fixed effects," CeMMAP working papers CWP02/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Jia Chen & Jiti Gao & Degui Li, 2010. "Semiparametric Trending Panel Data Models with Cross-Sectional Dependence," School of Economics and Public Policy Working Papers 2010-10, University of Adelaide, School of Economics and Public Policy.
    6. Michael Vogt & Oliver Linton, 2014. "Nonparametric estimation of a periodic sequence in the presence of a smooth trend," Biometrika, Biometrika Trust, vol. 101(1), pages 121-140.
    7. Chen, Bin & Huang, Liquan, 2018. "Nonparametric testing for smooth structural changes in panel data models," Journal of Econometrics, Elsevier, vol. 202(2), pages 245-267.
    8. Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.
    9. Meng, Xiaochun & Taylor, James W., 2022. "Comparing probabilistic forecasts of the daily minimum and maximum temperature," International Journal of Forecasting, Elsevier, vol. 38(1), pages 267-281.
    10. Javier Hidalgo & Jungyoon Lee, 2014. "A Cusum Test of Common Trends in Large Heterogeneous Panels," STICERD - Econometrics Paper Series 576, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    11. Yonghui Zhang & Liangjun Su & Peter C. B. Phillips, 2012. "Testing for common trends in semi‐parametric panel data models with fixed effects," Econometrics Journal, Royal Economic Society, vol. 15(1), pages 56-100, February.
    12. Xu, Ke-Li, 2016. "Multivariate trend function testing with mixed stationary and integrated disturbances," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 38-57.
    13. Jia Chen & Degui Li & Jiti Gao, 2013. "Non- and Semi-Parametric Panel Data Models: A Selective Review," Monash Econometrics and Business Statistics Working Papers 18/13, Monash University, Department of Econometrics and Business Statistics.
    14. Marina Khismatullina & Michael Vogt, 2022. "Multiscale Comparison of Nonparametric Trend Curves," Papers 2209.10841, arXiv.org.

  71. Oliver Linton & Sorawoot Srisuma, 2010. "Semiparametric Estimation of Markov Decision Processeswith Continuous State Space," STICERD - Econometrics Paper Series 550, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Otsu, Taisuke & Pesendorfer, Martin & Takahashi, Yuya, 2013. "Testing for equilibrium multiplicity in dynamic Markov games," LSE Research Online Documents on Economics 101968, London School of Economics and Political Science, LSE Library.
    2. Victor Aguirregabiria & Allan Collard-Wexler & Stephen P. Ryan, 2021. "Dynamic Games in Empirical Industrial Organization," NBER Working Papers 29291, National Bureau of Economic Research, Inc.
    3. Pesendorfer, Martin & Takahashi, Yuya & Otsu, Taisuke, 2014. "Testing Equilibrium Multiplicity in Dynamic Games," CEPR Discussion Papers 10111, C.E.P.R. Discussion Papers.
    4. Otsu, Taisuke & Pesendorfer, Martin & Takahashi, Yuya, 2016. "Pooling data across markets in dynamic Markov games," LSE Research Online Documents on Economics 66182, London School of Economics and Political Science, LSE Library.
    5. Ariel Neufeld & Julian Sester & Mario v{S}iki'c, 2022. "Markov Decision Processes under Model Uncertainty," Papers 2206.06109, arXiv.org, revised Jan 2023.
    6. Armstrong, Timothy B. & Bertanha, Marinho & Hong, Han, 2014. "A fast resample method for parametric and semiparametric models," Journal of Econometrics, Elsevier, vol. 179(2), pages 128-133.
    7. Otero, Karina V., 2016. "Nonparametric identification of dynamic multinomial choice games: unknown payoffs and shocks without interchangeability," MPRA Paper 86784, University Library of Munich, Germany.
    8. Otsu, Taisuke & Pesendorfer, Martin, 2023. "Equilibrium multiplicity in dynamic games: testing and estimation," LSE Research Online Documents on Economics 113588, London School of Economics and Political Science, LSE Library.
    9. Hiroyuki Kasahara & Katsumi Shimotsu, 2018. "Estimation of Discrete Choice Dynamic Programming Models," The Japanese Economic Review, Springer, vol. 69(1), pages 28-58, March.
    10. Truquet, Lionel, 2023. "Strong mixing properties of discrete-valued time series with exogenous covariates," Stochastic Processes and their Applications, Elsevier, vol. 160(C), pages 294-317.
    11. Jason R. Blevins & Wei Shi & Donald R. Haurin & Stephanie Moulton, 2020. "A Dynamic Discrete Choice Model Of Reverse Mortgage Borrower Behavior," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 61(4), pages 1437-1477, November.
    12. Komarova, Tatiana & Sanches, Fábio & Silva Junior, Daniel & Srisuma, Sorawoot, 2018. "Joint analysis of the discount factor and payoff parameters in dynamic discrete choice games," LSE Research Online Documents on Economics 86858, London School of Economics and Political Science, LSE Library.
    13. Cheng Chou & Geert Ridder & Ruoyao Shi, 2024. "Identification and Estimation of Nonstationary Dynamic Binary Choice Models," Working Papers 202402, University of California at Riverside, Department of Economics.
    14. Taisuke Otsu & Martin Pesendorfer, 2023. "Equilibrium multiplicity in dynamic games: Testing and estimation," The Econometrics Journal, Royal Economic Society, vol. 26(1), pages 26-42.
    15. Fabio A. Miessi Sanches & Daniel Silva Junior, Sorawoot Srisuma, 2014. "Ordinary Least Squares Estimation for a Dynamic Game," Working Papers, Department of Economics 2014_19, University of São Paulo (FEA-USP), revised 23 Feb 2015.
    16. Ariel Neufeld & Julian Sester & Mario Šikić, 2023. "Markov decision processes under model uncertainty," Mathematical Finance, Wiley Blackwell, vol. 33(3), pages 618-665, July.
    17. Buchholz, Nicholas & Shum, Matthew & Xu, Haiqing, 2021. "Semiparametric estimation of dynamic discrete choice models," Journal of Econometrics, Elsevier, vol. 223(2), pages 312-327.
    18. Sears, Louis S. & Lin Lawell, C.-Y. Cynthia & Walter, M. Todd, 2020. "Groundwater Under Open Access: A Structural Model of the Dynamic Common Pool Extraction Game," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304276, Agricultural and Applied Economics Association.

  72. Wolfgang Härdle & Oliver Linton & Yingcun Xia, 2009. "Optimal Smoothing for a Computationallyand StatisticallyEfficient Single Index Estimator," STICERD - Econometrics Paper Series 537, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Strausz, Roland, 2009. "The political economy of regulatory risk," SFB 649 Discussion Papers 2009-040, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Michal Grajek & Lars-Hendrik Röller, 2009. "Regulation and investment in network industries: Evidence from European telecoms," ESMT Research Working Papers ESMT-09-004, ESMT European School of Management and Technology.
    3. Choroś, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2009. "CDO and HAC," SFB 649 Discussion Papers 2009-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Chuan Goh, 2009. "Bootstrap-based Bandwidth Selection for Semiparametric Generalized Regression Estimators," Working Papers tecipa-375, University of Toronto, Department of Economics.
    5. Grith, Maria & Härdle, Wolfgang Karl & Park, Juhyun, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers 2009-041, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  73. Linton, Oliver & Song, Kyungchul & Whang, Yoon-Jae, 2009. "An improved bootstrap test of stochastic dominance," UC3M Working papers. Economics we094827, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Yoichi Arai & Yu-Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2021. "Testing identifying assumptions in fuzzy regression discontinuity designs," CeMMAP working papers CWP16/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Toru Kitagawa & Aleksey Tetenov, 2018. "Who Should Be Treated? Empirical Welfare Maximization Methods for Treatment Choice," Econometrica, Econometric Society, vol. 86(2), pages 591-616, March.
    3. Linton, Oliver & Seo, Myung Hwan & Whang, Yoon-Jae, 2023. "Testing stochastic dominance with many conditioning variables," Journal of Econometrics, Elsevier, vol. 235(2), pages 507-527.
    4. Arvanitis, Stelios & Post, Thierry & Potì, Valerio & Karabati, Selcuk, 2021. "Nonparametric tests for Optimal Predictive Ability," International Journal of Forecasting, Elsevier, vol. 37(2), pages 881-898.
    5. Sokbae (Simon) Lee & Kyungchui (Kevin) Song & Yoon-Jae Whang, 2014. "Testing for a general class of functional inequalities," CeMMAP working papers CWP09/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Donald W.K. Andrews & Xiaoxia Shi, 2010. "Inference Based on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1761R2, Cowles Foundation for Research in Economics, Yale University, revised May 2012.
    7. Wei Zhao & David M. Kaplan, 2023. "Conditions for Extrapolating Differences in Consumption to Differences in Welfare," Working Papers 2307, Department of Economics, University of Missouri.
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  74. Christian M. Hafner & Oliver Linton, 2009. "Efficient Estimation of a Multivariate Multiplicative Volatility Model," STICERD - Econometrics Paper Series 541, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

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    1. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    2. Michael Vogt, 2012. "Nonparametric regression for locally stationary time series," CeMMAP working papers CWP22/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Yulia Kotlyarova & Marcia M Schafgans & Victoria Zinde-Walsh, 2011. "Adapting Kernel Estimation to Uncertain Smoothness," STICERD - Econometrics Paper Series 557, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    4. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    5. Jia Chen & Degui Li & Yuning Li & Oliver Linton, 2023. "Estimating Time-Varying Networks for High-Dimensional Time Series," Papers 2302.02476, arXiv.org.
    6. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    7. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
    8. Khismatullina, Marina & Vogt, Michael, 2023. "Nonparametric comparison of epidemic time trends: The case of COVID-19," Journal of Econometrics, Elsevier, vol. 232(1), pages 87-108.
    9. Valentin Patilea & Hamdi Raïssi, 2014. "Testing Second-Order Dynamics for Autoregressive Processes in Presence of Time-Varying Variance," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1099-1111, September.
    10. Quentin Giai Gianetto & Hamdi Raïssi, 2015. "Testing Instantaneous Causality in Presence of Nonconstant Unconditional Covariance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 46-53, January.
    11. Cristina Amado & Annastiina Silvennoinen & Timo Ter¨asvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," NIPE Working Papers 07/2018, NIPE - Universidade do Minho.
    12. Matthieu Garcin & Clément Goulet, 2015. "Non-parameteric news impact curve: a variational approach," Documents de travail du Centre d'Economie de la Sorbonne 15086r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Jul 2016.
    13. Hafner, C. M., 2022. "Dynamic Autoregressive Liquidity (DArLiQ)," Cambridge Working Papers in Economics 2214, Faculty of Economics, University of Cambridge.
    14. Audrino, Francesco, 2011. "Forecasting correlations during the late-2000s financial crisis: short-run component, long-run component, and structural breaks," Economics Working Paper Series 1112, University of St. Gallen, School of Economics and Political Science.
    15. Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI & Luc BAUWENS, Manuela BRAIONE and Giuseppe STORTI, 2017. "A dynamic component model for forecasting high-dimensional realized covariance matrices," LIDAM Reprints CORE 2812, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    17. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    18. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    19. Campos-Martins, Susana & Amado, Cristina, 2025. "Modelling dynamic interdependence in nonstationary variances with an application to carbon markets," Journal of Economic Dynamics and Control, Elsevier, vol. 173(C).
    20. Proietti, Tommaso, 2014. "Exponential Smoothing, Long Memory and Volatility Prediction," MPRA Paper 57230, University Library of Munich, Germany.
    21. BAUWENS, Luc & HAFNER, Christian & pierret, Diane, 2011. "Multivariate volatility modeling of electricity futures," LIDAM Discussion Papers CORE 2011011, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    22. López Cabrera, Brenda & Schulz, Franziska, 2016. "Volatility linkages between energy and agricultural commodity prices," Energy Economics, Elsevier, vol. 54(C), pages 190-203.
    23. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    24. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    25. Dark, Jonathan, 2024. "An adaptive long memory conditional correlation model," Journal of Empirical Finance, Elsevier, vol. 75(C).
    26. Golosnoy, Vasyl & Gribisch, Bastian & Liesenfeld, Roman, 2010. "The conditional autoregressive wishart model for multivariate stock market volatility," Economics Working Papers 2010-07, Christian-Albrechts-University of Kiel, Department of Economics.
    27. Feiyu Jiang & Dong Li & Ke Zhu, 2019. "Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model," Papers 1907.04147, arXiv.org, revised Oct 2020.
    28. Geert Dhaene & Piet Sercu & Jianbin Wu, 2022. "Volatility spillovers: A sparse multivariate GARCH approach with an application to commodity markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(5), pages 868-887, May.
    29. BAUWENS, Luc & BRAIONE, Manuela & STORTI, Giuseppe, 2016. "Multiplicative Conditional Correlation Models for Realized Covariance Matrices," LIDAM Discussion Papers CORE 2016041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    30. Francisco Blasques & Enzo D'Innocenzo & Siem Jan Koopman, 2021. "Common and Idiosyncratic Conditional Volatility Factors: Theory and Empirical Evidence," Tinbergen Institute Discussion Papers 21-057/III, Tinbergen Institute.
    31. Golosnoy, Vasyl & Schmid, Wolfgang & Seifert, Miriam Isabel & Lazariv, Taras, 2020. "Statistical inferences for realized portfolio weights," Econometrics and Statistics, Elsevier, vol. 14(C), pages 49-62.
    32. Conrad, Christian & Stuermer, Karin, 2017. "On the economic determinants of optimal stock-bond portfolios: international evidence," Working Papers 0636, University of Heidelberg, Department of Economics.
    33. Matthieu Garcin & Clément Goulet, 2015. "Non-parameteric news impact curve: a variational approach," Documents de travail du Centre d'Economie de la Sorbonne 15086rr, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Feb 2017.
    34. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    35. Acatrinei, Marius & Gorun, Adrian & Marcu, Nicu, 2013. "A DCC-GARCH Model To Estimate the Risk to the Capital Market in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 136-148, March.
    36. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.
    37. Erhua Zhang & Xiaojun Song & Jilin Wu, 2022. "A non‐parametric test for multi‐variate trend functions," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(6), pages 856-871, November.
    38. Jiang, Feiyu & Li, Dong & Zhu, Ke, 2021. "Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model," Journal of Econometrics, Elsevier, vol. 224(2), pages 306-329.
    39. Yuanyuan Zhang & Rong Liu & Qin Shao & Lijian Yang, 2020. "Two‐Step Estimation for Time Varying Arch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 551-570, July.

  75. Oliver Linton & Søren Feodor Nielsen & Jens Perch Nielsen, 2009. "Nonparametric Regression with a Latent Time Series," STICERD - Econometrics Paper Series 538, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

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    1. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "A semiparametric model for heterogeneous panel data with fixed effects," CeMMAP working papers CWP02/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Buch-Kromann, Tine & Guillén, Montserrat & Linton, Oliver & Nielsen, Jens Perch, 2011. "Multivariate density estimation using dimension reducing information and tail flattening transformations," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 99-110, January.
    3. Dursun Aydın & Ersin Yılmaz, 2021. "Semiparametric modeling of the right-censored time-series based on different censorship solution techniques," Empirical Economics, Springer, vol. 61(4), pages 2143-2172, October.
    4. Mammen, Enno & Park, Byeong U. & Schienle, Melanie, 2012. "Additive models: Extensions and related models," SFB 649 Discussion Papers 2012-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  76. Woocheol Kim & Oliver Linton, 2009. "Estimation Of A Semiparametricigarch(1,1) Model," STICERD - Econometrics Paper Series 539, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

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    1. Strohsal, Till & Weber, Enzo, 2011. "Mean-variance cointegration and the expectations hypothesis," SFB 649 Discussion Papers 2011-007, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  77. Xiaohong Chen & David T. Jacho-Chávez & Oliver Linton, 2009. "An Alternative Way of ComputingEfficient Instrumental VariableEstimators," STICERD - Econometrics Paper Series 536, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

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    1. Neil Shephard & Kevin Sheppard & Robert F. Engle, 2008. "Fitting vast dimensional time-varying covariance models," Economics Series Working Papers 403, University of Oxford, Department of Economics.
    2. Yves Dominicy & Hiroaki Ogata & David Veredas, 2013. "Inference for vast dimensional elliptical distributions," Computational Statistics, Springer, vol. 28(4), pages 1853-1880, August.
    3. Carrasco, Marine, 2012. "A regularization approach to the many instruments problem," Journal of Econometrics, Elsevier, vol. 170(2), pages 383-398.
    4. DiTraglia, Francis J., 2016. "Using invalid instruments on purpose: Focused moment selection and averaging for GMM," Journal of Econometrics, Elsevier, vol. 195(2), pages 187-208.
    5. Sla{dj}ana Babi'c & Christophe Ley & Lorenzo Ricci & David Veredas, 2020. "TailCoR," Papers 2011.14817, arXiv.org.
    6. Francis J. DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, Second Version," PIER Working Paper Archive 14-045, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 09 Dec 2014.
    7. Francis DiTraglia, 2011. "Using Invalid Instruments on Purpose: Focused Moment Selection and Averaging for GMM, Second Version," PIER Working Paper Archive 15-027, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 10 Aug 2015.

  78. Efang Kong & Oliver Linton & Yingcun Xia, 2009. "Uniform Bahadur Representation for LocalPolynomial Estimates of M-Regressionand Its Application to The Additive Model," STICERD - Econometrics Paper Series 535, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Clément de Chaisemartin & Xavier d'Haultfœuille & Gonzalo Vazquez-Bare, 2024. "Difference-in-Difference Estimators with Continuous Treatments and No Stayers," Post-Print hal-04888940, HAL.
    2. Victor Chernozhukov & Sokbae Lee & Adam M. Rosen, 2013. "Intersection Bounds: Estimation and Inference," Econometrica, Econometric Society, vol. 81(2), pages 667-737, March.
    3. Graciela Boente & Alejandra Martínez, 2017. "Marginal integration M-estimators for additive models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 231-260, June.
    4. Song, Song & Ritov, Ya’acov & Härdle, Wolfgang K., 2012. "Bootstrap confidence bands and partial linear quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 244-262.
    5. Shin Kanaya, 2015. "Uniform Convergence Rates of Kernel-Based Nonparametric Estimators for Continuous Time Diffusion Processes: A Damping Function Approach," CREATES Research Papers 2015-50, Department of Economics and Business Economics, Aarhus University.
    6. Chiang, Harold D. & Hsu, Yu-Chin & Sasaki, Yuya, 2019. "Robust uniform inference for quantile treatment effects in regression discontinuity designs," Journal of Econometrics, Elsevier, vol. 211(2), pages 589-618.
    7. Härdle, Wolfgang Karl & Ritov, Ya'acov & Wang, Weining, 2013. "Tie the straps: Uniform bootstrap con fidence bands for bounded influence curve estimators," SFB 649 Discussion Papers 2013-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. Haoze Hou & Wei Huang & Zheng Zhang, 2025. "Non-parametric Quantile Regression and Uniform Inference with Unknown Error Distribution," Papers 2504.01761, arXiv.org.
    9. Henry, Marc & Méango, Romuald & Mourifié, Ismaël, 2024. "Role models and revealed gender-specific costs of STEM in an extended Roy model of major choice," Journal of Econometrics, Elsevier, vol. 238(2).
    10. Härdle, Wolfgang Karl & Ritov, Ya'acov & Song, Song, 2010. "Partial linear quantile regression and bootstrap confidence bands," SFB 649 Discussion Papers 2010-002, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    11. Debopam Bhattacharya & Pascaline Dupas & Shin Kanaya, 2013. "Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets," Economics Series Working Papers 646, University of Oxford, Department of Economics.
    12. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Iv'an Fern'andez-Val, 2011. "Conditional Quantile Processes based on Series or Many Regressors," Papers 1105.6154, arXiv.org, revised Aug 2018.
    13. Jia-Young Michael Fu & Joel L. Horowitz & Matthias Parey, 2015. "Testing exogeneity in nonparametric instrumental variables identified by conditional quantile restrictions," CeMMAP working papers CWP68/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Pedro H. C. Sant'Anna & Qi Xu, 2023. "Difference-in-Differences with Compositional Changes," Papers 2304.13925, arXiv.org, revised Nov 2025.
    15. Sarnetzki, Florian & Dzemski, Andreas, 2014. "Overidentification test in a nonparametric treatment model with unobserved heterogeneity," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100620, Verein für Socialpolitik / German Economic Association.
    16. Pavel Boček & Miroslav Šiman, 2017. "On weighted and locally polynomial directional quantile regression," Computational Statistics, Springer, vol. 32(3), pages 929-946, September.
    17. Gerard, François & Rokkanen, Miikka & Rothe, Christoph, 2016. "Identification and Inference in Regression Discontinuity Designs with a Manipulated Running Variable," CEPR Discussion Papers 11048, C.E.P.R. Discussion Papers.
    18. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2011. "Semiparametric Estimation with Generated Covariates," IZA Discussion Papers 6084, Institute of Labor Economics (IZA).
    19. Matias D. Cattaneo & Richard K. Crump & Max H. Farrell & Yingjie Feng, 2024. "Nonlinear Binscatter Methods," Papers 2407.15276, arXiv.org.
    20. Qu, Zhongjun & Yoon, Jungmo, 2015. "Nonparametric estimation and inference on conditional quantile processes," Journal of Econometrics, Elsevier, vol. 185(1), pages 1-19.
    21. Mammen, Enno & Van Keilegom, Ingrid & Yu, Kyusang, 2013. "Expansion for Moments of Regression Quantiles with Applications to Nonparametric Testing," LIDAM Discussion Papers ISBA 2013027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    22. Koo, Bonsoo & Linton, Oliver, 2015. "Let’S Get Lade: Robust Estimation Of Semiparametric Multiplicative Volatility Models," Econometric Theory, Cambridge University Press, vol. 31(4), pages 671-702, August.
    23. Timothy B. Armstrong & Shu Shen, 2023. "Inference on optimal treatment assignments," The Japanese Economic Review, Springer, vol. 74(4), pages 471-500, October.
    24. Christou, Eliana & Akritas, Michael G., 2016. "Single index quantile regression for heteroscedastic data," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 169-182.
    25. Chiang, Harold D. & Sasaki, Yuya, 2019. "Causal inference by quantile regression kink designs," Journal of Econometrics, Elsevier, vol. 210(2), pages 405-433.
    26. Haitian Xie, 2021. "Uniform Convergence Results for the Local Linear Regression Estimation of the Conditional Distribution," Papers 2112.08546, arXiv.org, revised Jun 2023.
    27. Laura Liu & Alexandre Poirier & Ji-Liang Shiu, 2021. "Identification and Estimation of Partial Effects in Nonlinear Semiparametric Panel Models," Papers 2105.12891, arXiv.org, revised Jul 2024.
    28. Laurent Davezies & Xavier D’Haultfoeuille & Louise Laage, 2025. "Identification and Estimation of Average Causal Effects in Fixed Effects Logit Models," Working Papers 2025-02, Center for Research in Economics and Statistics.
    29. Zongwu Cai & Ying Fang & Ming Lin & Shengfang Tang, 2020. "Inferences for Partially Conditional Quantile Treatment Effect Model," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202005, University of Kansas, Department of Economics, revised Feb 2020.
    30. Yixiao Sun & Haitian Xie & Yuhang Zhang, 2025. "Difference-in-Differences Meets Synthetic Control: Doubly Robust Identification and Estimation," Papers 2503.11375, arXiv.org, revised Sep 2025.
    31. Cl'ement de Chaisemartin & Xavier D'Haultf{oe}uille & Gonzalo Vazquez-Bare, 2024. "Difference-in-Differences Estimators with Continuous Treatments and no Stayers," Papers 2402.05432, arXiv.org.
    32. Emmanuel Guerre & Camille Sabbah, 2009. "Uniform Bias Study and Bahadur Representation for Local Polynomial Estimators of the Conditional Quantile Function," Working Papers 648, Queen Mary University of London, School of Economics and Finance.
    33. Marc Hallin & Zudi Lu & Davy Paindaveine & Miroslav Siman, 2012. "Local Constant and Local Bilinear Multiple-Output Quantile Regression," Working Papers ECARES ECARES 2012-003, ULB -- Universite Libre de Bruxelles.
    34. Härdle, Wolfgang Karl & Ritov, Ya’acov & Wang, Weining, 2015. "Tie the straps: Uniform bootstrap confidence bands for semiparametric additive models," Journal of Multivariate Analysis, Elsevier, vol. 134(C), pages 129-145.
    35. Fan, Yanqin & Guerre, Emmanuel & Zhu, Dongming, 2017. "Partial identification of functionals of the joint distribution of “potential outcomes”," Journal of Econometrics, Elsevier, vol. 197(1), pages 42-59.
    36. Rothe, Christoph & Firpo, Sergio, 2013. "Semiparametric Estimation and Inference Using Doubly Robust Moment Conditions," IZA Discussion Papers 7564, Institute of Labor Economics (IZA).
    37. Bravo, Francesco & Chu, Ba & Jacho-Chavez, David, 2013. "Semiparametric estimation of moment condition models with weakly dependent data," MPRA Paper 79686, University Library of Munich, Germany, revised 2016.
    38. Zongwu Cai & Xiyuan Liu, 2020. "A Functional-Coefficient VAR Model for Dynamic Quantiles with Constructing Financial Network," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202017, University of Kansas, Department of Economics, revised Oct 2020.
    39. Härdle, Wolfgang K. & Song, Song, 2010. "Confidence Bands In Quantile Regression," Econometric Theory, Cambridge University Press, vol. 26(4), pages 1180-1200, August.
    40. Härdle, Wolfgang Karl & Wang, Weining & Yu, Lining, 2016. "TENET: Tail-Event driven NETwork risk," Journal of Econometrics, Elsevier, vol. 192(2), pages 499-513.
    41. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.
    42. Juan Carlos Escanciano, 2020. "Uniform Rates for Kernel Estimators of Weakly Dependent Data," Papers 2005.09951, arXiv.org.
    43. Shih-Kang Chao & Katharina Proksch & Holger Dette & Wolfgang Karl Härdle, 2017. "Confidence Corridors for Multivariate Generalized Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(1), pages 70-85, January.
    44. Cizek, Pavel & Sadikoglu, Serhan, 2022. "Nonseparable Panel Models with Index Structure and Correlated Random Effects," Discussion Paper 2022-009, Tilburg University, Center for Economic Research.
    45. Härdle, Wolfgang Karl & Spokoiny, Vladimir & Wang, Weining, 2010. "Local quantile regression," SFB 649 Discussion Papers 2011-005, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    46. Yingying DONG & Ying-Ying LEE & Michael GOU, 2019. "Regression Discontinuity Designs with a Continuous Treatment," Discussion papers 19058, Research Institute of Economy, Trade and Industry (RIETI).
    47. Eliana Christou & Annabel Settle & Andreas Artemiou, 2021. "Nonlinear dimension reduction for conditional quantiles," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(4), pages 937-956, December.
    48. Li, Jialiang & Zhang, Wenyang & Kong, Efang, 2018. "Factor models for asset returns based on transformed factors," Journal of Econometrics, Elsevier, vol. 207(2), pages 432-448.
    49. Cattaneo, Matias D. & Farrell, Max H., 2013. "Optimal convergence rates, Bahadur representation, and asymptotic normality of partitioning estimators," Journal of Econometrics, Elsevier, vol. 174(2), pages 127-143.
    50. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2010. "Nonparametric regression with nonparametrically generated covariates," SFB 649 Discussion Papers 2010-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    51. Efang Kong & Oliver Linton & Yingcun Xia, 2011. "Global Bahadur representation for nonparametric censored regression quantiles and its applications," CeMMAP working papers CWP33/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    52. Daniel Hlubinka & Lukáš Kotík & Miroslav Šiman, 2022. "Multivariate quantiles with both overall and directional probability interpretation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1586-1604, December.
    53. Noh, Hohsuk & El Ghouch, Anouar & Van Keilegom, Ingrid, 2011. "Quality of fit measures in the framework of quantile regression," LIDAM Discussion Papers ISBA 2011025, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  79. Iglesias, Emma M. & Linton, Oliver, 2009. "Estimation of tail thickness parameters from GJR-GARCH models," UC3M Working papers. Economics we094726, Universidad Carlos III de Madrid. Departamento de Economía.

    Cited by:

    1. Iglesias, Emma M., 2015. "Value at Risk of the main stock market indexes in the European Union (2000–2012)," Journal of Policy Modeling, Elsevier, vol. 37(1), pages 1-13.
    2. Ngai Chan & Liang Peng & Rongmao Zhang, 2012. "Interval estimation of the tail index of a GARCH(1,1) model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 546-565, September.
    3. Degiannakis, Stavros & Floros, Christos & Livada, Alexandra, 2012. "Evaluating Value-at-Risk Models before and after the Financial Crisis of 2008: International Evidence," MPRA Paper 80463, University Library of Munich, Germany.
    4. Beran, Jan & Schell, Dieter, 2012. "On robust tail index estimation," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3430-3443.
    5. Emma M. Iglesias, 2012. "An analysis of extreme movements of exchange rates of the main currencies traded in the Foreign Exchange market," Applied Economics, Taylor & Francis Journals, vol. 44(35), pages 4631-4637, December.
    6. Iglesias, Emma M., 2015. "Value at Risk and expected shortfall of firms in the main European Union stock market indexes: A detailed analysis by economic sectors and geographical situation," Economic Modelling, Elsevier, vol. 50(C), pages 1-8.
    7. Emma M. Iglesias & Mar�a Dolores Lagoa Varela, 2012. "Extreme movements of the main stocks traded in the Eurozone: an analysis by sectors in the 2000's decade," Applied Financial Economics, Taylor & Francis Journals, vol. 22(24), pages 2085-2100, December.

  80. Gordon Anderson & Oliver Linton & Yoon-Jae Whang, 2009. "Nonparametric Estimation of a Polarization Measure," STICERD - Econometrics Paper Series 534, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Gordon Anderson & Teng Wah Leo & Oliver Linton, 2010. "Making Inferences About Rich Country - Poor Country Convergence: The Polarization Trapezoid and Overlap measures," Working Papers tecipa-387, University of Toronto, Department of Economics.
    2. Gordon Anderson & Kinda Hachem, 2009. "Institutions and Economic Outcomes: A Dominance Based Analysis of Causality and Multivariate Welfare With Discrete and Continuous Variables," Working Papers tecipa-378, University of Toronto, Department of Economics.
    3. Sokbae (Simon) Lee & Yoon-Jae Whang, 2009. "Nonparametric tests of conditional treatment effects," CeMMAP working papers CWP36/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Gordon Anderson & Oliver Linton & Teng Leo, 2012. "A polarization-cohesion perspective on cross-country convergence," Journal of Economic Growth, Springer, vol. 17(1), pages 49-69, March.
    5. Hani M. Samawi & Amal Helu & Robert Vogel, 2011. "A nonparametric test of symmetry based on the overlapping coefficient," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(5), pages 885-898, February.
    6. Gordon Anderson, 2010. "Polarization Of The Poor: Multivariate Relative Poverty Measurement Sans Frontiers," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(1), pages 84-101, March.
    7. Amal Helu & Hani Samawi & Robert Vogel, 2011. "Nonparametric overlap coefficient estimation using ranked set sampling," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 385-397.
    8. Maria Grazia Pittau & Roberto Zelli & Paul A. Johnson, 2010. "Mixture Models, Convergence Clubs, And Polarization," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(1), pages 102-122, March.

  81. Xia, Yingcun & Härdle, Wolfgang Karl & Linton, Oliver, 2009. "Optimal smoothing for a computationally and statistically efficient single index estimator," SFB 649 Discussion Papers 2009-028, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

    Cited by:

    1. Strausz, Roland, 2009. "The political economy of regulatory risk," SFB 649 Discussion Papers 2009-040, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    2. Michal Grajek & Lars-Hendrik Röller, 2009. "Regulation and investment in network industries: Evidence from European telecoms," ESMT Research Working Papers ESMT-09-004, ESMT European School of Management and Technology.
    3. Choroś, Barbara & Härdle, Wolfgang Karl & Okhrin, Ostap, 2009. "CDO and HAC," SFB 649 Discussion Papers 2009-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Chuan Goh, 2009. "Bootstrap-based Bandwidth Selection for Semiparametric Generalized Regression Estimators," Working Papers tecipa-375, University of Toronto, Department of Economics.
    5. Grith, Maria & Härdle, Wolfgang Karl & Park, Juhyun, 2009. "Shape invariant modelling pricing kernels and risk aversion," SFB 649 Discussion Papers 2009-041, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  82. Wagner P. Gaglianone & Luiz Renato Lima & Oliver Linton, 2008. "Evaluating Value-at-Risk Models via Quantile Regressions," Working Papers Series 161, Central Bank of Brazil, Research Department.

    Cited by:

    1. Nowotarski, Jakub & Weron, Rafał, 2018. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
    2. Nupur Moni Das & Bhabani Sankar Rout, 2024. "Equity Price Risk of Commercial Banks in India," Arthaniti: Journal of Economic Theory and Practice, , vol. 23(2), pages 179-201, December.
    3. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    4. Zongwu Cai & Haiqiang Chen & Xiaosai Liao, 2020. "A New Robust Inference for Predictive Quantile Regression," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202002, University of Kansas, Department of Economics, revised Feb 2020.
    5. Steven Kou & Xianhua Peng, 2014. "On the Measurement of Economic Tail Risk," Papers 1401.4787, arXiv.org, revised Aug 2015.
    6. So Yeon Chun & Alexander Shapiro & Stan Uryasev, 2012. "Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics," Operations Research, INFORMS, vol. 60(4), pages 739-756, August.
    7. Jenq-Tzong Shiau & Jia-Wei Lin, 2016. "Clustering Quantile Regression-Based Drought Trends in Taiwan," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(3), pages 1053-1069, February.
    8. Sullivan Hu'e & Christophe Hurlin & Yang Lu, 2024. "Backtesting Expected Shortfall: Accounting for both duration and severity with bivariate orthogonal polynomials," Papers 2405.02012, arXiv.org, revised May 2024.
    9. Benjamin R. Auer & Benjamin Mögel, 2016. "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series 6288, CESifo.
    10. Jenq-Tzong Shiau & Ting-Ju Chen, 2015. "Quantile Regression-Based Probabilistic Estimation Scheme for Daily and Annual Suspended Sediment Loads," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2805-2818, June.
    11. Erik Kole & Thijs Markwat & Anne Opschoor & Dick van Dijk, 2017. "Forecasting Value-at-Risk under Temporal and Portfolio Aggregation," Journal of Financial Econometrics, Oxford University Press, vol. 15(4), pages 649-677.
    12. Tjeerd de Vries, 2021. "A Tale of Two Tails: A Model-free Approach to Estimating Disaster Risk Premia and Testing Asset Pricing Models," Papers 2105.08208, arXiv.org, revised Oct 2023.
    13. Timo Dimitriadis & iaochun Liu & Julie Schnaitmann, 2023. "Encompassing Tests for Value at Risk and Expected Shortfall Multistep Forecasts Based on Inference on the Boundary," Journal of Financial Econometrics, Oxford University Press, vol. 21(2), pages 412-444.
    14. Sebastian Bayer & Timo Dimitriadis, 2018. "Regression Based Expected Shortfall Backtesting," Papers 1801.04112, arXiv.org, revised Sep 2019.
    15. Emese Lazar & Ning Zhang, 2017. "Model Risk of Expected Shortfall," ICMA Centre Discussion Papers in Finance icma-dp2017-10, Henley Business School, University of Reading.
    16. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    17. Zhu, Xuening & Wang, Weining & Wang, Hansheng & Härdle, Wolfgang Karl, 2019. "Network quantile autoregression," Journal of Econometrics, Elsevier, vol. 212(1), pages 345-358.
    18. Bonga-Bonga, Lumengo & Manguzvane, Mathias Mandla, 2018. "Assessing the extent of contagion of sovereign credit risk among BRICS countries," MPRA Paper 89200, University Library of Munich, Germany.
    19. Wang, Jying-Nan & Du, Jiangze & Hsu, Yuan-Teng, 2018. "Measuring long-term tail risk: Evaluating the performance of the square-root-of-time rule," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 120-138.
    20. Ophélie Couperier & Jérémy Leymarie, 2020. "Backtesting Expected Shortfall via Multi-Quantile Regression," Working Papers halshs-01909375, HAL.
    21. Christophe Boucher & Jon Danielsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk Model-at-Risk," Post-Print hal-01386003, HAL.
    22. Hotta, Luiz Koodi & Trucíos Maza, Carlos César & Pereira, Pedro L. Valls & Zevallos Herencia, Mauricio Henrique, 2024. "Forecasting VaR and ES through Markov-switching GARCH models: does the specication matter?," Textos para discussão 567, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    23. David Kohns & Tibor Szendrei, 2020. "Horseshoe Prior Bayesian Quantile Regression," Papers 2006.07655, arXiv.org, revised Mar 2021.
    24. Marius Galabe Sampid & Haslifah M Hasim & Hongsheng Dai, 2018. "Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-33, June.
    25. Karim, Sitara & Husain, Afzol & Lim, Weng Marc & Chan, Ling-Foon & Tehseen, Shehnaz, 2024. "AI, FinTech and clean minerals: A wavelet analysis and quantile value-at-risk investigation," Resources Policy, Elsevier, vol. 99(C).
    26. Yannick Hoga & Christian Schulz, 2025. "Self-Normalized Inference in (Quantile, Expected Shortfall) Regressions for Time Series," Papers 2502.10065, arXiv.org, revised Jun 2025.
    27. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    28. Gaglianone, Wagner Piazza & Issler, João Victor, 2015. "Microfounded forecasting," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 766, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    29. Bruno Ferreira Frascaroli & Wellington Charles Lacerda Nobrega, 2019. "Inflation Targeting and Inflation Risk in Latin America," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(11), pages 2389-2408, September.
    30. Laura Garcia-Jorcano & Lidia Sanchis-Marco, 2023. "Measuring Systemic Risk Using Multivariate Quantile-Located ES Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(1), pages 1-72.
    31. Karmakar, Madhusudan & Paul, Samit, 2019. "Intraday portfolio risk management using VaR and CVaR:A CGARCH-EVT-Copula approach," International Journal of Forecasting, Elsevier, vol. 35(2), pages 699-709.
    32. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying – the case of multivariate GARCH models," Economics Working Paper Series 1517, University of St. Gallen, School of Economics and Political Science.
    33. Timo Dimitriadis & Andrew J. Patton & Patrick W. Schmidt, 2019. "Testing Forecast Rationality for Measures of Central Tendency," Papers 1910.12545, arXiv.org, revised Jul 2024.
    34. Liu Xiaochun & Luger Richard, 2018. "Markov-switching quantile autoregression: a Gibbs sampling approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(2), pages 1, April.
    35. Mr. Germán López-Espinosa & Mr. Antonio Rubia & Ms. Laura Valderrama & Mr. Antonio Moreno, 2012. "Systemic Risk and Asymmetric Responses in the Financial Industry," IMF Working Papers 2012/152, International Monetary Fund.
    36. Taylor, James W., 2022. "Forecasting Value at Risk and expected shortfall using a model with a dynamic omega ratio," Journal of Banking & Finance, Elsevier, vol. 140(C).
    37. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
    38. Luis Melo Velandia & Luis Fernando Melo Velandia, 2019. "Regresión cuantílica dinámica para la medición del valor en riesgo: Una aplicación a datos colombianos," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 38(76), pages 23-50.
    39. Steven Kou & Xianhua Peng, 2016. "On the Measurement of Economic Tail Risk," Operations Research, INFORMS, vol. 64(5), pages 1056-1072, October.
    40. Katherine Uylangco & Siqiwen Li, 2016. "An evaluation of the effectiveness of Value-at-Risk (VaR) models for Australian banks under Basel III," Australian Journal of Management, Australian School of Business, vol. 41(4), pages 699-718, November.
    41. Vica Tendenan & Richard Gerlach & Chao Wang, 2020. "Tail risk forecasting using Bayesian realized EGARCH models," Papers 2008.05147, arXiv.org, revised Aug 2020.
    42. Filippo Curti & Marco Migueis, 2016. "Predicting Operational Loss Exposure Using Past Losses," Finance and Economics Discussion Series 2016-2, Board of Governors of the Federal Reserve System (U.S.).
    43. Hua, Jian & Manzan, Sebastiano, 2013. "Forecasting the return distribution using high-frequency volatility measures," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4381-4403.
    44. Argyropoulos, Christos & Panopoulou, Ekaterini, 2019. "Backtesting VaR and ES under the magnifying glass," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 22-37.
    45. Sebastian Bayer & Timo Dimitriadis, 2022. "Regression-Based Expected Shortfall Backtesting [Backtesting Expected Shortfall]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 437-471.
    46. Storti, Giuseppe & Wang, Chao, 2022. "A multivariate semi-parametric portfolio risk optimization and forecasting framework," MPRA Paper 115266, University Library of Munich, Germany.
    47. Chao Wang & Richard Gerlach & Qian Chen, 2018. "A Semi-parametric Realized Joint Value-at-Risk and Expected Shortfall Regression Framework," Papers 1807.02422, arXiv.org, revised Jan 2021.
    48. Sirio Aramonte & Marius del Giudice Rodriguez & Jason J. Wu, 2011. "Dynamic factor value-at-risk for large, heteroskedastic portfolios," Finance and Economics Discussion Series 2011-19, Board of Governors of the Federal Reserve System (U.S.).
    49. Chao Wang & Richard Gerlach, 2019. "Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall," Papers 1906.09961, arXiv.org.
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    51. Chan Jennifer So Kuen & Ng Kok-Haur & Nitithumbundit Thanakorn & Peiris Shelton, 2019. "Efficient estimation of financial risk by regressing the quantiles of parametric distributions: An application to CARR models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-22, April.
    52. Rubia, Antonio & Sanchis-Marco, Lidia, 2013. "On downside risk predictability through liquidity and trading activity: A dynamic quantile approach," International Journal of Forecasting, Elsevier, vol. 29(1), pages 202-219.
    53. Richard Gerlach & Chao Wang, 2016. "Bayesian Semi-parametric Realized-CARE Models for Tail Risk Forecasting Incorporating Realized Measures," Papers 1612.08488, arXiv.org.
    54. Richard Gerlach & Declan Walpole & Chao Wang, 2017. "Semi-parametric Bayesian tail risk forecasting incorporating realized measures of volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 199-215, February.
    55. Richard Gerlach & Chao Wang, 2018. "Semi-parametric Dynamic Asymmetric Laplace Models for Tail Risk Forecasting, Incorporating Realized Measures," Papers 1805.08653, arXiv.org.
    56. Cai, Zongwu & Chen, Haiqiang & Liao, Xiaosai, 2023. "A new robust inference for predictive quantile regression," Journal of Econometrics, Elsevier, vol. 234(1), pages 227-250.
    57. Wagner Piazza Gaglianone & Luiz Renato Lima, 2012. "Constructing Density Forecasts from Quantile Regressions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(8), pages 1589-1607, December.
    58. Elena-Ivona DUMITRESCU, 2011. "Backesting Value-at-Risk: From DQ (Dynamic Quantile) to DB (Dynamic Binary) Tests," LEO Working Papers / DR LEO 262, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    59. Thiele, Stephen, 2019. "Detecting underestimates of risk in VaR models," Journal of Banking & Finance, Elsevier, vol. 101(C), pages 12-20.
    60. Krystian Jaworski, 2019. "Sentiment-induced regime switching in density forecasts of emerging markets’ exchange rates. Calibrated simulation trumps estimated autoregression," Bank i Kredyt, Narodowy Bank Polski, vol. 50(1), pages 83-106.
    61. Wilson Calmon & Eduardo Ferioli & Davi Lettieri & Johann Soares & Adrian Pizzinga, 2021. "An Extensive Comparison of Some Well‐Established Value at Risk Methods," International Statistical Review, International Statistical Institute, vol. 89(1), pages 148-166, April.
    62. Geenens, Gery & Dunn, Richard, 2022. "A nonparametric copula approach to conditional Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 21(C), pages 19-37.
    63. Wang, Keli & Liu, Xiaoquan & Ye, Wuyi, 2023. "Intraday VaR: A copula-based approach," Journal of Empirical Finance, Elsevier, vol. 74(C).
    64. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    65. Chavleishvili, Sulkhan & Moench, Emanuel, 2025. "Natural disasters as macroeconomic tail risks," Journal of Econometrics, Elsevier, vol. 247(C).
    66. Wagner Piazza Gaglianone & João Victor Issler & Silvia Maria Matos, 2017. "Applying a microfounded-forecasting approach to predict Brazilian inflation," Empirical Economics, Springer, vol. 53(1), pages 137-163, August.
    67. De Rezende, Rafael B., 2015. "Risks in macroeconomic fundamentals and excess bond returns predictability," Working Paper Series 295, Sveriges Riksbank (Central Bank of Sweden).
    68. Marc Hallin & Carlos Trucíos, 2020. "Forecasting Value-at-Risk and Expected Shortfall in Large Portfolios: a General Dynamic Factor Approach," Working Papers ECARES 2020-50, ULB -- Universite Libre de Bruxelles.
    69. Malin Song & Zixu Sui & Xin Zhao, 2023. "A risk measurement study evaluating the impact of COVID-19 on China's financial market using the QR-SGED-EGARCH model," Annals of Operations Research, Springer, vol. 330(1), pages 787-806, November.
    70. Liu, Xiaochun, 2017. "An integrated macro-financial risk-based approach to the stressed capital requirement," Review of Financial Economics, Elsevier, vol. 34(C), pages 86-98.
    71. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    72. Elena-Ivona Dumitrescu & Christophe Hurlin & Vinson Pham, 2012. "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests," Working Papers halshs-00671658, HAL.
    73. Richard Gerlach & Chao Wang, 2016. "Forecasting risk via realized GARCH, incorporating the realized range," Quantitative Finance, Taylor & Francis Journals, vol. 16(4), pages 501-511, April.
    74. Hallin, Marc & Trucíos, Carlos, 2023. "Forecasting value-at-risk and expected shortfall in large portfolios: A general dynamic factor model approach," Econometrics and Statistics, Elsevier, vol. 27(C), pages 1-15.
    75. Hayette Gatfaoui, 2017. "Equity market information and credit risk signaling: A quantile cointegrating regression approach," Post-Print hal-01745285, HAL.
    76. Pradhan, Ashis Kumar & Tiwari, Aviral Kumar, 2021. "Estimating the market risk of clean energy technologies companies using the expected shortfall approach," Renewable Energy, Elsevier, vol. 177(C), pages 95-100.
    77. Xiaochun Liu, 2016. "Markov switching quantile autoregression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 356-395, November.
    78. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    79. Chao Wang & Qian Chen & Richard Gerlach, 2017. "Bayesian Realized-GARCH Models for Financial Tail Risk Forecasting Incorporating Two-sided Weibull Distribution," Papers 1707.03715, arXiv.org.
    80. Iqbal, Javed, 2017. "Does gold hedge stock market, inflation and exchange rate risks? An econometric investigation," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 1-17.
    81. Benjamin Mögel & Benjamin R. Auer, 2018. "How accurate are modern Value-at-Risk estimators derived from extreme value theory?," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 979-1030, May.
    82. Lúcio Godeiro, Lucas, 2012. "Estimando o VaR (Value-at-Risk) de carteiras via modelos da família GARCH e via Simulação de Monte Carlo [Estimating the VaR (Value-at-Risk) of portfolios via GARCH family models and via Monte Carl," MPRA Paper 45146, University Library of Munich, Germany.
    83. Gerlach, Richard & Abeywardana, Sachin, 2016. "Variational Bayes for assessment of dynamic quantile forecasts," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1385-1402.
    84. Jack Fosten & Daniel Gutknecht & Marc-Oliver Pohle, 2023. "Testing Quantile Forecast Optimality," Papers 2302.02747, arXiv.org, revised Oct 2023.
    85. Timo Dimitriadis & Sebastian Bayer, 2017. "A Joint Quantile and Expected Shortfall Regression Framework," Papers 1704.02213, arXiv.org, revised Aug 2017.
    86. Armstrong, Christopher S. & Blouin, Jennifer L. & Jagolinzer, Alan D. & Larcker, David F., 2015. "Corporate governance, incentives, and tax avoidance," Journal of Accounting and Economics, Elsevier, vol. 60(1), pages 1-17.
    87. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    88. Giessing, Alexander & He, Xuming, 2019. "On the predictive risk in misspecified quantile regression," Journal of Econometrics, Elsevier, vol. 213(1), pages 235-260.

  83. Oliver Linton & Kyungchul Song & Yoon-Jae Whang, 2008. "Bootstrap Tests of Stochastic Dominance with AsymptoticSimilarity on the Boundary," STICERD - Econometrics Paper Series 527, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Gonzalo, Jesús & Olmo, José, 2008. "Testing downside risk efficiency under market distress," UC3M Working papers. Economics we084321, Universidad Carlos III de Madrid. Departamento de Economía.
    2. Le-Yu Chen & Jerzy Szroeter, 2009. "Hypothesis testing of multiple inequalities: the method of constraint chaining," CeMMAP working papers CWP13/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Gonzalo, Jesús & Olmo, José, 2009. "Downside Risk Efficiency Under Market Distress," UC3M Working papers. Economics we094423, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Christopher J. Bennett, 2009. "Consistent and Asymptotically Unbiased MinP Tests of Multiple Inequality Moment Restrictions," Vanderbilt University Department of Economics Working Papers 0908, Vanderbilt University Department of Economics.
    5. Martin Huber & Giovanni Mellace, 2015. "Testing Instrument Validity for LATE Identification Based on Inequality Moment Constraints," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 398-411, May.

  84. Gregory Connor & Matthias Hagmann & Oliver Linton, 2007. "Efficient Estimation of a SemiparametricCharacteristic-Based Factor Model of Security Returns," STICERD - Econometrics Paper Series 524, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Zhang, Lyuou & Zhou, Wen & Wang, Haonan, 2021. "A semiparametric latent factor model for large scale temporal data with heteroscedasticity," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    2. Kunpeng Li & Qi Li & Lina Lu, 2018. "Quasi Maximum Likelihood Analysis of High Dimensional Constrained Factor Models," Supervisory Research and Analysis Working Papers RPA 18-2, Federal Reserve Bank of Boston.
    3. Jaeheon Jung, 2019. "Estimating a Large Covariance Matrix in Time-varying Factor Models," Papers 1910.11965, arXiv.org.
    4. Yang, Shuquan & Ling, Nengxiang, 2023. "Robust projected principal component analysis for large-dimensional semiparametric factor modeling," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    5. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2020. "Estimation of large dimensional conditional factor models in finance," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 219-282, Elsevier.
    6. Patrick GAGLIARDINI & Christian GOURIEROUX, 2010. "Efficiency in Large Dynamic Panel Models with Common Factor," Working Papers 2010-05, Center for Research in Economics and Statistics.
    7. Gong, Xiaomin & Xie, Fei & Zhou, Zhongsheng & Zhang, Chenyang, 2024. "The enhanced benefits of ESG in portfolios: A multi-factor model perspective based on LightGBM," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    8. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    9. Borak, Szymon & Härdle, Wolfgang Karl & Mammen, Enno & Park, Byeong U., 2007. "Time series modelling with semiparametric factor dynamics," SFB 649 Discussion Papers 2007-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Yuan Liao & Xiye Yang, 2017. "Uniform Inference for Characteristic Effects of Large Continuous-Time Linear Models," Papers 1711.04392, arXiv.org, revised Dec 2018.
    11. French, Declan & Wu, Yuliang & Li, Youwei, 2016. "Identifying the relative importance of stock characteristics," Journal of Multinational Financial Management, Elsevier, vol. 34(C), pages 80-91.
    12. Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
    13. Ge, S. & Li, S. & Linton, O., 2020. "A Dynamic Network of Arbitrage Characteristics," Cambridge Working Papers in Economics 2060, Faculty of Economics, University of Cambridge.
    14. Xu, R. & Fan, Q., 2025. "Single-Index Quantile Factor Model with Observed Characteristics," Janeway Institute Working Papers 2524, Faculty of Economics, University of Cambridge.
    15. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.
    16. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A projection based approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Feb 2025.
    17. Gregory Connor & Lisa R. Goldberg & Robert A. Korajczyk, 2010. "Portfolio Risk Analysis," Economics Books, Princeton University Press, edition 1, number 9224.

  85. Ilze Kalnina & Oliver Linton, 2007. "Inference about Realized Volatility using Infill Subsampling," STICERD - Econometrics Paper Series 523, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Jacod, Jean & Li, Yingying & Mykland, Per A. & Podolskij, Mark & Vetter, Mathias, 2007. "Microstructure noise in the continuous case: the pre-averaging approach," Technical Reports 2007,41, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    2. Mykland, Per A. & Zhang, Lan, 2016. "Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price," Journal of Econometrics, Elsevier, vol. 194(2), pages 242-262.
    3. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    4. Jean Jacod & Yingying Li & Per A. Mykland & Mark Podolskij & Mathias Vetter, 2007. "Microstructure Noise in the Continuous Case: The Pre-Averaging Approach - JLMPV-9," CREATES Research Papers 2007-43, Department of Economics and Business Economics, Aarhus University.

  86. Li, Sheng & Linton, Oliver, 2007. "Evaluating hedge fund performance: a stochastic dominance approach," LSE Research Online Documents on Economics 24486, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Guo, Dongmei & Hu, Yi & Wang, Shouyang & Zhao, Lin, 2016. "Comparing risks with reference points: A stochastic dominance approach," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 105-116.

  87. Cho, Young-Hyun & Linton, Oliver & Whang, Yoon-Jae, 2006. "Are there Monday effects in stock returns: a stochastic dominance approach," LSE Research Online Documents on Economics 24520, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Chuan-Hao Hsu & Hung-Gay Fung & Yi-Ping Chang, 2016. "The performance of Taiwanese firms after a share repurchase announcement," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1251-1269, November.
    2. Christos Kollias & Stephanos Papadamou, 2012. "Rogue State Behavior and Markets: The Financial Fallout of North Korean Nuclear Tests," Economics of Security Working Paper Series 67, DIW Berlin, German Institute for Economic Research.
    3. Kaplanski, Guy & Levy, Haim, 2010. "Sentiment and stock prices: The case of aviation disasters," Journal of Financial Economics, Elsevier, vol. 95(2), pages 174-201, February.
    4. Charles, Amélie, 2010. "The day-of-the-week effects on the volatility: The role of the asymmetry," European Journal of Operational Research, Elsevier, vol. 202(1), pages 143-152, April.
    5. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    6. Linton, O. & Wu, J., 2016. "A coupled component GARCH model for intraday and overnight volatility," Cambridge Working Papers in Economics 1671, Faculty of Economics, University of Cambridge.
    7. António Afonso & José Alves & Wojciech Grabowski & Sofia Monteiro, 2025. "Stock and Sovereign Returns Linkages: Time-Varying Causality and Extreme-Quantile Determinants," CESifo Working Paper Series 11667, CESifo.
    8. Roberto Cellini & Tiziana Cuccia & Johan Lyrvall, 2023. "On the price dynamics of non-fungible tokens: The ‘Bored Apes’ case," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-20, November.
    9. Scherf, Matthias & Matschke, Xenia & Rieger, Marc Oliver, 2022. "Stock market reactions to COVID-19 lockdown: A global analysis," Finance Research Letters, Elsevier, vol. 45(C).
    10. Irshad Hira & Taib Hasniza Mohd & Hussain Haroon & Hussain Rana Yassir, 2023. "Conventional and Islamic Equity Market Reaction Towards Terrorism: Evidence Based on Target Types, Location and Islamic Calendar Months," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 33(4), pages 70-116, December.
    11. Marshall, Ben R. & Nguyen, Hung T. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat & Young, Martin, 2021. "Do climate risks matter for green investment?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    12. Levy, Tamir & Yagil, Joseph, 2012. "The week-of-the-year effect: Evidence from around the globe," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1963-1974.
    13. Al-Khazali, Osamah & Mirzaei, Ali, 2017. "Stock market anomalies, market efficiency and the adaptive market hypothesis: Evidence from Islamic stock indices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 190-208.
    14. Kim Chang Sik, 2009. "Test for Spatial Dominances in the Distribution of Stock Returns: Evidence from the Korean Stock Market Before and After the East Asian Financial Crisis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(4), pages 1-27, September.
    15. Olfa Chaouachi & Imen Dhaou, 2020. "The Day of the Week Effect: Unconditional and Conditional Market Risk Analysis," International Journal of Economics and Financial Issues, Econjournals, vol. 10(6), pages 94-98.
    16. Cohen, Gil, 2014. "Why don’t you trade only four days a year? An empirical study into the abnormal returns of quarters first trading day," Economics Letters, Elsevier, vol. 124(3), pages 335-337.
    17. Eunhee Lee & Chang Kim & In-Moo Kim, 2015. "Equity premium over different investment horizons," Empirical Economics, Springer, vol. 48(3), pages 1169-1187, May.
    18. Ülkü, Numan & Rogers, Madeline, 2018. "Who drives the Monday effect?," Journal of Economic Behavior & Organization, Elsevier, vol. 148(C), pages 46-65.
    19. Kumar, Satish, 2016. "Revisiting calendar anomalies: Three decades of multicurrency evidence," Journal of Economics and Business, Elsevier, vol. 86(C), pages 16-32.
    20. Robert Elliott & Ying Zhou, 2013. "State-owned Enterprises, Exporting and Productivity in China: A Stochastic Dominance Approach," The World Economy, Wiley Blackwell, vol. 36(8), pages 1000-1028, August.
    21. Cheema, Arbab K. & Eshraghi, Arman & Wang, Qingwei, 2023. "Macroeconomic news and price synchronicity," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 390-412.
    22. Annaert, Jan & Osselaer, Sofieke Van & Verstraete, Bert, 2009. "Performance evaluation of portfolio insurance strategies using stochastic dominance criteria," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 272-280, February.
    23. Chow, Nikolai Sheung-Chi, 2025. "Risk Measures and Portfolio Choices for Gain-Loss Dependent Objectives," MPRA Paper 124440, University Library of Munich, Germany.
    24. Erling Røed Larsen, 2021. "Intra‐Week Price Patterns in the Housing Market," Scandinavian Journal of Economics, Wiley Blackwell, vol. 123(1), pages 327-352, January.
    25. Al-Khazali, Osamah, 2014. "Revisiting fast profit investor sentiment and stock returns during Ramadan," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 158-170.
    26. Chundakkadan, Radeef & Nedumparambil, Elizabeth, 2022. "In search of COVID-19 and stock market behavior," Global Finance Journal, Elsevier, vol. 54(C).
    27. Chatzitzisi, Evanthia & Fountas, Stilianos & Panagiotidis, Theodore, 2021. "Another look at calendar anomalies," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 823-840.
    28. Roberto Cellini & Tiziana Cuccia, 2014. "Seasonal processes in the Euro--US Dollar daily exchange rate," Applied Financial Economics, Taylor & Francis Journals, vol. 24(3), pages 161-174, February.
    29. Zhuo Qiao & Wing-Keung Wong, 2015. "Which is a better investment choice in the Hong Kong residential property market: a big or small property?," Applied Economics, Taylor & Francis Journals, vol. 47(16), pages 1670-1685, April.
    30. Ichev, Riste & Marinč, Matej, 2018. "Stock prices and geographic proximity of information: Evidence from the Ebola outbreak," International Review of Financial Analysis, Elsevier, vol. 56(C), pages 153-166.
    31. Qiao, Zhuo & Pukthuanthong, Kuntara, 2019. "Has the difference in stock liquidity and stock returns between Chinese state owned and privately owned enterprises become smaller?," Finance Research Letters, Elsevier, vol. 28(C), pages 39-44.
    32. Laurence E. Blose & Vijay Gondhalekar, 2013. "Weekend gold returns in bull and bear markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 53(3), pages 609-622, September.
    33. Sheng-Ping Yang & Thanh Nguyen, 2019. "Skewness Preference and Asset Pricing: Evidence from the Japanese Stock Market," JRFM, MDPI, vol. 12(3), pages 1-10, September.
    34. Kaiser, Lars, 2019. "Seasonality in cryptocurrencies," Finance Research Letters, Elsevier, vol. 31(C).
    35. Chui, David & Wing Cheng, Wui & Chi Chow, Sheung & LI, Ya, 2020. "Eastern Halloween effect: A stochastic dominance approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 68(C).
    36. Radeef Chundakkadan, 2021. "Light a lamp and look at the stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-21, December.
    37. Qadan, Mahmoud & Idilbi-Bayaa, Yasmeen, 2021. "The day-of-the-week-effect on the volatility of commodities," Resources Policy, Elsevier, vol. 71(C).
    38. Audrius Kabašinskas & Lina Kadikinaitė, 2016. "The construction of an investment portfolio using stochastic programming," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 6(3), pages 151-160, July.
    39. Sungro Lee, Chang Sik Kim, In-Moo Kim & Chang Sik Kim & In-Moo Kim, 2012. "Testing the Monday Effect using High-frequency Intraday Returns: A Spatial Dominance Approach," Korean Economic Review, Korean Economic Association, vol. 28, pages 69-90.
    40. Santi, Caterina & Zwinkels, Remco C.J., 2023. "Exploring style herding by mutual funds," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    41. Ali CELÝK, 2021. "Volatility of BIST 100 Returns After 2020, Calendar Anomalies and COVID-19 Effect," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 15(1), pages 61-81.
    42. Kapalczynski, Anna & Lien, Donald, 2021. "Effectiveness of Augmented Dollar-Cost Averaging," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    43. McSweeney, Brendan, 2009. "The roles of financial asset market failure denial and the economic crisis: Reflections on accounting and financial theories and practices," Accounting, Organizations and Society, Elsevier, vol. 34(6-7), pages 835-848, August.
    44. Jeffrey E. Jarrett, 2008. "Predicting Daily Stock Returns: A Lengthy Study of the Hong Kong and Tokyo Stock Exchanges," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 7(1), pages 37-51, April.
    45. Al-Khazali, Osamah & Lean, Hooi Hooi & Samet, Anis, 2014. "Do Islamic stock indexes outperform conventional stock indexes? A stochastic dominance approach," Pacific-Basin Finance Journal, Elsevier, vol. 28(C), pages 29-46.

  88. Gregory Connor & Oliver Linton, 2006. "Semiparametric Estimation of aCharacteristic-based Factor Model ofCommon Stock Returns," STICERD - Econometrics Paper Series 506, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Charle Augusto Londoño, 2011. "Regresión del cuantil aplicada al modelo de redes neuronales artificiales," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 29(64), pages 62-109, July.
    2. Cheng, Mingmian & Liao, Yuan & Yang, Xiye, 2023. "Uniform predictive inference for factor models with instrumental and idiosyncratic betas," Journal of Econometrics, Elsevier, vol. 237(2).
    3. Zhang, Lyuou & Zhou, Wen & Wang, Haonan, 2021. "A semiparametric latent factor model for large scale temporal data with heteroscedasticity," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    4. Alex Huang, 2013. "Value at risk estimation by quantile regression and kernel estimator," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 225-251, August.
    5. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
    6. Kunpeng Li & Qi Li & Lina Lu, 2018. "Quasi Maximum Likelihood Analysis of High Dimensional Constrained Factor Models," Supervisory Research and Analysis Working Papers RPA 18-2, Federal Reserve Bank of Boston.
    7. Sainan Jin & Liangjun Su & Yonghui Zhang, 2015. "Nonparametric testing for anomaly effects in empirical asset pricing models," Empirical Economics, Springer, vol. 48(1), pages 9-36, February.
    8. Jaeheon Jung, 2019. "Estimating a Large Covariance Matrix in Time-varying Factor Models," Papers 1910.11965, arXiv.org.
    9. Yang, Shuquan & Ling, Nengxiang, 2023. "Robust projected principal component analysis for large-dimensional semiparametric factor modeling," Journal of Multivariate Analysis, Elsevier, vol. 195(C).
    10. Xiang, Jingjie & Li, Kunpeng & Cui, Guowei, 2018. "A note on the asymptotic properties of least squares estimation in high dimensional constrained factor models," Economics Letters, Elsevier, vol. 171(C), pages 144-148.
    11. Linton, O. & Xiao, Z., 2019. "Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity," Cambridge Working Papers in Economics 1907, Faculty of Economics, University of Cambridge.
    12. Yuan Liao & Xiye Yang, 2017. "Uniform Inference for Conditional Factor Models with Instrumental and Idiosyncratic Betas," Departmental Working Papers 201711, Rutgers University, Department of Economics.
    13. Liang Chen & Juan Jose Dolado & Jesus Gonzalo & Haozi Pan, 2023. "Estimation of Characteristics-based Quantile Factor Models," Papers 2304.13206, arXiv.org.
    14. Matias Cattaneo & Richard K. Crump & Weining Wang, 2024. "Beta-sorted portfolios," CeMMAP working papers 20/24, Institute for Fiscal Studies.
    15. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2020. "Estimation of large dimensional conditional factor models in finance," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 219-282, Elsevier.
    16. Gong, Xiaomin & Xie, Fei & Zhou, Zhongsheng & Zhang, Chenyang, 2024. "The enhanced benefits of ESG in portfolios: A multi-factor model perspective based on LightGBM," Pacific-Basin Finance Journal, Elsevier, vol. 85(C).
    17. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    18. Shujie Ma & Oliver Linton & Jiti Gao, 2017. "Estimation and inference in semiparametric quantile factor models," Monash Econometrics and Business Statistics Working Papers 8/17, Monash University, Department of Econometrics and Business Statistics.
    19. Connor, Gregory & Hagmann, Matthias & Linton, Oliver, 2007. "Efficient estimation of a semiparametric characteristic-based factor model of security returns," LSE Research Online Documents on Economics 24504, London School of Economics and Political Science, LSE Library.
    20. Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
    21. Borak, Szymon & Härdle, Wolfgang Karl & Mammen, Enno & Park, Byeong U., 2007. "Time series modelling with semiparametric factor dynamics," SFB 649 Discussion Papers 2007-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    22. Lee, Jiyon, 2015. "A semiparametric single index model with heterogeneous impacts on an unobserved variable," Journal of Econometrics, Elsevier, vol. 184(1), pages 13-36.
    23. Sakemoto, Ryuta, 2019. "Currency carry trades and the conditional factor model," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 198-208.
    24. Onatski, Alexei, 2012. "Asymptotics of the principal components estimator of large factor models with weakly influential factors," Journal of Econometrics, Elsevier, vol. 168(2), pages 244-258.
    25. Sung Hoon Choi, 2021. "Feasible Weighted Projected Principal Component Analysis for Factor Models with an Application to Bond Risk Premia," Papers 2108.10250, arXiv.org, revised May 2022.
    26. Yuan Liao & Xiye Yang, 2017. "Uniform Inference for Characteristic Effects of Large Continuous-Time Linear Models," Papers 1711.04392, arXiv.org, revised Dec 2018.
    27. French, Declan & Wu, Yuliang & Li, Youwei, 2016. "Identifying the relative importance of stock characteristics," Journal of Multinational Financial Management, Elsevier, vol. 34(C), pages 80-91.
    28. Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
    29. Ge, S. & Li, S. & Linton, O., 2020. "A Dynamic Network of Arbitrage Characteristics," Cambridge Working Papers in Economics 2060, Faculty of Economics, University of Cambridge.
    30. Xu, R. & Fan, Q., 2025. "Single-Index Quantile Factor Model with Observed Characteristics," Janeway Institute Working Papers 2524, Faculty of Economics, University of Cambridge.
    31. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.
    32. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A projection based approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Feb 2025.
    33. Gregory Connor & Lisa R. Goldberg & Robert A. Korajczyk, 2010. "Portfolio Risk Analysis," Economics Books, Princeton University Press, edition 1, number 9224.

  89. Kalnina, Ilze & Linton, Oliver, 2006. "Estimating quadratic variation consistently in the presence of correlated measurement error," LSE Research Online Documents on Economics 4413, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Kalnina, Ilze & Linton, Oliver, 2007. "Inference about realized volatility using infill subsampling," LSE Research Online Documents on Economics 4411, London School of Economics and Political Science, LSE Library.
    2. Neil Shephard & Ole E. Barndorff-Nielsen & Asger Lunde, 2006. "Subsampling realised kernels," Economics Series Working Papers 278, University of Oxford, Department of Economics.
    3. Neil Shephard & Dacheng Xiu, 2012. "Econometric analysis of multivariate realised QML: efficient positive semi-definite estimators of the covariation of equity prices," Economics Papers 2012-W04, Economics Group, Nuffield College, University of Oxford.
    4. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Economics Papers 2008-W10, Economics Group, Nuffield College, University of Oxford.
    5. Kim Christensen & Mark Podolskij & Mathias Vetter, 2009. "Bias-correcting the realized range-based variance in the presence of market microstructure noise," Finance and Stochastics, Springer, vol. 13(2), pages 239-268, April.
    6. Lidan Grossmass, 2014. "Obtaining and Predicting the Bounds of Realized Correlations," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 150(III), pages 191-226, September.
    7. O. E. Barndorff-Nielsen & P. Reinhard Hansen & A. Lunde & N. Shephard, 2009. "Realized kernels in practice: trades and quotes," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 1-32, November.
    8. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2006. "Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise," Economics Papers 2006-W03, Economics Group, Nuffield College, University of Oxford.
    9. Elezovic, Suad, 2009. "Functional modelling of volatility in the Swedish limit order book," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2107-2118, April.

  90. David Jacho-Chavez & Arthur Lewbel & Oliver Linton, 2006. "Identification and Nonparametric Estimation of a Transformed Additively Separable Model," Boston College Working Papers in Economics 652, Boston College Department of Economics, revised 26 Nov 2008.

    Cited by:

    1. Colling, Benjamin & Van Keilegom, Ingrid, 2016. "Goodness-of-fit tests in semiparametric transformation models using the integrated regression function," LIDAM Discussion Papers ISBA 2016031, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Joel L. Horowitz & Sokbae (Simon) Lee, 2015. "Nonparametric estimation and inference under shape restrictions," CeMMAP working papers CWP67/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. David Jacho-Chavez & Arthur Lewbel & Oliver Linton, 2006. "Identification and Nonparametric Estimation of a Transformed Additively Separable Model," Boston College Working Papers in Economics 652, Boston College Department of Economics, revised 26 Nov 2008.
    4. Ruixuan Liu, 2020. "A competing risks model with time‐varying heterogeneity and simultaneous failure," Quantitative Economics, Econometric Society, vol. 11(2), pages 535-577, May.
    5. Krief, Jerome M., 2017. "Direct instrumental nonparametric estimation of inverse regression functions," Journal of Econometrics, Elsevier, vol. 201(1), pages 95-107.
    6. Christoph Breunig & Stephan Martin, 2020. "Nonclassical Measurement Error in the Outcome Variable," Papers 2009.12665, arXiv.org, revised May 2021.
    7. Vanhems, Anne & Van Keilegom, Ingrid, 2011. "Semiparametric transformation model with endogeneity: a control function approach," LIDAM Discussion Papers ISBA 2011011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Arthur Lewbel & Xun Lu & Liangjun Su, 2012. "Specification Testing for Transformation Models with an Application to Generalized Accelerated Failure-time Models," Boston College Working Papers in Economics 817, Boston College Department of Economics, revised 01 May 2013.
    9. Centorrino, Samuele & Florens, Jean-Pierre, 2021. "Nonparametric Instrumental Variable Estimation of Binary Response Models with Continuous Endogenous Regressors," Econometrics and Statistics, Elsevier, vol. 17(C), pages 35-63.
    10. Van Keilegom, Ingrid & Vanhems, Anne, 2016. "Estimation of a semiparametric transformation model in the presence of endogeneity," TSE Working Papers 16-654, Toulouse School of Economics (TSE).
    11. Chiappori, Pierre-André & Komunjer, Ivana & Kristensen, Dennis, 2015. "Nonparametric identification and estimation of transformation models," Journal of Econometrics, Elsevier, vol. 188(1), pages 22-39.
    12. Vanhems, Anne & Van Keilegom, Ingrid, 2013. "Semiparametric transformation model with endogeneity: a control function approach," LIDAM Discussion Papers ISBA 2013018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    13. Koohyun Kwon & Soonwoo Kwon, 2020. "Adaptive Inference in Multivariate Nonparametric Regression Models Under Monotonicity," Papers 2011.14219, arXiv.org.
    14. Van Keilegom, Ingrid & Vanhems, Anne, 2011. "Semiparametric transformation model with endogeneity: a control function approach," TSE Working Papers 11-243, Toulouse School of Economics (TSE).
    15. Colling, Benjamin & Van Keilegom, Ingrid, 2017. "Goodness-of-fit tests in semiparametric transformation models using the integrated regression function," Journal of Multivariate Analysis, Elsevier, vol. 160(C), pages 10-30.

  91. Sokbae Lee & Oliver Linton & Yoon-Jae Whang, 2006. "Testing For Stochasticmonotonicity," STICERD - Econometrics Paper Series 504, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Sokbae Lee & Ryo Okui & Yoon†Jae Whang, 2017. "Doubly robust uniform confidence band for the conditional average treatment effect function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1207-1225, November.
    2. Ismael Mourifie & Marc Henry & Romuald Meango, 2017. "Sharp bounds and testability of a Roy model of STEM major choices," Papers 1709.09284, arXiv.org, revised Nov 2019.
    3. Takashi Kamihigashi & John Stachurski, 2011. "Existence, Stability and Computation of Stationary Distributions: An Extension of the Hopenhayn-Prescott Theorem," Discussion Paper Series DP2011-32, Research Institute for Economics & Business Administration, Kobe University.
    4. Victor Chernozhukov & Sokbae Lee & Adam M. Rosen, 2013. "Intersection Bounds: Estimation and Inference," Econometrica, Econometric Society, vol. 81(2), pages 667-737, March.
    5. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2012. "Inference on counterfactual distributions," CeMMAP working papers 05/12, Institute for Fiscal Studies.
    6. Markus Jantti & Stephen P. Jenkins, 2014. "Income Mobility," Working Papers 319, ECINEQ, Society for the Study of Economic Inequality.
    7. Takashi Kamihigashi & John Stachurski, 2011. "Stability of Stationary Distributions in Monotone Economies," ANU Working Papers in Economics and Econometrics 2011-561, Australian National University, College of Business and Economics, School of Economics.
    8. Gutknecht, Daniel, 2016. "Testing for monotonicity under endogeneity," Journal of Econometrics, Elsevier, vol. 190(1), pages 100-114.
    9. Le-Yu Chen & Jerzy Szroeter, 2009. "Hypothesis testing of multiple inequalities: the method of constraint chaining," CeMMAP working papers CWP13/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Henry, Marc & Méango, Romuald & Mourifié, Ismaël, 2024. "Role models and revealed gender-specific costs of STEM in an extended Roy model of major choice," Journal of Econometrics, Elsevier, vol. 238(2).
    11. Salim Bouzebda & Thouria El-hadjali & Anouar Abdeldjaoued Ferfache, 2023. "Uniform in Bandwidth Consistency of Conditional U-statistics Adaptive to Intrinsic Dimension in Presence of Censored Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(2), pages 1548-1606, August.
    12. Arden Finn & Murray Leibbrandt & Vimal Ranchhod, 2016. "Patterns of persistence: Intergenerational mobility and education in South Africa," SALDRU Working Papers 175, Southern Africa Labour and Development Research Unit, University of Cape Town.
    13. Delgado, Miguel A. & Escanciano, Juan Carlos, 2012. "Distribution-free tests of stochastic monotonicity," Journal of Econometrics, Elsevier, vol. 170(1), pages 68-75.
    14. Denis Chetverikov & Daniel Wilhelm, 2017. "Nonparametric Instrumental Variable Estimation Under Monotonicity," Econometrica, Econometric Society, vol. 85, pages 1303-1320, July.
    15. Ibarra-Ramírez Raúl, 2011. "Stocks, Bonds and the Investment Horizon: A Spatial Dominance Approach," Working Papers 2011-03, Banco de México.
    16. Qu, Zhongjun & Yoon, Jungmo, 2015. "Nonparametric estimation and inference on conditional quantile processes," Journal of Econometrics, Elsevier, vol. 185(1), pages 1-19.
    17. Vladimir Vladimirovich Vinogradov & Richard Bruce Paris, 2021. "On two extensions of the canonical Feller–Spitzer distribution," Journal of Statistical Distributions and Applications, Springer, vol. 8(1), pages 1-25, December.
    18. Daniel Gutknecht, 2013. "Testing for Monotonicity under Endogeneity An Application to the Reservation Wage Function," Economics Series Working Papers 673, University of Oxford, Department of Economics.
    19. Abdelaati Daouia & Hohsuk Noh & Byeong U. Park, 2016. "Data envelope fitting with constrained polynomial splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 3-30, January.
    20. Valentino Dardanoni & Mario Fiorini & Antonio Forcina, 2008. "Stochastic Monotonicity in Intergenerational Mobility Tables," Working Paper Series 156, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    21. Sungwon Lee, 2021. "Partial Identification and Inference for Conditional Distributions of Treatment Effects," Papers 2108.00723, arXiv.org, revised Nov 2023.
    22. Christopher A. Hennessy & Ilya A. Strebulaev, 2020. "Beyond Random Assignment: Credible Inference and Extrapolation in Dynamic Economies," Journal of Finance, American Finance Association, vol. 75(2), pages 825-866, April.
    23. Timothy B. Armstrong & Hock Peng Chan, 2013. "Multiscale Adaptive Inference on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1885R, Cowles Foundation for Research in Economics, Yale University, revised Oct 2014.
    24. Salim Bouzebda & Inass Soukarieh, 2022. "Non-Parametric Conditional U -Processes for Locally Stationary Functional Random Fields under Stochastic Sampling Design," Mathematics, MDPI, vol. 11(1), pages 1-69, December.
    25. Denis Chetverikov & Daniel Wilhelm & Dongwoo Kim, 2020. "An Adaptive Test of Stochastic Monotonicity," CeMMAP working papers CWP17/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Gutknecht, Daniel, "undated". "Do Reservation Wages Decline Monotonically? A Novel Statistical Test," Economic Research Papers 270635, University of Warwick - Department of Economics.
    27. Salim Bouzebda & Boutheina Nemouchi, 2023. "Weak-convergence of empirical conditional processes and conditional U-processes involving functional mixing data," Statistical Inference for Stochastic Processes, Springer, vol. 26(1), pages 33-88, April.
    28. Lee, Tae-Hwy & Tu, Yundong & Ullah, Aman, 2014. "Nonparametric and semiparametric regressions subject to monotonicity constraints: Estimation and forecasting," Journal of Econometrics, Elsevier, vol. 182(1), pages 196-210.
    29. Seo, Juwon, 2018. "Tests of stochastic monotonicity with improved power," Journal of Econometrics, Elsevier, vol. 207(1), pages 53-70.
    30. Inass Soukarieh & Salim Bouzebda, 2022. "Exchangeably Weighted Bootstraps of General Markov U -Process," Mathematics, MDPI, vol. 10(20), pages 1-42, October.
    31. Sungwon Lee, 2024. "Partial identification and inference for conditional distributions of treatment effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 107-127, January.
    32. Ying-Ying Lee, 2014. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Economics Series Working Papers 706, University of Oxford, Department of Economics.
    33. Matthew A. Masten & Alexandre Poirier, 2018. "Interpreting Quantile Independence," Papers 1804.10957, arXiv.org.
    34. Misha Beek & Hennie Daniels, 2014. "A Non-parametric Test for Partial Monotonicity in Multiple Regression," Computational Economics, Springer;Society for Computational Economics, vol. 44(1), pages 87-100, June.
    35. Salim Bouzebda & Amel Nezzal & Tarek Zari, 2022. "Uniform Consistency for Functional Conditional U -Statistics Using Delta-Sequences," Mathematics, MDPI, vol. 11(1), pages 1-39, December.
    36. Daniel Wilhelm, 2019. "Testing for the presence of measurement error," CeMMAP working papers CWP48/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    37. Aradillas-López, Andrés & Gandhi, Amit & Quint, Daniel, 2016. "A simple test for moment inequality models with an application to English auctions," Journal of Econometrics, Elsevier, vol. 194(1), pages 96-115.
    38. Feng, Long & Lan, Wei & Liu, Binghui & Ma, Yanyuan, 2022. "High-dimensional test for alpha in linear factor pricing models with sparse alternatives," Journal of Econometrics, Elsevier, vol. 229(1), pages 152-175.
    39. José Romeo & Nelson Tanaka & Antonio Pedroso-de-Lima & Victor Salinas-Torres, 2013. "Large sample properties for a class of copulas in bivariate survival analysis," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(8), pages 997-1015, November.
    40. Maribel Jiménez, 2016. "Movilidad Intergeneracional del Ingreso en Argentina. Un Análisis de sus Cambios Temporales desde el Enfoque de Igualdad de Oportunidades," CEDLAS, Working Papers 0203, CEDLAS, Universidad Nacional de La Plata.
    41. Takashi Kamihigashi & John Stachurski, 2014. "Partial Stochastic Dominance," Discussion Paper Series DP2014-23, Research Institute for Economics & Business Administration, Kobe University.
    42. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    43. Berghaus, Betina & Bücher, Axel, 2014. "Nonparametric tests for tail monotonicity," Journal of Econometrics, Elsevier, vol. 180(2), pages 117-126.
    44. Inass Soukarieh & Salim Bouzebda, 2024. "Weak convergence of the conditional U-statistics for locally stationary functional time series," Statistical Inference for Stochastic Processes, Springer, vol. 27(2), pages 227-304, July.
    45. Takashi Kamihigashi & John Stachurski, 2012. "Existence, Uniqueness and Stability of Stationary Distributions: An Extension of the Hopenhayn-Prescott Theorem," Discussion Paper Series DP2012-27, Research Institute for Economics & Business Administration, Kobe University.

  92. Oliver Linton & Enno Mammen, 2006. "Nonparametric Transformation to White Noise," STICERD - Econometrics Paper Series 503, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," The Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
    2. Gagliardini, Patrick & Scaillet, Olivier, 2012. "Tikhonov regularization for nonparametric instrumental variable estimators," Journal of Econometrics, Elsevier, vol. 167(1), pages 61-75.
    3. Degui Li & Oliver Linton & Zudi Lu, 2012. "A flexible semiparametric model for time series," CeMMAP working papers CWP28/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Juliane Geller & Michael H. Neumann, 2018. "Improved local polynomial estimation in time series regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 1-27, January.
    5. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Short-Term Exuberance and Long-Term Stability: A Simultaneous Optimization of Stock Return Predictions for Short and Long Horizons," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    6. Ozabaci, Deniz & Henderson, Daniel J., 2014. "Additive Kernel Estimates of Returns to Schooling," IZA Discussion Papers 8736, Institute of Labor Economics (IZA).
    7. Connor, Gregory & Hagmann, Matthias & Linton, Oliver, 2007. "Efficient estimation of a semiparametric characteristic-based factor model of security returns," LSE Research Online Documents on Economics 24504, London School of Economics and Political Science, LSE Library.
    8. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Short-Term Exuberance and long-term stability: A simultaneous optimization of stock return predictions for short and long horizons," Graz Economics Papers 2020-20, University of Graz, Department of Economics.
    9. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.
    10. Liangjun Su & Aman Ullah & Yun Wang, 2013. "Nonparametric regression estimation with general parametric error covariance: a more efficient two-step estimator," Empirical Economics, Springer, vol. 45(2), pages 1009-1024, October.
    11. Oliver Linton & Qiying Wang, 2013. "Non-parametric transformation regression with non-stationary data," CeMMAP working papers CWP16/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Koo, Bonsoo & Linton, Oliver, 2012. "Estimation of semiparametric locally stationary diffusion models," Journal of Econometrics, Elsevier, vol. 170(1), pages 210-233.
    13. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional Variance Forecasts for Long-Term Stock Returns," Risks, MDPI, vol. 7(4), pages 1-22, November.
    14. Mammen, Enno & Park, Byeong U. & Schienle, Melanie, 2012. "Additive models: Extensions and related models," SFB 649 Discussion Papers 2012-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Longer-Term Forecasting of Excess Stock Returns—The Five-Year Case," Mathematics, MDPI, vol. 8(6), pages 1-20, June.
    16. Mammen, Enno & Martínez-Miranda, María Dolores & Nielsen, Jens Perch & Vogt, Michael, 2021. "Calendar effect and in-sample forecasting," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 31-52.
    17. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2019. "Machine Learning for Forecasting Excess Stock Returns The Five-Year-View," Graz Economics Papers 2019-06, University of Graz, Department of Economics.

  93. Linton, Oliver & Seo, Myunghwan, 2005. "A smoothed least squares estimator for threshold regression models," LSE Research Online Documents on Economics 4434, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Kemp, Gordon C.R. & Santos Silva, J.M.C., 2012. "Regression towards the mode," Journal of Econometrics, Elsevier, vol. 170(1), pages 92-101.
    2. Young-Joo Kim & Myung Hwan Seo, 2017. "Is There a Jump in the Transition?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 241-249, April.
    3. Junho Lee & Ying Sun & Huixia Judy Wang, 2021. "Spatial cluster detection with threshold quantile regression," Environmetrics, John Wiley & Sons, Ltd., vol. 32(8), December.
    4. Daniel Ordoñez-Callamand & Luis F. Melo-Velandia & Oscar M. Valencia-Arana, 2017. "Current Account Sustainability in Latin America Considering Nonlinearities," Borradores de Economia 987, Banco de la Republica de Colombia.
    5. Lixiong Yang & Mingjian Ren & Jianming Bai, 2025. "Threshold mixed data sampling logit model with an application to forecasting US bank failures," Empirical Economics, Springer, vol. 68(1), pages 433-477, January.
    6. Olaoye, Olumide O. & Eluwole, Oluwatosin O. & Ayesha, Aziz & Afolabi, Olugbenga O., 2020. "Government spending and economic growth in ECOWAS: An asymmetric analysis," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    7. Yoonseok Lee & Yulong Wang, 2020. "Inference in Threshold Models," Center for Policy Research Working Papers 223, Center for Policy Research, Maxwell School, Syracuse University.
    8. Peter H. Egger & Yulong Wang, 2025. "Estimating Export-productivity Cutoff Contours with Profit Data: A Novel Threshold Estimation Approach," Papers 2502.03406, arXiv.org, revised May 2025.
    9. Yoonseok Lee & Yulong Wang, 2019. "Threshold Regression with Nonparametric Sample Splitting," Papers 1905.13140, arXiv.org, revised Jan 2021.
    10. Myung Hwan Seo, 2007. "Estimation of Nonlinear Error CorrectionModels," STICERD - Econometrics Paper Series 517, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    11. Andros Kourtellos & Thanasis Stengos & Chih Ming Tan, 2011. "Structural Threshold Regression," University of Cyprus Working Papers in Economics 13-2011, University of Cyprus Department of Economics.
    12. Kourtellos, Andros & Stengos, Thanasis & Sun, Yiguo, 2022. "Endogeneity In Semiparametric Threshold Regression," Econometric Theory, Cambridge University Press, vol. 38(3), pages 562-595, June.
    13. Chaoyi Chen & Yiguo Sun & Yao Rao, 2023. "Threshold MIDAS Forecasting of Inflation Rate," Working Papers 202314, University of Liverpool, Department of Economics.
    14. Jesús Gonzalo & Jean-Yves Pitarakis, 2013. "Estimation and inference in threshold type regime switching models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 8, pages 189-205, Edward Elgar Publishing.
    15. N. R. Ramírez-Rondán, 2020. "Maximum likelihood estimation of dynamic panel threshold models," Econometric Reviews, Taylor & Francis Journals, vol. 39(3), pages 260-276, March.
    16. Shota Takeishi, 2023. "Asymptotic properties of the maximum smoothed partial likelihood estimator in the change‐plane Cox model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(3), pages 1503-1531, September.
    17. T. V. S. Ramamohan Rao, 2025. "An Efficient Algorithm for the Estimation of a Mixture of Switching and Threshold Regressions," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 23(3), pages 661-677, September.
    18. Haiqiang Chen, "undated". "Robust Estimation and Inference for Threshold Models with Integrated Regressors," Working Papers 2013-12-02, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    19. Egger, Peter & Erhardt, Katharina & Keuschnigg, Christian, 2014. "Heterogeneous Tax Sensitivity of Firm-level Investments," Economics Working Paper Series 1426, University of St. Gallen, School of Economics and Political Science.
    20. Hong, Han & Mahajan, Aprajit & Nekipelov, Denis, 2015. "Extremum estimation and numerical derivatives," Journal of Econometrics, Elsevier, vol. 188(1), pages 250-263.
    21. Jiatong Li & Hongqiang Yan, 2024. "Uniform Inference in High-Dimensional Threshold Regression Models," Papers 2404.08105, arXiv.org, revised Sep 2025.
    22. Lee, Sokbae & Seo, Myung Hwan, 2008. "Semiparametric estimation of a binary response model with a change-point due to a covariate threshold," Journal of Econometrics, Elsevier, vol. 144(2), pages 492-499, June.
    23. Shuyu Li & Rongrong Li, 2021. "Revisiting the Existence of EKC Hypothesis under Different Degrees of Population Aging: Empirical Analysis of Panel Data from 140 Countries," IJERPH, MDPI, vol. 18(23), pages 1-19, December.
    24. Sun, Yuying & Han, Ai & Hong, Yongmiao & Wang, Shouyang, 2018. "Threshold autoregressive models for interval-valued time series data," Journal of Econometrics, Elsevier, vol. 206(2), pages 414-446.
    25. Qusai Mohammad Qasim Alabed & Fathin Faizah Said & Zulkefly Abdul Karim & Mohd Azlan Shah Zaidi & Mohammed Daher Alshammary, 2021. "Energy–Growth Nexus in the MENA Region: A Dynamic Panel Threshold Estimation," Sustainability, MDPI, vol. 13(22), pages 1-18, November.
    26. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    27. Miao, Ke & Li, Kunpeng & Su, Liangjun, 2020. "Panel threshold models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 219(1), pages 137-170.
    28. Chaoyi Chen & Yiguo Sun, 2018. "Monte Carlo Comparison for Nonparametric Threshold Estimators," JRFM, MDPI, vol. 11(3), pages 1-15, August.
    29. Sokbae Lee & Yuan Liao & Myung Hwan Seo & Youngki Shin, 2019. "Factor-Driven Two-Regime Regression," Working Paper Series no128, Institute of Economic Research, Seoul National University.
    30. Motegi, Kaiji & Hamori, Shigeyuki, 2025. "Conditional threshold effects of stock market volatility on crude oil market volatility," Energy Economics, Elsevier, vol. 143(C).
    31. Yu, Ping, 2015. "Adaptive estimation of the threshold point in threshold regression," Journal of Econometrics, Elsevier, vol. 189(1), pages 83-100.
    32. Alogoskoufis, George & Malliaris, A.G. & Stengos, Thanasis, 2023. "The scope and methodology of economic and financial asymmetries," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    33. Hasanov, Fakhri J. & Aliyev, Ruslan & Taskin, Dilvin & Suleymanov, Elchin, 2023. "Oil rents and non-oil economic growth in CIS oil exporters. The role of financial development," Resources Policy, Elsevier, vol. 82(C).
    34. Kourtellos, A. & Tan, C.M. & Stengos, T., 2008. "THRET: Threshold Regression with Endogenous Threshold Variables," Working Papers 0801, University of Guelph, Department of Economics and Finance.
    35. Massacci, Daniele, 2013. "A switching model with flexible threshold variable: With an application to nonlinear dynamics in stock returns," Economics Letters, Elsevier, vol. 119(2), pages 199-203.
    36. Seo, Myung Hwan & Shin, Yongcheol, 2016. "Dynamic panels with threshold effect and endogeneity," Journal of Econometrics, Elsevier, vol. 195(2), pages 169-186.
    37. Hidalgo, Javier & Lee, Jungyoon & Seo, Myung Hwan, 2019. "Robust inference for threshold regression models," Journal of Econometrics, Elsevier, vol. 210(2), pages 291-309.
    38. Chlibi Souhir & Jawadi Fredj & Sellami Mohamed, 2017. "Modeling threshold effects in stock price co-movements: a vector nonlinear cointegration approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 47-63, February.
    39. T. V. S. Ramamohan Rao, 2024. "On the Estimation of a Class of Threshold Regression Models," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 22(1), pages 199-209, March.
    40. Andros Kourtellos & Thanasis Stengos & Chih ming Tan, 2010. "Do institutions rule? The role of heterogeneity in the institutions vs. geography debate," Economics Bulletin, AccessEcon, vol. 30(3), pages 1710-1719.
    41. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    42. Yélou, Clément & Larue, Bruno & Tran, Kien C., 2010. "Threshold effects in panel data stochastic frontier models of dairy production in Canada," Economic Modelling, Elsevier, vol. 27(3), pages 641-647, May.
    43. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    44. Donayre Luiggi & Eo Yunjong & Morley James, 2018. "Improving likelihood-ratio-based confidence intervals for threshold parameters in finite samples," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(1), pages 1-11, February.
    45. Yuanqing Zhang & Chunrong Ai & Yaqin Feng, 2024. "Threshold effect in varying coefficient models with unknown heteroskedasticity," Computational Statistics, Springer, vol. 39(3), pages 1165-1181, May.
    46. Li, Dong & Tong, Howell, 2016. "Nested sub-sample search algorithm for estimation of threshold models," LSE Research Online Documents on Economics 68880, London School of Economics and Political Science, LSE Library.
    47. Rothfelder, Mario & Boldea, Otilia, 2019. "Testing for a Threshold in Models with Endogenous Regressors," Other publications TiSEM 94a7c921-f27f-43a0-82f4-4, Tilburg University, School of Economics and Management.
    48. Li, Ting & Shi, Chengchun & Lu, Zhaohua & Li, Yi & Zhu, Hongtu, 2024. "Evaluating dynamic conditional quantile treatment effects with applications in ridesharing," LSE Research Online Documents on Economics 122488, London School of Economics and Political Science, LSE Library.
    49. Li, Dong & Ling, Shiqing, 2012. "On the least squares estimation of multiple-regime threshold autoregressive models," Journal of Econometrics, Elsevier, vol. 167(1), pages 240-253.
    50. Dong Li & Shiqing Ling & Rongmao Zhang, 2016. "On a Threshold Double Autoregressive Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 68-80, January.
    51. Laurent Callot & Mehmet Caner & Anders Bredahl Kock & Juan Andres Riquelme, 2015. "Sharp Threshold Detection Based on Sup-norm Error rates in High-dimensional Models," CREATES Research Papers 2015-10, Department of Economics and Business Economics, Aarhus University.
    52. Bruce E. Hansen, 2017. "Regression Kink With an Unknown Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(2), pages 228-240, April.
    53. Sadikoglu, Serhan, 2019. "Essays in econometric theory," Other publications TiSEM 99d83644-f9dc-49e3-a4e1-5, Tilburg University, School of Economics and Management.
    54. Yan Sun & Wei Huang, 2024. "Estimation and testing of kink regression model with endogenous regressors," Computational Statistics, Springer, vol. 39(6), pages 3115-3135, September.
    55. Chen, Haiqiang & Li, Yingxing & Lin, Ming & Zhu, Yanli, 2018. "A Regime Shift Model with Nonparametric Switching Mechanism," IRTG 1792 Discussion Papers 2018-048, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    56. Seo, Myung Hwan & Koo, Bonsoo & Yang, Yangzhuoran Fin, 2024. "Nonlinear dynamics of Kimchi premium," Economic Modelling, Elsevier, vol. 135(C).
    57. Iglesias Emma M, 2010. "First and Second Order Asymptotic Bias Correction of Nonlinear Estimators in a Non-Parametric Setting and an Application to the Smoothed Maximum Score Estimator," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-30, May.
    58. Duan Lianjie, 2023. "Export Cutoff Productivity, Uncertainty and Duration of Waiting for Exporting," Economics - The Open-Access, Open-Assessment Journal, De Gruyter, vol. 17(1), pages 1-19, January.
    59. Daniel J. Henderson & Christopher F. Parmeter & Liangjun Su, 2017. "M-Estimation of a Nonparametric Threshold Regression Model," Working Papers 2017-15, University of Miami, Department of Economics.
    60. Zhu Yanli & Chen Haiqiang & Lin Ming, 2019. "Threshold models with time-varying threshold values and their application in estimating regime-sensitive Taylor rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(5), pages 1-17, December.

  94. Post, G.T. & Linton, O. & Whang, Y-J., 2005. "Testing for Stochastic Dominance Efficiency," ERIM Report Series Research in Management ERS-2005-033-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Cited by:

    1. Arvanitis, Stelios & Topaloglou, Nikolas, 2017. "Testing for prospect and Markowitz stochastic dominance efficiency," Journal of Econometrics, Elsevier, vol. 198(2), pages 253-270.
    2. Duc Khuong Nguyen & Nikolas Topaloglou & Thomas Walther, 2020. "Asset Classes and Portfolio Diversification: Evidence from a Stochastic Spanning Approach," Working Papers 2020-009, Department of Research, Ipag Business School.
    3. Sungro Lee, Chang Sik Kim, In-Moo Kim & Chang Sik Kim & In-Moo Kim, 2012. "Testing the Monday Effect using High-frequency Intraday Returns: A Spatial Dominance Approach," Korean Economic Review, Korean Economic Association, vol. 28, pages 69-90.

  95. Kim, Woocheol & Linton, Oliver B., 2004. "The live method for generalized additive volatility models," LSE Research Online Documents on Economics 321, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Peter C.B. Phillips & Ke-Li Xu, 2007. "Tilted Nonparametric Estimation of Volatility Functions," Cowles Foundation Discussion Papers 1612, Cowles Foundation for Research in Economics, Yale University, revised Jul 2010.
    2. Douglas Gomes dos Santos & Flávio Augusto Ziegelmann, 2008. "Estimação de volatilidade em períodos de crise: Modelos aditivos semi-paramétricos versus modelos versus modelo Garch," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807201932370, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    3. Xu, Ke-Li & Phillips, Peter C. B., 2011. "Tilted Nonparametric Estimation of Volatility Functions With Empirical Applications," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 518-528.

  96. Linton, Oliver & Mammen, Enno, 2004. "Estimating semiparametric ARCH (∞) models by kernel smoothing methods," LSE Research Online Documents on Economics 24762, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Xilong Chen & Eric Ghysels, 2011. "News--Good or Bad--and Its Impact on Volatility Predictions over Multiple Horizons," The Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 46-81, October.
    2. Ai, Chunrong & Chen, Xiaohong, 2007. "Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables," Journal of Econometrics, Elsevier, vol. 141(1), pages 5-43, November.
    3. Dufour, Jean-Marie & García, René & Taamouti, Abderrahim, 2008. "Measuring causality between volatility and returns with high-frequency data," UC3M Working papers. Economics we084422, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Gagliardini, Patrick & Scaillet, Olivier, 2012. "Tikhonov regularization for nonparametric instrumental variable estimators," Journal of Econometrics, Elsevier, vol. 167(1), pages 61-75.
    5. Iglesias, Emma M. & Linton, Oliver, 2009. "Estimation of tail thickness parameters from GJR-GARCH models," UC3M Working papers. Economics we094726, Universidad Carlos III de Madrid. Departamento de Economía.
    6. Hidalgo, Javier & Zaffaroni, Paolo, 2007. "A goodness-of-fit test for ARCH([infinity]) models," Journal of Econometrics, Elsevier, vol. 141(2), pages 835-875, December.
    7. Yu, Jun, 2012. "A semiparametric stochastic volatility model," Journal of Econometrics, Elsevier, vol. 167(2), pages 473-482.
    8. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.
    9. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2013. "A nonparametric test of a strong leverage hypothesis," CeMMAP working papers 28/13, Institute for Fiscal Studies.
    10. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
    11. HAFNER, Christian & PREMINGER, Arie, 2016. "On Asymptotic Theory for ARCH(infinite) Models," LIDAM Discussion Papers CORE 2016030, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Degui Li & Oliver Linton & Zudi Lu, 2012. "A flexible semiparametric model for time series," CeMMAP working papers CWP28/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Linton, O. & Xiao, Z., 2019. "Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity," Cambridge Working Papers in Economics 1907, Faculty of Economics, University of Cambridge.
    14. Songhua Tan & Qianqian Zhu, 2022. "Asymmetric linear double autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 371-388, May.
    15. Degui Li & Oliver Linton & Zudi Lu, 2010. "Loch Linear Fitting under Near Epoch Dependence: Uniform Consistency with Convergence Rate," STICERD - Econometrics Paper Series 549, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    16. Hou, Ai Jun, 2013. "Asymmetry effects of shocks in Chinese stock markets volatility: A generalized additive nonparametric approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 23(C), pages 12-32.
    17. Royer, Julien, 2021. "Conditional asymmetry in Power ARCH($\infty$) models," MPRA Paper 109118, University Library of Munich, Germany.
    18. Matthieu Garcin & Clément Goulet, 2015. "Non-parameteric news impact curve: a variational approach," Documents de travail du Centre d'Economie de la Sorbonne 15086r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Jul 2016.
    19. Woocheol Kim, 2004. "Identification And Estimation Of Nonparametric Structural," Econometric Society 2004 Far Eastern Meetings 733, Econometric Society.
    20. Wilson Ye Chen & Richard H. Gerlach, 2017. "Semiparametric GARCH via Bayesian model averaging," Papers 1708.07587, arXiv.org.
    21. Connor, Gregory & Hagmann, Matthias & Linton, Oliver, 2007. "Efficient estimation of a semiparametric characteristic-based factor model of security returns," LSE Research Online Documents on Economics 24504, London School of Economics and Political Science, LSE Library.
    22. Dahl Christian M & Iglesias Emma, 2011. "Modeling the Volatility-Return Trade-Off When Volatility May Be Nonstationary," Journal of Time Series Econometrics, De Gruyter, vol. 3(1), pages 1-32, February.
    23. Oliver Linton & Sorawoot Srisuma, 2010. "Semiparametric Estimation of Markov Decision Processeswith Continuous State Space," STICERD - Econometrics Paper Series 550, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    24. Muhammad Surajo Sanusi, 2017. "Investigating the sources of Black’s leverage effect in oil and gas stocks," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1318812-131, January.
    25. Stanislav Anatolyev, 2005. "Optimal Instruments in Time Series: A Survey," Working Papers w0069, New Economic School (NES).
    26. Zaffaroni, Paolo, 2009. "Whittle estimation of EGARCH and other exponential volatility models," Journal of Econometrics, Elsevier, vol. 151(2), pages 190-200, August.
    27. Degiannakis, Stavros & Floros, Christos & Livada, Alexandra, 2012. "Evaluating Value-at-Risk Models before and after the Financial Crisis of 2008: International Evidence," MPRA Paper 80463, University Library of Munich, Germany.
    28. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.
    29. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2012. "A nonparametric test of the leverage hypothesis," CeMMAP working papers CWP24/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. Meister, Alexander & Kreiß, Jens-Peter, 2016. "Statistical inference for nonparametric GARCH models," Stochastic Processes and their Applications, Elsevier, vol. 126(10), pages 3009-3040.
    31. Degui Li & Zudi Lu & Oliver Linton, 2011. "Local Linear Fitting Under Near Epoch Dependence: Uniform consistency with Convergence Rates," Monash Econometrics and Business Statistics Working Papers 16/11, Monash University, Department of Econometrics and Business Statistics.
    32. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    33. Fengler, M.R. & Mammen, E. & Vogt, M., 2015. "Specification and structural break tests for additive models with applications to realized variance data," Journal of Econometrics, Elsevier, vol. 188(1), pages 196-218.
    34. Linton, Oliver B. & Mammen, Enno, 2008. "Nonparametric transformation to white noise," Journal of Econometrics, Elsevier, vol. 142(1), pages 241-264, January.
    35. Heejoon Han & Shen Zhang, 2012. "Non‐stationary non‐parametric volatility model," Econometrics Journal, Royal Economic Society, vol. 15(2), pages 204-225, June.
    36. Chen, Xiaohong & Huang, Zhuo & Yi, Yanping, 2021. "Efficient estimation of multivariate semi-nonparametric GARCH filtered copula models," Journal of Econometrics, Elsevier, vol. 222(1), pages 484-501.
    37. Xiaohong Chen & Zhuo Huang & Yanping Yi, 2019. "Efficient Estimation of Multivariate Semi-nonparametric GARCH Filtered Copula Models," Cowles Foundation Discussion Papers 2215, Cowles Foundation for Research in Economics, Yale University.
    38. Benoit Perron, 2004. "Détection non paramétrique de sauts dans la volatilité des marchés financiers," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 229-251.
    39. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    40. Mammen, Enno & Park, Byeong U. & Schienle, Melanie, 2012. "Additive models: Extensions and related models," SFB 649 Discussion Papers 2012-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    41. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    42. Dag Tjøstheim, 2012. "Rejoinder on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 469-476, September.
    43. Matthieu Garcin & Clément Goulet, 2015. "Non-parameteric news impact curve: a variational approach," Documents de travail du Centre d'Economie de la Sorbonne 15086rr, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Feb 2017.

  97. Michael Sabbatini & Oliver Linton, 2004. "A GARCH Model of the Implied Volatility of the Swiss Market Index From Option Pricesdffrom Options Prices," FMG Discussion Papers dp516, Financial Markets Group.

    Cited by:

    1. Kiyotaka Satoyoshi & Hidetoshi Mitsui, 2011. "Empirical Study of Nikkei 225 Options with the Markov Switching GARCH Model," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 18(1), pages 55-68, March.

  98. Oliver Linton, 2004. "Nonparametric inference for unbalance time series data," CeMMAP working papers 06/04, Institute for Fiscal Studies.

    Cited by:

    1. Phillips, Peter C.B., 2005. "Automated Discovery In Econometrics," Econometric Theory, Cambridge University Press, vol. 21(1), pages 3-20, February.
    2. Andrew J. Patton, 2006. "Estimation of multivariate models for time series of possibly different lengths," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 147-173.

  99. Arthur Lewbel & Oliver Linton, 2003. "Nonparametric estimation of homothetic and homothetically separable functions," CeMMAP working papers 14/03, Institute for Fiscal Studies.

    Cited by:

    1. Muhammad Nazmul Khan, 2022. "Estimating empirical marginal adjustment cost function: a power series approach," Empirical Economics, Springer, vol. 63(6), pages 3185-3210, December.

  100. Oliver Linton & Yoon-Jae Whang, 2003. "A Quantilogram Approach to Evaluating Directional Predictability," STICERD - Econometrics Paper Series 463, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.
    2. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, Center for Economic and Financial Research (CEFIR).
    3. Gilbert W. Bassett Jr Bassett & Roger Koenker & Gregory Kordas, 2004. "Pessimistic portfolio allocation and Choquet expected utility," CeMMAP working papers CWP09/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
    5. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    6. Gilbert W. Bassett Jr Bassett & Roger Koenker & Gregory Kordas, 2004. "Pessimistic portfolio allocation and Choquet expected utility," CeMMAP working papers 09/04, Institute for Fiscal Studies.

  101. Wolfgang Härdle & Oliver Linton & Wang & Qihua, 2003. "Semiparametric regression analysis with missing response at random," CeMMAP working papers 11/03, Institute for Fiscal Studies.

    Cited by:

    1. Wangli Xu & Xu Guo, 2013. "Nonparametric checks for varying coefficient models with missing response at random," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(4), pages 459-482, May.
    2. Ioannis Kalogridis & Gerda Claeskens & Stefan Aelst, 2023. "Robust and efficient estimation of nonparametric generalized linear models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(3), pages 1055-1078, September.
    3. Lai, Peng & Wang, Qihua, 2014. "Semiparametric efficient estimation for partially linear single-index models with responses missing at random," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 33-50.
    4. Øystein Sørensen & Anders M. Fjell & Kristine B. Walhovd, 2023. "Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 456-486, June.
    5. Zhong, Ping-Shou & Chen, Sixia, 2014. "Jackknife empirical likelihood inference with regression imputation and survey data," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 193-205.
    6. Ash Abebe & Huybrechts F. Bindele & Masego Otlaadisa & Boikanyo Makubate, 2021. "Robust estimation of single index models with responses missing at random," Statistical Papers, Springer, vol. 62(5), pages 2195-2225, October.
    7. Qihua Wang & Tao Zhang & Wolfgang Karl Härdle, 2016. "An Extended Single-index Model with Missing Response at Random," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1140-1152, December.
    8. Sun, Zhihua & Wang, Qihua & Dai, Pengjie, 2009. "Model checking for partially linear models with missing responses at random," Journal of Multivariate Analysis, Elsevier, vol. 100(4), pages 636-651, April.
    9. Sun, Shilin & Li, Qi & Hu, Wenyang & Liang, Zhongchao & Wang, Tianyang & Chu, Fulei, 2023. "Wind turbine blade breakage detection based on environment-adapted contrastive learning," Renewable Energy, Elsevier, vol. 219(P2).
    10. Majid Mojirsheibani & Timothy Reese, 2017. "Kernel regression estimation for incomplete data with applications," Statistical Papers, Springer, vol. 58(1), pages 185-209, March.
    11. Bianco, Ana & Boente, Graciela & González-Manteiga, Wenceslao & Pérez-González, Ana, 2010. "Estimation of the marginal location under a partially linear model with missing responses," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 546-564, February.
    12. Dlugosz, Stephan & Mammen, Enno & Wilke, Ralf A., 2015. "Generalised partially linear regression with misclassified data and an application to labour market transitions," ZEW Discussion Papers 15-043, ZEW - Leibniz Centre for European Economic Research.
    13. Katarzyna Reluga & María‐José Lombardía & Stefan Sperlich, 2023. "Simultaneous inference for linear mixed model parameters with an application to small area estimation," International Statistical Review, International Statistical Institute, vol. 91(2), pages 193-217, August.
    14. Tang, Niansheng & Xia, Linli & Yan, Xiaodong, 2019. "Feature screening in ultrahigh-dimensional partially linear models with missing responses at random," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 208-227.
    15. Chen, Songxi, 2012. "Estimation in semiparametric models with missing data," MPRA Paper 46216, University Library of Munich, Germany.
    16. Waleed B. Altukhaes & Mahdi Roozbeh & Nur A. Mohamed, 2024. "Robust Liu Estimator Used to Combat Some Challenges in Partially Linear Regression Model by Improving LTS Algorithm Using Semidefinite Programming," Mathematics, MDPI, vol. 12(17), pages 1-23, September.
    17. Wangli Xu & Xu Guo & Lixing Zhu, 2012. "Goodness-of-fitting for partial linear model with missing response at random," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(1), pages 103-118.
    18. Benjamin Owusu & Bettina Bökemeier & Alfred Greiner, 2023. "Assessing nonlinearities and heterogeneity in debt sustainability analysis: a panel spline approach," Empirical Economics, Springer, vol. 64(3), pages 1315-1346, March.
    19. Nengxiang Ling & Rui Kan & Philippe Vieu & Shuyu Meng, 2019. "Semi-functional partially linear regression model with responses missing at random," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(1), pages 39-70, January.
    20. Vahid Goodarzi Vanani & Davood Shahsavani & Mohammad Kazemi, 2025. "A robust partial linear model combining modified Huber loss function and variable selection," Statistical Papers, Springer, vol. 66(6), pages 1-28, October.
    21. Duran, Esra Akdeniz & Härdle, Wolfgang Karl & Osipenko, Maria, 2011. "Difference based ridge and Liu type estimators in semiparametric regression models," SFB 649 Discussion Papers 2011-014, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    22. Kalogridis, Ioannis & Van Aelst, Stefan, 2023. "Robust penalized estimators for functional linear regression," Journal of Multivariate Analysis, Elsevier, vol. 194(C).
    23. Bravo, Francesco & Escanciano, Juan Carlos & Van Keilegom, Ingrid, 2015. "Wilks' Phenomenon in Two-Step Semiparametric Empirical Likelihood Inference," LIDAM Discussion Papers ISBA 2015016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    24. Wang, Qihua & Sun, Zhihua, 2007. "Estimation in partially linear models with missing responses at random," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1470-1493, August.
    25. Lu Wang & Zhongzhe Ouyang & Xihong Lin, 2024. "Doubly Robust Estimation and Semiparametric Efficiency in Generalized Partially Linear Models with Missing Outcomes," Stats, MDPI, vol. 7(3), pages 1-20, August.
    26. Chen, Xiaohong & Hong, Han & Tarozzi, Alessandro, 2008. "Semiparametric Efficiency in GMM Models of Nonclassical Measurement Errors, Missing Data and Treatment Effects," Working Papers 42, Yale University, Department of Economics.
    27. Elizabeth Goult & Laura Andrea Barrero Guevara & Michael Briga & Matthieu Domenech de Cellès, 2024. "Estimating the optimal age for infant measles vaccination," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    28. Caldeira, João F. & Santos, André A.P. & Torrent, Hudson S., 2023. "Semiparametric portfolios: Improving portfolio performance by exploiting non-linearities in firm characteristics," Economic Modelling, Elsevier, vol. 122(C).
    29. Goepp, Vivien & Bouaziz, Olivier & Nuel, Grégory, 2025. "Spline regression with automatic knot selection," Computational Statistics & Data Analysis, Elsevier, vol. 202(C).
    30. M. Hristache & V. Patilea, 2017. "Conditional moment models with data missing at random," Biometrika, Biometrika Trust, vol. 104(3), pages 735-742.
    31. Inkmann, J., 2005. "Inverse Probability Weighted Generalised Empirical Likelihood Estimators : Firm Size and R&D Revisited," Discussion Paper 2005-131, Tilburg University, Center for Economic Research.
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    Cited by:

    1. Nir Billfeld & Moshe Kim, 2019. "Semiparametric Wavelet-based JPEG IV Estimator for endogenously truncated data," Papers 1908.02166, arXiv.org.
    2. David Jacho-Chavez & Arthur Lewbel & Oliver Linton, 2006. "Identification and Nonparametric Estimation of a Transformed Additively Separable Model," Boston College Working Papers in Economics 652, Boston College Department of Economics, revised 26 Nov 2008.
    3. Le-Yu Chen, 2009. "Identification of structural dynamic discrete choice models," CeMMAP working papers CWP08/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Patrick Saart & Jiti Gao & Nam Hyun Kim, 2014. "Semiparametric methods in nonlinear time series analysis: a selective review," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 141-169, March.
    5. Daniel J. Henderson, 2009. "A Non‐parametric Examination of Capital–Skill Complementarity," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(4), pages 519-538, August.
    6. Escanciano, Juan Carlos & Jacho-Chávez, David T. & Lewbel, Arthur, 2014. "Uniform convergence of weighted sums of non and semiparametric residuals for estimation and testing," Journal of Econometrics, Elsevier, vol. 178(P3), pages 426-443.
    7. Delgado, Miguel A. & Escanciano, Juan Carlos, 2012. "Distribution-free tests of stochastic monotonicity," Journal of Econometrics, Elsevier, vol. 170(1), pages 68-75.
    8. Centorrino, Samuele & Florens, Jean-Pierre, 2021. "Nonparametric Instrumental Variable Estimation of Binary Response Models with Continuous Endogenous Regressors," Econometrics and Statistics, Elsevier, vol. 17(C), pages 35-63.
    9. Denis Chetverikov & Daniel Wilhelm & Dongwoo Kim, 2020. "An Adaptive Test of Stochastic Monotonicity," CeMMAP working papers CWP17/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Dong, Yingying & Lewbel, Arthur, 2011. "Nonparametric identification of a binary random factor in cross section data," Journal of Econometrics, Elsevier, vol. 163(2), pages 163-171, August.
    11. Sungwon Lee, 2020. "Nonparametric Identification and Estimation of Panel Quantile Models with Sample Selection," Working Papers 2012, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).

  104. Woocheol Kim & Oliver Linton, 2003. "A Local Instrumental Variable Estimation Method for Generalized Additive Volatility Models," STICERD - Econometrics Paper Series 456, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Chen, Bin & Song, Zhaogang, 2013. "Testing whether the underlying continuous-time process follows a diffusion: An infinitesimal operator-based approach," Journal of Econometrics, Elsevier, vol. 173(1), pages 83-107.
    2. Chen, Bin & Hong, Yongmiao, 2012. "Testing For The Markov Property In Time Series," Econometric Theory, Cambridge University Press, vol. 28(1), pages 130-178, February.
    3. Heejoon Han & Shen Zhang, 2012. "Non‐stationary non‐parametric volatility model," Econometrics Journal, Royal Economic Society, vol. 15(2), pages 204-225, June.

  105. Oliver Linton & Enno Mammen, 2003. "Estimating Semiparametric ARCH (8) Models by Kernel Smoothing Methods," STICERD - Econometrics Paper Series 453, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Woocheol Kim, 2004. "Identification And Estimation Of Nonparametric Structural," Econometric Society 2004 Far Eastern Meetings 733, Econometric Society.
    2. O. Linton & E. Mammen, 2005. "Estimating Semiparametric ARCH(∞) Models by Kernel Smoothing Methods," Econometrica, Econometric Society, vol. 73(3), pages 771-836, May.
    3. Oliver Linton & Sorawoot Srisuma, 2010. "Semiparametric Estimation of Markov Decision Processeswith Continuous State Space," STICERD - Econometrics Paper Series 550, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    4. Benoit Perron, 2004. "Détection non paramétrique de sauts dans la volatilité des marchés financiers," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 229-251.

  106. Oliver Linton & Mototsugu Shintani, 2002. "Nonparametric Neutral Network Estimation of Lyapunov Exponents and a Direct Test for Chaos," STICERD - Econometrics Paper Series 434, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Park, Joon Y. & Whang, Yoon-Jae, 2012. "Random walk or chaos: A formal test on the Lyapunov exponent," Journal of Econometrics, Elsevier, vol. 169(1), pages 61-74.
    2. Matilla-García, Mariano & Marín, Manuel Ruiz, 2010. "A new test for chaos and determinism based on symbolic dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 600-614, December.
    3. Bask, Miia & Bask, Mikael, 2013. "Social Influence and the Matthew Mechanism: The Case of an Artificial Cultural Market," Working Paper Series 2013:11, Uppsala University, Department of Economics.
    4. Cars Hommes & Sebastiano Manzan, 2006. "Testing for Nonlinear Structure and Chaos in Economic Time. A Comment," Tinbergen Institute Discussion Papers 06-030/1, Tinbergen Institute.
    5. Borusyak, K., 2011. "Nonlinear Dynamics of the Russian Stock Market in Problems of Risk Management," Journal of the New Economic Association, New Economic Association, issue 11, pages 85-105.
    6. Bask, Mikael, 2007. "Measuring potential market risk," Bank of Finland Research Discussion Papers 20/2007, Bank of Finland.
    7. Belaire-Franch, Jorge, 2018. "Exchange rates expectations and chaotic dynamics: A replication study," Economics Discussion Papers 2018-34, Kiel Institute for the World Economy (IfW Kiel).
    8. Kyrtsou, Catherine & Serletis, Apostolos, 2006. "Univariate tests for nonlinear structure," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 154-168, March.
    9. Dominique Guegan & Justin Leroux, 2008. "Forecasting chaotic systems : the role of local Lyapunov exponents," Post-Print halshs-00259238, HAL.
    10. William Barnett, 2005. "Comment on 'Chaotic Monetary Dynamics with Confidence'," Macroeconomics 0505017, University Library of Munich, Germany.
    11. Bask, Mikael & Widerberg, Anna, 2007. "The Stability and Volatility of Electricity Prices: An Illustration of (lambda, sigma-2) Analysis," Working Papers in Economics 267, University of Gothenburg, Department of Economics.
    12. Lorenzo Trapani, 2021. "Testing for strict stationarity in a random coefficient autoregressive model," Econometric Reviews, Taylor & Francis Journals, vol. 40(3), pages 220-256, April.
    13. Dominique Guégan & Justin Leroux, 2007. "Forecasting chaotic systems: The role of local Lyapunov exponents," Cahiers de recherche 07-12, HEC Montréal, Institut d'économie appliquée.
    14. Mastroeni, Loretta & Vellucci, Pierluigi & Naldi, Maurizio, 2019. "A reappraisal of the chaotic paradigm for energy commodity prices," Energy Economics, Elsevier, vol. 82(C), pages 167-178.
    15. Elena Olmedo & Ricardo Gimeno & Lorenzo Escot & Ruth Mateos, 2007. "Convergencia y Estabilidad de los Tipos de Cambio Europeos: Una Aplicación de Exponentes de Lyapunov," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 44(129), pages 91-108.
    16. Mototsugu Shintani, 2004. "A Dynamic Factor Approach to Nonlinear Stability Analysis," Vanderbilt University Department of Economics Working Papers 0418, Vanderbilt University Department of Economics.
    17. Santamaría-Bonfil, G. & Reyes-Ballesteros, A. & Gershenson, C., 2016. "Wind speed forecasting for wind farms: A method based on support vector regression," Renewable Energy, Elsevier, vol. 85(C), pages 790-809.
    18. Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    19. Dominique Guegan & Justin Leroux, 2009. "Local Lyapunov Exponents: A new way to predict chaotic systems," PSE-Ecole d'économie de Paris (Postprint) halshs-00511996, HAL.
    20. Charles-Cadogan, G., 2021. "Market Instability, Investor Sentiment, And Probability Judgment Error in Index Option Prices," CRETA Online Discussion Paper Series 71, Centre for Research in Economic Theory and its Applications CRETA.
    21. Marco Pangallo, 2023. "Synchronization of endogenous business cycles," LEM Papers Series 2023/01, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    22. Marisa Faggini & Bruna Bruno & Anna Parziale, 2019. "Does Chaos Matter in Financial Time Series Analysis?," International Journal of Economics and Financial Issues, Econjournals, vol. 9(4), pages 18-24.
    23. Vitaliy Vandrovych, 2005. "Study of Nonlinearities in the Dynamics of Exchange Rates: Is There Any Evidence of Chaos?," Computing in Economics and Finance 2005 234, Society for Computational Economics.
    24. Serletis, Apostolos & Shahmoradi, Asghar, 2007. "Chaos, self-organized criticality, and SETAR nonlinearity: An analysis of purchasing power parity between Canada and the United States," Chaos, Solitons & Fractals, Elsevier, vol. 33(5), pages 1437-1444.
    25. Patrick Krieger & Carsten Lausberg & Kristin Wellner, 2018. "Einblicke in die Gründe für nicht-normalverteilte Immobilienrenditen: eine explorative Untersuchung deutscher Wohnimmobilienportfolios [Insights into the reasons for non-normal real estate returns:," Zeitschrift für Immobilienökonomie (German Journal of Real Estate Research), Springer;Gesellschaft für Immobilienwirtschaftliche Forschung e. V., vol. 4(1), pages 49-79, November.
    26. Dominique Guégan & Justin Leroux, 2008. "Local Lyapunov exponents: Zero plays no role in Forecasting chaotic systems," Cahiers de recherche 08-10, HEC Montréal, Institut d'économie appliquée.
    27. Serletis, Apostolos & Uritskaya, Olga Y., 2007. "Detecting signatures of stochastic self-organization in US money and velocity measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 281-291.
    28. Bask, Mikael & Liu, Tung & Widerberg, Anna, 2007. "The stability of electricity prices: Estimation and inference of the Lyapunov exponents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 565-572.
    29. Serletis, Apostolos & Shahmoradi, Asghar & Serletis, Demitre, 2007. "Effect of noise on estimation of Lyapunov exponents from a time series," Chaos, Solitons & Fractals, Elsevier, vol. 32(2), pages 883-887.
    30. BenSaïda, Ahmed & Litimi, Houda, 2013. "High level chaos in the exchange and index markets," Chaos, Solitons & Fractals, Elsevier, vol. 54(C), pages 90-95.
    31. Matilla-Garci­a, Mariano & Ruiz Mari­n, Manuel, 2008. "A non-parametric independence test using permutation entropy," Journal of Econometrics, Elsevier, vol. 144(1), pages 139-155, May.
    32. Lucía Inglada-Pérez & Sandra González y Gil, 2024. "A Study on the Nature of Complexity in the Spanish Electricity Market Using a Comprehensive Methodological Framework," Mathematics, MDPI, vol. 12(6), pages 1-21, March.
    33. Dominique Guegan & Justin Leroux, 2009. "Local Lyapunov Exponents: A new way to predict chaotic systems," Post-Print halshs-00511996, HAL.
    34. Mariano Matilla-García, 2007. "Nonlinear Dynamics in Energy Futures," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 7-30.
    35. Kyrtsou, Catherine & Malliaris, Anastasios G. & Serletis, Apostolos, 2009. "Energy sector pricing: On the role of neglected nonlinearity," Energy Economics, Elsevier, vol. 31(3), pages 492-502, May.
    36. Bask, Mikael & Widerberg, Anna, 2009. "Market structure and the stability and volatility of electricity prices," Energy Economics, Elsevier, vol. 31(2), pages 278-288, March.
    37. Guégan, Dominique & Leroux, Justin, 2009. "Forecasting chaotic systems: The role of local Lyapunov exponents," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2401-2404.
    38. Dominique Guegan & Justin Leroux, 2010. "Predicting chaos with Lyapunov exponents: Zero plays no role in forecasting chaotic systems," Post-Print halshs-00462454, HAL.
    39. Dominique Guegan, 2009. "Chaos in Economics and Finance," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00375713, HAL.
    40. Serletis, Apostolos & He, Mingyu & Chowdhury, M.M. Islam, 2023. "Chaos in long-maturity real rates," Economics Letters, Elsevier, vol. 225(C).
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    43. Sandubete, Julio E. & Escot, Lorenzo, 2020. "Chaotic signals inside some tick-by-tick financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    44. Jorge Belaire-Franch & Kwaku Opong, 2013. "A Time Series Analysis of U.K. Construction and Real Estate Indices," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 516-542, April.
    45. Miia Bask & Mikael Bask, 2015. "Cumulative (Dis)Advantage and the Matthew Effect in Life-Course Analysis," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-14, November.
    46. Serletis, Apostolos & Shintani, Mototsugu, 2006. "Chaotic monetary dynamics with confidence," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 228-252, March.
    47. Pangallo, Marco, 2025. "Synchronization of endogenous business cycles," Journal of Economic Behavior & Organization, Elsevier, vol. 229(C).
    48. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.
    49. Marco Pangallo, 2020. "Synchronization of endogenous business cycles," Papers 2002.06555, arXiv.org, revised Sep 2024.
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    Cited by:

    1. Saraswata Chaudhuriy & David T. Frazierz & Eric Renault, 2016. "Indirect Inference with Endogenously Missing Exogenous Variables," CIRANO Working Papers 2016s-15, CIRANO.
    2. Anisha Ghosh & Oliver Linton, 2019. "Estimation with Mixed Data Frequencies: A Bias-Correction Approach," CeMMAP working papers CWP65/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Negera Wakgari Deresa & Ingrid Van Keilegom, 2025. "Semiparametric transformation models for survival data with dependent censoring," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 77(3), pages 425-457, June.
    4. Ai, Chunrong & Chen, Xiaohong, 2007. "Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables," Journal of Econometrics, Elsevier, vol. 141(1), pages 5-43, November.
    5. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    6. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    7. Luciano de Castro & Antonio F. Galvao & David M. Kaplan & Xin Liu, 2017. "Smoothed GMM for quantile models," Papers 1707.03436, arXiv.org, revised Feb 2018.
    8. Dong, Yingying, 2010. "Endogenous regressor binary choice models without instruments, with an application to migration," Economics Letters, Elsevier, vol. 107(1), pages 33-35, April.
    9. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.
    10. Muller, Christophe, 2018. "Heterogeneity and nonconstant effect in two-stage quantile regression," Econometrics and Statistics, Elsevier, vol. 8(C), pages 3-12.
    11. Le-Yu Chen & Sokbae (Simon) Lee, 2017. "Exact computation of GMM estimators for instrumental variable quantile regression models," CeMMAP working papers CWP52/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Sokbae (Simon) Lee & Kyungchui (Kevin) Song & Yoon-Jae Whang, 2014. "Testing for a general class of functional inequalities," CeMMAP working papers CWP09/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Dennis Kristensen, 2009. "Semiparametric modelling and estimation (in Russian)," Quantile, Quantile, issue 7, pages 53-83, September.
    14. Xiaohong Chen & Demian Pouzo, 2012. "Estimation of Nonparametric Conditional Moment Models With Possibly Nonsmooth Generalized Residuals," Econometrica, Econometric Society, vol. 80(1), pages 277-321, January.
    15. Chen, Xiaohong & Liao, Zhipeng, 2014. "Sieve M inference on irregular parameters," Journal of Econometrics, Elsevier, vol. 182(1), pages 70-86.
    16. Clément de Chaisemartin & Xavier d'Haultfoeuille, 2014. "Fuzzy Changes-in-Changes," Working Papers 2014-18, Center for Research in Economics and Statistics.
    17. Florens, Jean-Pierre & Johannes, Jan & Van Bellegem, Sébastien, 2009. "Instrumental Regression in Partially Linear Models," TSE Working Papers 10-167, Toulouse School of Economics (TSE).
    18. Tae-Hwan Kim & Christophe Muller, 2017. "A Robust Test of Exogeneity Based on Quantile Regressions," AMSE Working Papers 1716, Aix-Marseille School of Economics, France.
    19. Debopam Bhattacharya & Pascaline Dupas, 2008. "Inferring Welfare Maximizing Treatment Assignment under Budget Constraints," NBER Working Papers 14447, National Bureau of Economic Research, Inc.
    20. Iglesias, Emma M. & Linton, Oliver, 2009. "Estimation of tail thickness parameters from GJR-GARCH models," UC3M Working papers. Economics we094726, Universidad Carlos III de Madrid. Departamento de Economía.
    21. Alejo, Javier & Galvao, Antonio F. & Montes-Rojas, Gabriel, 2018. "Quantile continuous treatment effects," Econometrics and Statistics, Elsevier, vol. 8(C), pages 13-36.
    22. Salim Bouzebda & Issam Elhattab & Anouar Abdeldjaoued Ferfache, 2022. "General M-Estimator Processes and their m out of n Bootstrap with Functional Nuisance Parameters," Methodology and Computing in Applied Probability, Springer, vol. 24(4), pages 2961-3005, December.
    23. Ji-Liang Shiu & Yingyao Hu, 2010. "Identification and Estimation of Nonlinear Dynamic Panel Data Models with Unobserved Covariates," Economics Working Paper Archive 557, The Johns Hopkins University,Department of Economics.
    24. Luofeng Liao & Christian Kroer, 2024. "Statistical Inference and A/B Testing in Fisher Markets and Paced Auctions," Papers 2406.15522, arXiv.org, revised Mar 2025.
    25. Clément de Chaisemartin, 2012. "Fuzzy differences in differences," Working Papers halshs-00671368, HAL.
    26. D'Haultfoeuille, Xavier & Gaillac, Christophe & Maurel, Arnaud, 2018. "Rationalizing Rational Expectations? Tests and Deviations," IZA Discussion Papers 11989, Institute of Labor Economics (IZA).
    27. Xiaohong Chen & Jinyong Hahn, 2012. "Asymptotic efficiency of semiparametric two-step GMM," CeMMAP working papers CWP31/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    28. Patrick Bajari & Chenghuan Sean Chu & Denis Nekipelov & Minjung Park, 2016. "Identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action," Quantitative Marketing and Economics (QME), Springer, vol. 14(4), pages 271-323, December.
    29. Gyungbae Park, 2024. "Debiased Machine Learning when Nuisance Parameters Appear in Indicator Functions," Papers 2403.15934, arXiv.org, revised Mar 2025.
    30. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "The effect of fragmentation in trading on market quality in the UK equity market," CeMMAP working papers 42/13, Institute for Fiscal Studies.
    31. David T. Frazier & Bonsoo Koo, 2020. "Indirect Inference for Locally Stationary Models," Monash Econometrics and Business Statistics Working Papers 30/20, Monash University, Department of Econometrics and Business Statistics.
    32. Xiaohong Chen & Demian Pouzo, 2008. "Efficient Estimation of Semiparametric Conditional Moment Models with Possibly Nonsmooth Residuals," Cowles Foundation Discussion Papers 1640R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2009.
    33. David Kang & Seojeong Lee, 2025. "Misspecification-Robust Asymptotic and Bootstrap Inference for Nonsmooth GMM," Working Papers 423284005, Lancaster University Management School, Economics Department.
    34. Haoze Hou & Wei Huang & Zheng Zhang, 2025. "Non-parametric Quantile Regression and Uniform Inference with Unknown Error Distribution," Papers 2504.01761, arXiv.org.
    35. Escanciano, Juan Carlos & Jacho-Chávez, David T. & Lewbel, Arthur, 2014. "Uniform convergence of weighted sums of non and semiparametric residuals for estimation and testing," Journal of Econometrics, Elsevier, vol. 178(P3), pages 426-443.
    36. Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP69/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    37. Raymond Carroll & Xiaohong Chen & Yingyao Hu, 2010. "Identification and estimation of nonlinear models using two samples with nonclassical measurement errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(4), pages 419-423.
    38. Dennis Kristensen, 2009. "Pseudo-Maximum Likelihood Estimation in Two Classes of Semiparametric Diffusion Models," CREATES Research Papers 2009-41, Department of Economics and Business Economics, Aarhus University.
    39. Xiaohong Chen & Zhipeng Liao, 2015. "Sieve Semiparametric Two-Step GMM under Weak Dependence," Cowles Foundation Discussion Papers 2012, Cowles Foundation for Research in Economics, Yale University.
    40. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    41. Chen, Xiaohong & Liu, Ying & Ma, Shujie & Zhang, Zheng, 2024. "Causal inference of general treatment effects using neural networks with a diverging number of confounders," Journal of Econometrics, Elsevier, vol. 238(1).
    42. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
    43. Xiaohong Chen & Jack Favilukis & Sydney Ludvigson, 2012. "An estimation of economic models with recursive preferences," CeMMAP working papers 32/12, Institute for Fiscal Studies.
    44. J. Carlos Escanciano & Carlos Velasco, 2010. "Specification tests of parametric dynamic conditional quantiles," Post-Print hal-00732534, HAL.
    45. Elise Coudin & Jean-Marie Dufour, 2009. "Finite-sample distribution-free inference in linear median regressions under heteroscedasticity and non-linear dependence of unknown form," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages 19-49, January.
    46. Laage, Louise, 2024. "A Correlated Random Coefficient panel model with time-varying endogeneity," Journal of Econometrics, Elsevier, vol. 242(2).
    47. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers CWP28/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    48. Komunjer, Ivana, 2002. "Quasi-Maximum Likelihood Estimation for Conditional Quantiles," Working Papers 1139, California Institute of Technology, Division of the Humanities and Social Sciences.
    49. Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2019. "A Unified Framework for Efficient Estimation of General Treatment Models," CeMMAP working papers CWP64/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    50. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2016. "Locally Robust Semiparametric Estimation," Papers 1608.00033, arXiv.org, revised Aug 2020.
    51. Chen, Xiaohong & Pouzo, Demian & Powell, James L., 2019. "Penalized sieve GEL for weighted average derivatives of nonparametric quantile IV regressions," Journal of Econometrics, Elsevier, vol. 213(1), pages 30-53.
    52. Debopam Bhattacharya & Pascaline Dupas & Shin Kanaya, 2013. "Estimating the Impact of Means-tested Subsidies under Treatment Externalities with Application to Anti-Malarial Bednets," Economics Series Working Papers 646, University of Oxford, Department of Economics.
    53. Sungwon Lee & Joon H. Ro, 2020. "Nonparametric Tests for Conditional Quantile Independence with Duration Outcomes," Working Papers 2013, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    54. Anna Kormilitsina & Denis Nekipelov, 2016. "Consistent Variance Of The Laplace‐Type Estimators: Application To Dsge Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(2), pages 603-622, May.
    55. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2014. "Program evaluation with high-dimensional data," CeMMAP working papers CWP33/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    56. Jad Beyhum & Jean-Pierre Florens & Ingrid Keilegom, 2023. "A nonparametric instrumental approach to confounding in competing risks models," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(4), pages 709-734, October.
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    58. Birke, M. & Van Bellegem, S. & Van Keilegom, I., 2014. "Semi-parametric estimation in a single-index model with endogenous variables," LIDAM Discussion Papers ISBA 2014043, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    59. Oliver Linton & Kyungchul Song & Yoon-Jae Whang, 2009. "An Improved Bootstrap Test of Stochastic Dominance," Cowles Foundation Discussion Papers 1713, Cowles Foundation for Research in Economics, Yale University.
    60. Hidehiko Ichimura & Whitney K. Newey, 2022. "The influence function of semiparametric estimators," Quantitative Economics, Econometric Society, vol. 13(1), pages 29-61, January.
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    62. Breunig, Christoph & Haan, Peter, 2021. "Nonparametric regression with selectively missing covariates," Journal of Econometrics, Elsevier, vol. 223(1), pages 28-52.
    63. Kyungchul Song, 2009. "Efficient Estimation of Average Treatment Effects under Treatment-Based Sampling," PIER Working Paper Archive 09-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    64. Delsol , Laurent & Van Keilegom, Ingrid, 2011. "Semiparametric M-Estimation with Non-Smooth Criterion Functions," LIDAM Discussion Papers ISBA 2011041, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    65. Erqian Li & Jianxin Pan & Manlai Tang & Keming Yu & Wolfgang Karl Härdle & Xiaowen Dai & Maozai Tian, 2023. "Weighted Competing Risks Quantile Regression Models and Variable Selection," Mathematics, MDPI, vol. 11(6), pages 1-23, March.
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    68. Chen, Songxi, 2012. "Estimation in semiparametric models with missing data," MPRA Paper 46216, University Library of Munich, Germany.
    69. Sung Jae Jun & Sokbae (Simon) Lee, 2019. "Identifying the effect of persuasion," CeMMAP working papers CWP69/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    70. Jaan Masso & Amaresh K Tiwari, 2024. "Retracted: Estimating Production Function And Productivity Impact Of Export Persistence In Presence Of Market Imperfections," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 150, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    71. D'Haultfoeuille, Xavier & Gaillac, Christophe & Maurel, Arnaud, 2021. "Rationalizing Rational Expectations: Characterizations and Tests," TSE Working Papers 21-1211, Toulouse School of Economics (TSE).
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    74. Degui Li & Oliver Linton & Zudi Lu, 2010. "Loch Linear Fitting under Near Epoch Dependence: Uniform Consistency with Convergence Rate," STICERD - Econometrics Paper Series 549, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    75. J. Carlos Escanciano, 2009. "Asymptotic Distribution-Free Diagnostic Tests For Heteroskedastic Time Series Models," CAEPR Working Papers 2009-019, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    76. Cristian Huse, 2004. "Comparing Nonparametric Regression Quantiles," Econometric Society 2004 Latin American Meetings 165, Econometric Society.
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    87. Delgado, Miguel A. & Escanciano, Juan Carlos, 2011. "Conditional stochastic dominance testing," UC3M Working papers. Economics we1138, Universidad Carlos III de Madrid. Departamento de Economía.
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    93. Dong, Yingying, 2011. "Semiparametric binary random effects models: Estimating two types of drinking behavior," Economics Letters, Elsevier, vol. 112(1), pages 79-81, July.
    94. Huber, Martin & Mellace, Giovanni, 2012. "Relaxing monotonicity in the identification of local average treatment effects," Economics Working Paper Series 1212, University of St. Gallen, School of Economics and Political Science.
    95. Koo, Bonsoo & Linton, Oliver, 2015. "Let’S Get Lade: Robust Estimation Of Semiparametric Multiplicative Volatility Models," Econometric Theory, Cambridge University Press, vol. 31(4), pages 671-702, August.
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    97. BIRKE, Mélanie & VAN BELLEGEM, Sébastien & VAN KEILEGOM, Ingrid, 2016. "Semi-Parametric Estimation in a Single- Index Model with Endogenous Variables," LIDAM Discussion Papers CORE 2016022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    98. Hong, Han & Mahajan, Aprajit & Nekipelov, Denis, 2015. "Extremum estimation and numerical derivatives," Journal of Econometrics, Elsevier, vol. 188(1), pages 250-263.
    99. Khan, Shakeeb, 2013. "Distribution free estimation of heteroskedastic binary response models using Probit/Logit criterion functions," Journal of Econometrics, Elsevier, vol. 172(1), pages 168-182.
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    102. Xiaohong Chen & Jack Fuvilukis & Sydney Ludvigson, 2012. "An Estimation of Economic Models with Recursive Preferences," Cowles Foundation Discussion Papers 1883, Cowles Foundation for Research in Economics, Yale University.
    103. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
    104. Yukitoshi Matsushita & Taisuke Otsu, 2018. "Likelihood Inference on Semiparametric Models: Average Derivative and Treatment Effect," The Japanese Economic Review, Springer, vol. 69(2), pages 133-155, June.
    105. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey, 2016. "Double machine learning for treatment and causal parameters," CeMMAP working papers CWP49/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    106. Weilun Zhou & Jiti Gao & David Harris & Hsein Kew, 2019. "Semiparametric Single-index Predictive Regression," Monash Econometrics and Business Statistics Working Papers 25/19, Monash University, Department of Econometrics and Business Statistics.
    107. Haitian Xie, 2020. "Efficient and Robust Estimation of the Generalized LATE Model," Papers 2001.06746, arXiv.org, revised Feb 2022.
    108. Xiaohong Chen & Yin Jia Qiu, 2016. "Methods for Nonparametric and Semiparametric Regressions with Endogeneity: a Gentle Guide," Cowles Foundation Discussion Papers 2032, Cowles Foundation for Research in Economics, Yale University.
    109. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    110. Le-Yu Chen & Sokbae (Simon) Lee & Myung Jae Sung, 2013. "Maximum score estimation of preference parameters for a binary choice model under uncertainty," CeMMAP working papers 14/13, Institute for Fiscal Studies.
    111. Bravo, Francesco & Escanciano, Juan Carlos & Van Keilegom, Ingrid, 2015. "Wilks' Phenomenon in Two-Step Semiparametric Empirical Likelihood Inference," LIDAM Discussion Papers ISBA 2015016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
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    126. Tae-Hwan Kim & Christophe Muller, 2012. "A test for endogeneity in conditional quantile models," Working papers 2012rwp-49, Yonsei University, Yonsei Economics Research Institute.
    127. Wayne Yuan Gao & Sheng Xu & Kan Xu, 2020. "Two-Stage Maximum Score Estimator," Papers 2009.02854, arXiv.org, revised Sep 2022.
    128. Takuya Ishihara, 2020. "Panel Data Quantile Regression for Treatment Effect Models," Papers 2001.04324, arXiv.org, revised Nov 2021.
    129. Oliver Linton & Sorawoot Srisuma, 2010. "Semiparametric Estimation of Markov Decision Processeswith Continuous State Space," STICERD - Econometrics Paper Series 550, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
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    Cited by:

    1. Dabo-Niang, Sophie & Francq, Christian & Zakoian, Jean-Michel, 2009. "Combining parametric and nonparametric approaches for more efficient time series prediction," MPRA Paper 16893, University Library of Munich, Germany.
    2. Sophie DABO-NIANG & Christian FRANCQ & Jean-Michel ZAKOIAN, 2009. "Combining Nonparametric and Optimal Linear Time Series Predictions," Working Papers 2009-18, Center for Research in Economics and Statistics.

  109. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Wang, 2002. "Consistent testing for stochastic dominance: a subsampling approach," CeMMAP working papers 03/02, Institute for Fiscal Studies.

    Cited by:

    1. Maasoumi, Esfandiar & Racine, Jeff & Stengos, Thanasis, 2007. "Growth and convergence: A profile of distribution dynamics and mobility," Journal of Econometrics, Elsevier, vol. 136(2), pages 483-508, February.
    2. Gonzalo, Jesús & Olmo, José, 2008. "Testing downside risk efficiency under market distress," UC3M Working papers. Economics we084321, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Néstor Gandelman, 2005. "Community tax evasion models: A stochastic dominance test," Journal of Applied Economics, Universidad del CEMA, vol. 8, pages 279-297, November.
    4. Ozkan Eren & Daniel Millimet, 2007. "Time to learn? The organizational structure of schools and student achievement," Empirical Economics, Springer, vol. 32(2), pages 301-332, May.
    5. Jean-Yves Duclos & Wen-Hao Chen, 2009. "Testing for Poverty Dominance: An Application to Canada," UFAE and IAE Working Papers 769.09, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    6. Milunovich, George & Thorp, Susan, 2006. "Valuing volatility spillovers," Global Finance Journal, Elsevier, vol. 17(1), pages 1-22, September.
    7. Park, Joon Y., 2005. "The Spatial Analysis of Time Series," Working Papers 2005-07, Rice University, Department of Economics.
    8. Millimet, Daniel & Wang, Le, 2005. "Is the Quantity-Quality Trade-off Really a Trade-off for All?," Departmental Working Papers 0502, Southern Methodist University, Department of Economics.
    9. Gordon Anderson, 2008. "The empirical assessment of multidimensional welfare, inequality and poverty: Sample weighted multivariate generalizations of the Kolmogorov–Smirnov two sample tests for stochastic dominance," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 6(1), pages 73-87, March.
    10. Dominic Gasbarro & Wing-Keung Wong & J. Kenton Zumwalt, 2007. "Stochastic Dominance Analysis of iShares," The European Journal of Finance, Taylor & Francis Journals, vol. 13(1), pages 89-101.
    11. Maasoumi, Esfandiar & Millimet, Daniel & Sarkar, Dipanwita, 2005. "The Distribution of Returns to Marriage," Departmental Working Papers 0503, Southern Methodist University, Department of Economics.
    12. Suhejla Hoiti & Esfandiar Maasoumi & Michael McAleer & Daniel Slottje, 2005. "Measuring the Volatility in U.S. Treasury Benchmarks and Debt Instruments," DEA Working Papers 14, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    13. Valentina Corradi & Norman R. Swanson, 2003. "A Test for Comparing Multiple Misspecified Conditional Distributions," Departmental Working Papers 200314, Rutgers University, Department of Economics.

  110. Linton, Oliver, 2001. "Estimating additive nonparametric models by partial Lq norm: the curse of fractionality," LSE Research Online Documents on Economics 319, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Efang Kong & Oliver Linton & Yingcun Xia, 2009. "Uniform Bahadur Representation for LocalPolynomial Estimates of M-Regressionand Its Application to The Additive Model," STICERD - Econometrics Paper Series 535, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    2. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    3. Efang Kong & Oliver Linton & Yingcun Xia, 2011. "Global Bahadur representation for nonparametric censored regression quantiles and its applications," CeMMAP working papers CWP33/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  111. Oliver Linton & Zhijie Xiao, 2001. "A Nonparametric Regression Estimator that Adapts to Error Distribution of Unknown Form," STICERD - Econometrics Paper Series 419, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Wang, Dong, 2010. "Modeling epigenetic modifications under multiple treatment conditions," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1179-1189, April.
    2. Linton, O. & Xiao, Z., 2019. "Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity," Cambridge Working Papers in Economics 1907, Faculty of Economics, University of Cambridge.
    3. Moradi Rekabdarkolaee, Hossein & Wang, Qin, 2017. "Variable selection through adaptive MAVE," Statistics & Probability Letters, Elsevier, vol. 128(C), pages 44-51.
    4. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2013. "A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 20/13, Monash University, Department of Econometrics and Business Statistics.
    5. Wang, Qin & Yao, Weixin, 2012. "An adaptive estimation of MAVE," Journal of Multivariate Analysis, Elsevier, vol. 104(1), pages 88-100, February.
    6. Yao, Weixin, 2013. "A note on EM algorithm for mixture models," Statistics & Probability Letters, Elsevier, vol. 83(2), pages 519-526.
    7. McCloud, Nadine & Parmeter, Christopher F., 2020. "Determining the Number of Effective Parameters in Kernel Density Estimation," Computational Statistics & Data Analysis, Elsevier, vol. 143(C).
    8. Xibin Zhang & Maxwell L. King & Han Lin Shang, 2011. "Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density," Monash Econometrics and Business Statistics Working Papers 10/11, Monash University, Department of Econometrics and Business Statistics.
    9. Chen, Yixin & Wang, Qin & Yao, Weixin, 2015. "Adaptive estimation for varying coefficient models," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 17-31.
    10. Chaouch, Mohamed, 2019. "Volatility estimation in a nonlinear heteroscedastic functional regression model with martingale difference errors," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 129-148.
    11. De Gooijer, Jan G. & Reichardt, Hugo, 2021. "A multi-step kernel–based regression estimator that adapts to error distributions of unknown form," LSE Research Online Documents on Economics 115083, London School of Economics and Political Science, LSE Library.

  112. Hidehiko Ichimura & Oliver Linton, 2001. "Asymptotic expansions for some semiparametric program evaluation estimators," CeMMAP working papers 04/01, Institute for Fiscal Studies.

    Cited by:

    1. Toru Kitagawa & Chris Muris, 2015. "Model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP46/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Annette Bergemann & Bernd Fitzenberger & Stefan Speckesser, 2009. "Evaluating the dynamic employment effects of training programs in East Germany using conditional difference-in-differences," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 797-823.
    3. Alberto Abadie & Guido W. Imbens, 2002. "Simple and Bias-Corrected Matching Estimators for Average Treatment Effects," NBER Technical Working Papers 0283, National Bureau of Economic Research, Inc.
    4. Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP69/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Jose C. Galdo & Jeffrey Smith & Dan Black, 2008. "Bandwidth Selection and the Estimation of Treatment Effects with Unbalanced Data," Annals of Economics and Statistics, GENES, issue 91-92, pages 189-216.
    6. Fitzenberger, Bernd & Speckesser, Stefan, 2005. "Employment effects of the provision of specific professional skills and techniques in Germany," IAB-Discussion Paper 200521, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    7. Biewen, Martin & Fitzenberger, Bernd & Osikominu, Aderonke & Waller, Marie, 2007. "Which Program for Whom? Evidence on the Comparative Effectiveness of Public Sponsored Training Programs in Germany," ZEW Discussion Papers 07-042, ZEW - Leibniz Centre for European Economic Research.
    8. Fitzenberger, Bernd & Osikominu, Aderonke & Völter, Robert, 2006. "Get training or wait? : long-run employment effects of training programs for the unemployed in West Germany," IAB-Discussion Paper 200617, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    9. Toru Kitagawa & Chris Muris, 2013. "Covariate selection and model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP61/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Millimet, Daniel L. & Tchernis, Rusty, 2009. "On the Specification of Propensity Scores, With Applications to the Analysis of Trade Policies," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(3), pages 397-415.
    11. Michael Lechner, 2004. "Sequential Matching Estimation of Dynamic Causal Models," University of St. Gallen Department of Economics working paper series 2004 2004-06, Department of Economics, University of St. Gallen.

  113. Linton, Oliver & Xiao, Zhijie, 2001. "Second-order approximation for adaptive regression estimators," LSE Research Online Documents on Economics 317, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Hidehiko Ichimura & Oliver Linton, 2003. "Asymptotic Expansions for Some Semiparametric Program Evaluation Estimators," STICERD - Econometrics Paper Series 451, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    2. Hafner, C. M., 2022. "Dynamic Autoregressive Liquidity (DArLiQ)," Cambridge Working Papers in Economics 2214, Faculty of Economics, University of Cambridge.
    3. Tamaki, Kenichiro, 2007. "Second order optimality for estimators in time series regression models," Journal of Multivariate Analysis, Elsevier, vol. 98(3), pages 638-659, March.
    4. Cattaneo, Matias D. & Crump, Richard K. & Jansson, Michael, 2012. "Optimal inference for instrumental variables regression with non-Gaussian errors," Journal of Econometrics, Elsevier, vol. 167(1), pages 1-15.
    5. Chen, Xiaohong, 2007. "Large Sample Sieve Estimation of Semi-Nonparametric Models," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 76, Elsevier.

  114. Oliver Linton & Mototsugu Shintani, 2001. "Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors," FMG Discussion Papers dp383, Financial Markets Group.

    Cited by:

    1. Tapas MISHRA & Mamata PARHI & Claude DIEBOLT, 2014. "Evolutionary efficiency and distributive effects of inertia in cross-country life-satisfaction," Economies et Sociétés (Serie 'Histoire Economique Quantitative'), Association Française de Cliométrie (AFC), issue 49, pages 1335-1356, Août.
    2. Park, Joon Y. & Whang, Yoon-Jae, 2012. "Random walk or chaos: A formal test on the Lyapunov exponent," Journal of Econometrics, Elsevier, vol. 169(1), pages 61-74.
    3. Cars Hommes & Sebastiano Manzan, 2006. "Testing for Nonlinear Structure and Chaos in Economic Time. A Comment," Tinbergen Institute Discussion Papers 06-030/1, Tinbergen Institute.
    4. Kyrtsou, Catherine & Serletis, Apostolos, 2006. "Univariate tests for nonlinear structure," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 154-168, March.
    5. Elena Olmedo & Ricardo Gimeno & Lorenzo Escot & Ruth Mateos, 2007. "Convergencia y Estabilidad de los Tipos de Cambio Europeos: Una Aplicación de Exponentes de Lyapunov," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 44(129), pages 91-108.
    6. Mototsugu Shintani, 2004. "A Dynamic Factor Approach to Nonlinear Stability Analysis," Vanderbilt University Department of Economics Working Papers 0418, Vanderbilt University Department of Economics.
    7. Orzeszko, Witold, 2008. "The new method of measuring the effects of noise reduction in chaotic data," Chaos, Solitons & Fractals, Elsevier, vol. 38(5), pages 1355-1368.
    8. Vitaliy Vandrovych, 2005. "Study of Nonlinearities in the Dynamics of Exchange Rates: Is There Any Evidence of Chaos?," Computing in Economics and Finance 2005 234, Society for Computational Economics.
    9. Oliver Linton & Mototsugu Shintani, 2002. "Nonparametric Neutral Network Estimation of Lyapunov Exponents and a Direct Test for Chaos," STICERD - Econometrics Paper Series 434, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    10. Serletis, Apostolos & Shahmoradi, Asghar, 2007. "Chaos, self-organized criticality, and SETAR nonlinearity: An analysis of purchasing power parity between Canada and the United States," Chaos, Solitons & Fractals, Elsevier, vol. 33(5), pages 1437-1444.
    11. Mototsugu Shintani, 2006. "A nonparametric measure of convergence towards purchasing power parity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 589-604.
    12. Orlando Gomes, 2004. "Heterogeneous Researchers in a Two-Sector Representative Consumer Economy," GE, Growth, Math methods 0409009, University Library of Munich, Germany.
    13. Vogl, Markus, 2022. "Controversy in financial chaos research and nonlinear dynamics: A short literature review," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    14. Mototsugu Shintani, 2006. "A nonparametric measure of convergence towards purchasing power parity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(5), pages 589-604, July.
    15. Serletis, Apostolos & Uritskaya, Olga Y., 2007. "Detecting signatures of stochastic self-organization in US money and velocity measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 281-291.
    16. Serletis, Apostolos & Shahmoradi, Asghar & Serletis, Demitre, 2007. "Effect of noise on estimation of Lyapunov exponents from a time series," Chaos, Solitons & Fractals, Elsevier, vol. 32(2), pages 883-887.
    17. Tapas Mishra & Mamata Parhi & Raúl Fuentes, 2015. "How Interdependent are Cross-Country Happiness Dynamics?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(2), pages 491-518, June.
    18. Musselwhite, Gary & Herath, Gamini, 2007. "Chaos theory and assessment of forest stakeholder attitudes towards Australian forest policy," Forest Policy and Economics, Elsevier, vol. 9(8), pages 947-964, May.
    19. Kyrtsou, Catherine & Malliaris, Anastasios G. & Serletis, Apostolos, 2009. "Energy sector pricing: On the role of neglected nonlinearity," Energy Economics, Elsevier, vol. 31(3), pages 492-502, May.
    20. Saeed Moshiri & Faezeh Foroutan, 2006. "Forecasting Nonlinear Crude Oil Futures Prices," The Energy Journal, , vol. 27(4), pages 81-96, October.
    21. Serletis, Apostolos & He, Mingyu & Chowdhury, M.M. Islam, 2023. "Chaos in long-maturity real rates," Economics Letters, Elsevier, vol. 225(C).
    22. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Testing Chaotic Dynamics via Lyapunov Exponents," Working Papers 2000-07, FEDEA.
    23. Sandubete, Julio E. & Escot, Lorenzo, 2020. "Chaotic signals inside some tick-by-tick financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    24. Serletis, Apostolos & Shintani, Mototsugu, 2006. "Chaotic monetary dynamics with confidence," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 228-252, March.
    25. Hommes, C.H. & Manzan, S., 2005. "Testing for Nonlinear Structure and Chaos in Economic Time Series: A Comment," CeNDEF Working Papers 05-14, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    26. Escot, Lorenzo & Sandubete, Julio E., 2023. "Estimating Lyapunov exponents on a noisy environment by global and local Jacobian indirect algorithms," Applied Mathematics and Computation, Elsevier, vol. 436(C).
    27. Pogany, Peter, 2010. "What’s wrong with the world? Rationality! A critique of economic anthropology in the spirit of Jean Gebser," MPRA Paper 26458, University Library of Munich, Germany.

  115. Xiaohong Chen & Oliver Linton & Peter M Robinson, 2001. "The Estimation of Conditional Densities," STICERD - Econometrics Paper Series 415, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Kotlyarova, Yulia & Schafgans, Marcia M.A. & Zinde-Walsh, Victoria, 2021. "Rates of expansions for functional estimators," LSE Research Online Documents on Economics 113436, London School of Economics and Political Science, LSE Library.
    2. Yulia Kotlyarova & Marcia M. A. Schafgans & Victoria Zinde-Walsh, 2022. "Correction to: Rates of Expansions for Functional Estimators," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(2), pages 487-487, June.
    3. Esteban-Bravo, Mercedes & Vidal-Sanz, Jose M. & Yildirim, Gökhan, 2012. "Valuing customer portfolios with endogenous mass-and-direct-marketing interventions using a stochastic dynamic programming decomposition," DEE - Working Papers. Business Economics. WB wb121304, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    4. Corradi, Valentina & Distaso, Walter & Fernandes, Marcelo, 2012. "International market links and volatility transmission," Journal of Econometrics, Elsevier, vol. 170(1), pages 117-141.
    5. Tindara Addabbo & Donata Favaro & Stefano Magrini, 2010. "Gender differences in productivity rewards in Italy: the role of human capital," Working Papers 2010_11, Department of Economics, University of Venice "Ca' Foscari".
    6. Otneim, Håkon & Tjøstheim, Dag, 2016. "Non-parametric estimation of conditional densities: A new method," Discussion Papers 2016/22, Norwegian School of Economics, Department of Business and Management Science.
    7. Jan G. de Gooijer & Dawit Zerom, 2002. "On Conditional Density Estimation," Tinbergen Institute Discussion Papers 02-032/4, Tinbergen Institute.
    8. Buch-Kromann, Tine & Guillén, Montserrat & Linton, Oliver & Nielsen, Jens Perch, 2011. "Multivariate density estimation using dimension reducing information and tail flattening transformations," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 99-110, January.
    9. Kateřina Konečná & Ivanka Horová, 2019. "Maximum likelihood method for bandwidth selection in kernel conditional density estimate," Computational Statistics, Springer, vol. 34(4), pages 1871-1887, December.
    10. Tindara Addabbo & Donata Favaro & Stefano Magrini, 2012. "Gender differences in productivity rewards: the role of human capital," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 59(1), pages 81-110, March.
    11. Donata Favaro & Stefano Magrini, 2005. "Group versus individual discrimination among young workers: a distributional approach," Labor and Demography 0506003, University Library of Munich, Germany.
    12. Alejandro Quintela-Del-Río, 2008. "Hazard function given a functional variable: Non-parametric estimation under strong mixing conditions," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(5), pages 413-430.
    13. Amaro de Matos, Joao & Fernandes, Marcelo, 2007. "Testing the Markov property with high frequency data," Journal of Econometrics, Elsevier, vol. 141(1), pages 44-64, November.

  116. Oliver Linton & Jens Perch Nielsen & Sara van de Geer, 2001. "Estimating Multiplicative and Additive Hazard Functions by Kernel Methods," STICERD - Econometrics Paper Series 411, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Toshio Honda, 2005. "Estimation in additive cox models by marginal integration," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(3), pages 403-423, September.

  117. Jeffrey, Andrew & Linton, Oliver & Nguyen, Thong, 2001. "Flexible term structure estimation: which method is preferred?," LSE Research Online Documents on Economics 2192, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. David Bolder & Scott Gusba, 2002. "Exponentials, Polynomials, and Fourier Series: More Yield Curve Modelling at the Bank of Canada," Staff Working Papers 02-29, Bank of Canada.
    2. Clive G. Bowsher & Roland Meeks, 2008. "The dynamics of economics functions: modelling and forecasting the yield curve," Working Papers 0804, Federal Reserve Bank of Dallas.
    3. Yan Liu & Jing Cynthia Wu, 2020. "Reconstructing the Yield Curve," NBER Working Papers 27266, National Bureau of Economic Research, Inc.
    4. Luís Oliveira & João Vidal Nunes & Luís Malcato, 2014. "The performance of deterministic and stochastic interest rate risk measures:," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 13(3), pages 141-165, December.
    5. Tatyana Krivobokova & Göran Kauermann & Theofanis Archontakis, 2006. "Estimating the term structure of interest rates using penalized splines," Statistical Papers, Springer, vol. 47(3), pages 443-459, June.
    6. Antonio Diaz & Francisco Jareno & Eliseo Navarro, 2010. "Term structure of volatilities and yield curve estimation methodology," Quantitative Finance, Taylor & Francis Journals, vol. 11(4), pages 573-586.
    7. Tong, Xiaojun & He, Zhuoqiong Chong & Sun, Dongchu, 2018. "Estimating Chinese Treasury yield curves with Bayesian smoothing splines," Econometrics and Statistics, Elsevier, vol. 8(C), pages 94-124.
    8. Oliveira, Luís & Curto, José Dias & Nunes, João Pedro, 2012. "The determinants of sovereign credit spread changes in the Euro-zone," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(2), pages 278-304.
    9. Michiel De Pooter, 2007. "Examining the Nelson-Siegel Class of Term Structure Models," Tinbergen Institute Discussion Papers 07-043/4, Tinbergen Institute.

  118. Oliver Linton & Yoon-Jae Whang, 2000. "Nonparametric Estimation with Aggregated Data," STICERD - Econometrics Paper Series 397, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Delaigle, Aurore & Meister, Alexander, 2007. "Nonparametric Regression Estimation in the Heteroscedastic Errors-in-Variables Problem," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1416-1426, December.
    2. Carroll, Raymond J. & Delaigle, Aurore & Hall, Peter, 2009. "Nonparametric Prediction in Measurement Error Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 993-1003.
    3. Felt, Marie-Hélène, 2020. "On the identification of joint distributions using marginals and aggregates," Economics Letters, Elsevier, vol. 194(C).
    4. Raymond J. Carroll & Aurore Delaigle & Peter Hall, 2007. "Non‐parametric regression estimation from data contaminated by a mixture of Berkson and classical errors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 859-878, November.
    5. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers 37/13, Institute for Fiscal Studies.
    6. Phuong, Cao Xuan & Thuy, Le Thi Hong, 2019. "Density deconvolution from grouped data with additive errors," Statistics & Probability Letters, Elsevier, vol. 148(C), pages 74-81.
    7. Marie-Hélène Felt, 2018. "A Look Inside the Box: Combining Aggregate and Marginal Distributions to Identify Joint Distributions," Staff Working Papers 18-29, Bank of Canada.
    8. Joel L. Horowitz, 2013. "Ill-posed inverse problems in economics," CeMMAP working papers CWP37/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Meister, Alexander, 2007. "Optimal convergence rates for density estimation from grouped data," Statistics & Probability Letters, Elsevier, vol. 77(11), pages 1091-1097, June.
    10. Li, Tong & Hsiao, Cheng, 2004. "Robust estimation of generalized linear models with measurement errors," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 51-65.
    11. Xiaohong Chen & Yingyao Hu, 2006. "Identification and Inference of Nonlinear Models Using Two Samples with Arbitrary Measurement Errors," Cowles Foundation Discussion Papers 1590, Cowles Foundation for Research in Economics, Yale University.

  119. Linton, Oliver & Perron, Benoit, 2000. "The shape of the risk premium: evidence from a semiparametric GARCH model," LSE Research Online Documents on Economics 24769, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Christensen, Bent Jesper & Dahl, Christian M. & Iglesias, Emma M., 2012. "Semiparametric inference in a GARCH-in-mean model," Journal of Econometrics, Elsevier, vol. 167(2), pages 458-472.
    2. Ghosh, Anisha & Linton, Oliver, 2009. "Consistent estimation of the risk-return tradeoff in the presence of measurement error," UC3M Working papers. Economics we094928, Universidad Carlos III de Madrid. Departamento de Economía.

  120. Linton, Oliver, 2000. "Efficient estimation of generalized additive nonparametric regression models," LSE Research Online Documents on Economics 314, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Gayle, Wayne-Roy, 2013. "Identification and N-consistent estimation of a nonlinear panel data model with correlated unobserved effects," Journal of Econometrics, Elsevier, vol. 175(2), pages 71-83.
    2. Oliver B. Linton & Enno Mammen & J. Nielsen & Carsten Tanggaard, 2000. "Yield Curve Estimation by Kernel Smoothing Methods," Econometric Society World Congress 2000 Contributed Papers 0235, Econometric Society.
    3. Kalnina, Ilze & Linton, Oliver, 2007. "Inference about realized volatility using infill subsampling," LSE Research Online Documents on Economics 4411, London School of Economics and Political Science, LSE Library.
    4. David Jacho-Chavez & Arthur Lewbel & Oliver Linton, 2006. "Identification and Nonparametric Estimation of a Transformed Additively Separable Model," Boston College Working Papers in Economics 652, Boston College Department of Economics, revised 26 Nov 2008.
    5. Dong, C. & Li, S., 2021. "Specification Lasso and an Application in Financial Markets," Cambridge Working Papers in Economics 2139, Faculty of Economics, University of Cambridge.
    6. Degui Li & Oliver Linton & Zudi Lu, 2012. "A flexible semiparametric model for time series," CeMMAP working papers CWP28/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Toshio Honda, 2005. "Estimation in additive cox models by marginal integration," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(3), pages 403-423, September.
    8. Ozabaci, Deniz & Henderson, Daniel J., 2014. "Additive Kernel Estimates of Returns to Schooling," IZA Discussion Papers 8736, Institute of Labor Economics (IZA).
    9. Ying Wang & Peter C. B. Phillips & Yundong Tu, 2024. "Limit Theory and Inference in Non-cointegrated Functional Coefficient Regression," Cowles Foundation Discussion Papers 2399, Cowles Foundation for Research in Economics, Yale University.
    10. Gozalo, Pedro L. & Linton, Oliver B., 2001. "Testing additivity in generalized nonparametric regression models with estimated parameters," Journal of Econometrics, Elsevier, vol. 104(1), pages 1-48, August.
    11. Arthur Lewbel & Krishna Pendakur, 2012. "Unobserved Preference Heterogeneity in Demand Using Generalized Random Coefficients," Boston College Working Papers in Economics 791, Boston College Department of Economics, revised 01 Jul 2013.
    12. Kim, Woocheol & Linton, Oliver, 2004. "A local instrumental variable estimation method for generalized additive volatility models," LSE Research Online Documents on Economics 24758, London School of Economics and Political Science, LSE Library.
    13. Barry K. Goodwin & Matthew T. Holt & Jeffrey P. Prestemon, 2021. "Semi-parametric models of spatial market integration," Empirical Economics, Springer, vol. 61(5), pages 2335-2361, November.
    14. Oliver Linton & E. Mammen & J. Nielsen & C. Tanggaard, 1998. "Estimating Yield Curves by Kernel Smoothing Methods," Cowles Foundation Discussion Papers 1205, Cowles Foundation for Research in Economics, Yale University.
    15. O. Linton & E. Mammen, 2005. "Estimating Semiparametric ARCH(∞) Models by Kernel Smoothing Methods," Econometrica, Econometric Society, vol. 73(3), pages 771-836, May.
    16. Moral, Ignacio & Rodriguez-Poo, Juan M., 2004. "An efficient marginal integration estimator of a semiparametric additive modelling," Statistics & Probability Letters, Elsevier, vol. 69(4), pages 451-463, October.
    17. Gao, Jiti & King, Maxwell, 2003. "Estimation and model specification testing in nonparametric and semiparametric econometric models," MPRA Paper 11989, University Library of Munich, Germany, revised Feb 2006.
    18. Théophile T. Azomahou & Bity Diene & Mbaye Diene, 2009. "Technology frontier, labor productivity and economic growth: Evidence from OECD countries," DEM Discussion Paper Series 09-19, Department of Economics at the University of Luxembourg.
    19. Azomahou, Théophile T. & Diene, Bity & Diene, Mbaye, 2013. "Nonlinearities in productivity growth: A semi-parametric panel analysis," Structural Change and Economic Dynamics, Elsevier, vol. 24(C), pages 45-75.
    20. Lin, Huazhen & Pan, Lixian & Lv, Shaogao & Zhang, Wenyang, 2018. "Efficient estimation and computation for the generalised additive models with unknown link function," Journal of Econometrics, Elsevier, vol. 202(2), pages 230-244.
    21. Su, Liangjun & Ullah, Aman, 2008. "Local polynomial estimation of nonparametric simultaneous equations models," Journal of Econometrics, Elsevier, vol. 144(1), pages 193-218, May.
    22. Oliver Linton & Enno Mammen, 2003. "Estimating Semiparametric ARCH (8) Models by Kernel Smoothing Methods," STICERD - Econometrics Paper Series 453, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    23. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.
    24. Cai, Zongwu & Li, Qi & Park, Joon Y., 2009. "Functional-coefficient models for nonstationary time series data," Journal of Econometrics, Elsevier, vol. 148(2), pages 101-113, February.
    25. Manzan, sebastiano & Zerom, Dawit, 2008. "A Semiparametric Analysis of Gasoline Demand in the US: Reexamining The Impact of Price," MPRA Paper 14386, University Library of Munich, Germany.
    26. Azomahou, Theophile & Diene, Bity & Diene, Mbaye, 2009. "Technology frontier, labor productivity and economic growth: Evidence from OECD countries," MERIT Working Papers 2009-059, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    27. Koo, Bonsoo & Linton, Oliver, 2012. "Estimation of semiparametric locally stationary diffusion models," Journal of Econometrics, Elsevier, vol. 170(1), pages 210-233.
    28. Ben-Moshe, Dan & D’Haultfœuille, Xavier & Lewbel, Arthur, 2017. "Identification of additive and polynomial models of mismeasured regressors without instruments," Journal of Econometrics, Elsevier, vol. 200(2), pages 207-222.
    29. Li, Qi & Hsiao, Cheng & Zinn, Joel, 2003. "Consistent specification tests for semiparametric/nonparametric models based on series estimation methods," Journal of Econometrics, Elsevier, vol. 112(2), pages 295-325, February.
    30. Tu, Yundong & Wang, Ying, 2022. "Spurious functional-coefficient regression models and robust inference with marginal integration," Journal of Econometrics, Elsevier, vol. 229(2), pages 396-421.
    31. Azomahou, Theophile & Diene, Bity & Diene, Mbaye, 2012. "Nonlinearities in productivity growth: A semi-parametric panel analysis," MERIT Working Papers 2012-046, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    32. Barry K. Goodwin, 2025. "Integration of the US cannabis market," American Journal of Agricultural Economics, John Wiley & Sons, vol. 107(2), pages 440-464, March.
    33. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    34. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    35. Barry K. Goodwin, 2014. "Comment on "The Evolving Relationships between Agricultural and Energy Commodity Prices: A Shifting-Mean Vector Autoregressive Analysis"," NBER Chapters, in: The Economics of Food Price Volatility, pages 187-192, National Bureau of Economic Research, Inc.

  121. Oliver Linton & Enno Mammen & N Nielsen, 2000. "The Existence and Asymptotic Properties of a Backfitting Projection Algorithm under Weak Conditions," STICERD - Econometrics Paper Series 386, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Oliver B. Linton & Enno Mammen & J. Nielsen & Carsten Tanggaard, 2000. "Yield Curve Estimation by Kernel Smoothing Methods," Econometric Society World Congress 2000 Contributed Papers 0235, Econometric Society.
    2. Lee, Kyeongeun & Lee, Young K. & Park, Byeong U. & Yang, Seong J., 2018. "Time-dynamic varying coefficient models for longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 123(C), pages 50-65.
    3. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers CWP20/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Song, Qiongxia & Yang, Lijian, 2010. "Oracally efficient spline smoothing of nonlinear additive autoregression models with simultaneous confidence band," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2008-2025, October.
    5. Yang, Lijian & Park, Byeong U. & Xue, Lan & Hardle, Wolfgang, 2006. "Estimation and Testing for Varying Coefficients in Additive Models With Marginal Integration," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1212-1227, September.
    6. Michael Vogt, 2012. "Nonparametric regression for locally stationary time series," CeMMAP working papers CWP22/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Gagliardini, Patrick & Scaillet, Olivier, 2012. "Tikhonov regularization for nonparametric instrumental variable estimators," Journal of Econometrics, Elsevier, vol. 167(1), pages 61-75.
    8. Patrick Saart & Jiti Gao & Nam Hyun Kim, 2014. "Semiparametric methods in nonlinear time series analysis: a selective review," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 141-169, March.
    9. Chaohua Dong & Oliver Linton, 2017. "Additive nonparametric models with time variable and both stationary and nonstationary regressions," CeMMAP working papers 59/17, Institute for Fiscal Studies.
    10. Gao, Jiti & Lu, Zudi & Tjostheim, Dag, 2003. "Estimation in semiparametric spatial regression," MPRA Paper 11979, University Library of Munich, Germany, revised Jul 2005.
    11. Raouf, BOUCEKKINE & Bity, DIENE & Théophile, AZOMAHOU, 2007. "A closer look at the relationship between life expectancy and economic growth," Discussion Papers (ECON - Département des Sciences Economiques) 2007043, Université catholique de Louvain, Département des Sciences Economiques.
    12. Hao Dong & Taisuke Otsu, 2018. "Nonparametric Estimation of Additive Model With Errors-in-Variables," Departmental Working Papers 1812, Southern Methodist University, Department of Economics.
    13. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.
    14. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
    15. Rüdiger Krause & Gerhard Tutz, 2006. "Genetic algorithms for the selection of smoothing parameters in additive models," Computational Statistics, Springer, vol. 21(1), pages 9-31, March.
    16. Suneel Babu Chatla, 2023. "Nonparametric inference for additive models estimated via simplified smooth backfitting," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(1), pages 71-97, February.
    17. Degui Li & Oliver Linton & Zudi Lu, 2012. "A flexible semiparametric model for time series," CeMMAP working papers CWP28/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    18. Lin, Lu & Song, Yunquan & Liu, Zhao, 2014. "Local linear–additive estimation for multiple nonparametric regressions," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 252-269.
    19. Gayle, Wayne-Roy & Namoro, Soiliou Daw, 2013. "Estimation of a nonlinear panel data model with semiparametric individual effects," Journal of Econometrics, Elsevier, vol. 175(1), pages 46-59.
    20. Ozabaci, Deniz & Henderson, Daniel J., 2014. "Additive Kernel Estimates of Returns to Schooling," IZA Discussion Papers 8736, Institute of Labor Economics (IZA).
    21. Huang, Zhensheng & Zhang, Riquan, 2009. "Efficient estimation of adaptive varying-coefficient partially linear regression model," Statistics & Probability Letters, Elsevier, vol. 79(7), pages 943-952, April.
    22. Guo, Zheng-Feng & Shintani, Mototsugu, 2011. "Nonparametric lag selection for nonlinear additive autoregressive models," Economics Letters, Elsevier, vol. 111(2), pages 131-134, May.
    23. Lena Boneva (Körber) & Oliver Linton & Michael Vogt, 2013. "A semiparametric model for heterogeneous panel data with fixed effects," CeMMAP working papers CWP02/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    24. Kim, Woocheol & Linton, Oliver, 2004. "A local instrumental variable estimation method for generalized additive volatility models," LSE Research Online Documents on Economics 24758, London School of Economics and Political Science, LSE Library.
    25. Florens, Jean-Pierre & Fève, Frédérique & Simar, Léopold, 2025. "Reconciling Engineers and Economists: the Case of a Cost Function for the Distribution of Gas," TSE Working Papers 25-1640, Toulouse School of Economics (TSE).
    26. Stefan Sperlich & Oliver Linton & Wolfgang Härdle, 1999. "Integration and backfitting methods in additive models-finite sample properties and comparison," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 8(2), pages 419-458, December.
    27. Profit, Stefan & Sperlich, Stefan, 1999. "Non-uniformity of job-matching in a transition economy- a nonparametric analysis for the czech republic," DES - Working Papers. Statistics and Econometrics. WS 6287, Universidad Carlos III de Madrid. Departamento de Estadística.
    28. Oliver Linton & E. Mammen & J. Nielsen & C. Tanggaard, 1998. "Estimating Yield Curves by Kernel Smoothing Methods," Cowles Foundation Discussion Papers 1205, Cowles Foundation for Research in Economics, Yale University.
    29. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    30. Müller, Ursula U. & Schick, Anton & Wefelmeyer, Wolfgang, 2014. "Testing for additivity in partially linear regression with possibly missing responses," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 51-61.
    31. Woocheol Kim, 2004. "Identification And Estimation Of Nonparametric Structural," Econometric Society 2004 Far Eastern Meetings 733, Econometric Society.
    32. Sperlich, Stefan & Tjøstheim, Dag & Yang, Lijian, 2002. "Nonparametric Estimation And Testing Of Interaction In Additive Models," Econometric Theory, Cambridge University Press, vol. 18(2), pages 197-251, April.
    33. Zhengyan Lin & Degui Li & Jiti Gao, 2009. "Local Linear M‐estimation in non‐parametric spatial regression," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 286-314, May.
    34. O. Linton & E. Mammen, 2005. "Estimating Semiparametric ARCH(∞) Models by Kernel Smoothing Methods," Econometrica, Econometric Society, vol. 73(3), pages 771-836, May.
    35. Vanhems, Anne & Van Keilegom, Ingrid, 2011. "Semiparametric transformation model with endogeneity: a control function approach," LIDAM Discussion Papers ISBA 2011011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    36. Jing Wang & Lijian Yang, 2009. "Efficient and fast spline-backfitted kernel smoothing of additive models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(3), pages 663-690, September.
    37. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    38. Martins-Filho, Carlos & yang, ke, 2007. "Finite sample performance of kernel-based regression methods for non-parametric additive models under common bandwidth selection criterion," MPRA Paper 39295, University Library of Munich, Germany.
    39. Schimek, Michael G. & Turlach, Berwin A., 1998. "Additive and generalized additive models: A survey," SFB 373 Discussion Papers 1998,97, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    40. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers 20/12, Institute for Fiscal Studies.
    41. Xia Cui & Heng Peng & Songqiao Wen & Lixing Zhu, 2013. "Component Selection in the Additive Regression Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(3), pages 491-510, September.
    42. Carroll, Raymond J. & Härdle, Wolfgang & Mammen, Enno, 1999. "Estimation in an additive model when the components are linked parametrically," SFB 373 Discussion Papers 1999,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    43. Van Keilegom, Ingrid & Vanhems, Anne, 2016. "Estimation of a semiparametric transformation model in the presence of endogeneity," TSE Working Papers 16-654, Toulouse School of Economics (TSE).
    44. Yang, Lijian & Sperlich, Stefan & Hardle, Wolfgang, 2000. "Derivative estimation and testing in generalized additive models," DES - Working Papers. Statistics and Econometrics. WS 10084, Universidad Carlos III de Madrid. Departamento de Estadística.
    45. Henderson, Daniel J. & Carroll, Raymond J. & Li, Qi, 2008. "Nonparametric estimation and testing of fixed effects panel data models," Journal of Econometrics, Elsevier, vol. 144(1), pages 257-275, May.
    46. Lin, Huazhen & Pan, Lixian & Lv, Shaogao & Zhang, Wenyang, 2018. "Efficient estimation and computation for the generalised additive models with unknown link function," Journal of Econometrics, Elsevier, vol. 202(2), pages 230-244.
    47. Qian Huang & Jinhong You & Liwen Zhang, 2022. "Efficient inference of longitudinal/functional data models with time‐varying additive structure," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 744-771, June.
    48. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 2001. "Bootstrap Inference in Semiparametric Generalized Additive Models," Finance Working Papers 01-3, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    49. Gutknecht, Daniel, "undated". "Do Reservation Wages Decline Monotonically? A Novel Statistical Test," Economic Research Papers 270635, University of Warwick - Department of Economics.
    50. Lu, Zudi & Lundervold, Arvid & Tjøstheim, Dag & Yao, Qiwei, 2007. "Exploring spatial nonlinearity using additive approximation," LSE Research Online Documents on Economics 5401, London School of Economics and Political Science, LSE Library.
    51. Juhyun Park & Burkhardt Seifert, 2010. "Local additive estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(2), pages 171-191, March.
    52. Horowitz, Joel L. & Mammen, Enno, 2002. "Nonparametric estimation of an additive model with a link function," SFB 373 Discussion Papers 2002,63, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    53. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.
    54. Horowitz, Joel L., 2004. "Semiparametric models," Papers 2004,17, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    55. Wang, Li & Wang, Suojin, 2011. "Nonparametric additive model-assisted estimation for survey data," Journal of Multivariate Analysis, Elsevier, vol. 102(7), pages 1126-1140, August.
    56. Fengler, M.R. & Mammen, E. & Vogt, M., 2015. "Specification and structural break tests for additive models with applications to realized variance data," Journal of Econometrics, Elsevier, vol. 188(1), pages 196-218.
    57. Vanhems, Anne & Van Keilegom, Ingrid, 2013. "Semiparametric transformation model with endogeneity: a control function approach," LIDAM Discussion Papers ISBA 2013018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    58. Linton, Oliver B. & Mammen, Enno, 2008. "Nonparametric transformation to white noise," Journal of Econometrics, Elsevier, vol. 142(1), pages 241-264, January.
    59. Peroni, Chiara, 2007. "A non-parametric investigation of risk premia," MPRA Paper 5126, University Library of Munich, Germany, revised 01 Dec 2007.
    60. Wolfgang Haerdle & Oliver Linton & Qihua Wang, 2003. "Semiparametric Regression Analysis under Imputation for Missing Response Data," STICERD - Econometrics Paper Series 454, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    61. Suphi Sen & Bertrand Melenberg & Herman R. J. Vollebergh, 2016. "Identification and Estimation of the Environmental Kuznets Curve: Pairwise Differencing to Deal with Nonlinearity and Nonstationarity," CESifo Working Paper Series 5837, CESifo.
    62. Green, Carl & Long, Wei & Hsiao, Cheng, 2015. "Testing error serial correlation in fixed effects nonparametric panel data models," Journal of Econometrics, Elsevier, vol. 188(2), pages 466-473.
    63. Berthold R. Haag, 2008. "Non‐parametric Regression Tests Using Dimension Reduction Techniques," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(4), pages 719-738, December.
    64. Grasshoff, Ulrike & Schwalbach, Joachim & Sperlich, Stefan, 1999. "Executive pay and corporate financial performance. An exploratiove data analysis," DES - Working Papers. Statistics and Econometrics. WS 6382, Universidad Carlos III de Madrid. Departamento de Estadística.
    65. Li, Qi & Hsiao, Cheng & Zinn, Joel, 2003. "Consistent specification tests for semiparametric/nonparametric models based on series estimation methods," Journal of Econometrics, Elsevier, vol. 112(2), pages 295-325, February.
    66. Rui Li & Yuanyuan Zhang, 2021. "Two-stage estimation and simultaneous confidence band in partially nonlinear additive model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(8), pages 1109-1140, November.
    67. Grith, Maria & Härdle, Wolfgang Karl & Schienle, Melanie, 2010. "Nonparametric estimation of risk-neutral densities," SFB 649 Discussion Papers 2010-021, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    68. Tu, Yundong & Wang, Ying, 2022. "Spurious functional-coefficient regression models and robust inference with marginal integration," Journal of Econometrics, Elsevier, vol. 229(2), pages 396-421.
    69. Häggström, Jenny, 2013. "Bandwidth selection for backfitting estimation of semiparametric additive models: A simulation study," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 136-148.
    70. Holger Dette & Matthias Guhlich & Natalie Neumeyer, 2015. "Testing for additivity in nonparametric quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(3), pages 437-477, June.
    71. Van Keilegom, Ingrid & Vanhems, Anne, 2011. "Semiparametric transformation model with endogeneity: a control function approach," TSE Working Papers 11-243, Toulouse School of Economics (TSE).
    72. Joel L. Horowitz & Enno Mammen, 2002. "Nonparametric estimation of an additive model with a link function," CeMMAP working papers 19/02, Institute for Fiscal Studies.
    73. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2012. "Generated covariates in nonparametric estimation: A short review," SFB 649 Discussion Papers 2012-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    74. Linton, Oliver & Sancetta, Alessio, 2009. "Consistent estimation of a general nonparametric regression function in time series," Journal of Econometrics, Elsevier, vol. 152(1), pages 70-78, September.
    75. Abhijit Mandal, 2020. "An optimal test for the additive model with discrete or categorical predictors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(6), pages 1397-1417, December.
    76. Dette, Holger & von Lieres und Wilkau, Carsten, 2000. "Testing additivity by kernel based methods - what is a reasonable test?," Technical Reports 2000,39, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    77. Fengler, Matthias R. & Mammen, Enno & Vogt, Michael, 2013. "Additive modeling of realized variance: tests for parametric specifications and structural breaks," Economics Working Paper Series 1332, University of St. Gallen, School of Economics and Political Science.
    78. Stefan Sperlich & Raoul Theler, 2015. "Modeling heterogeneity: a praise for varying-coefficient models in causal analysis," Computational Statistics, Springer, vol. 30(3), pages 693-718, September.
    79. Mammen, Enno & Park, Byeong U. & Schienle, Melanie, 2012. "Additive models: Extensions and related models," SFB 649 Discussion Papers 2012-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    80. Joel L. Horowitz & Enno Mammen, 2002. "Nonparametric estimation of an additive model with a link function," CeMMAP working papers CWP19/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    81. Li, Cong & Liang, Zhongwen, 2015. "Asymptotics for nonparametric and semiparametric fixed effects panel models," Journal of Econometrics, Elsevier, vol. 185(2), pages 420-434.
    82. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    83. Rodriguez Poo, Juan M. & Sperlich, Stefan & Vieu, Philippe, 2000. "Semiparametric estimation of weak and strong separable models," DES - Working Papers. Statistics and Econometrics. WS 10064, Universidad Carlos III de Madrid. Departamento de Estadística.
    84. Hengartner, Nicolas W. & Sperlich, Stefan, 2005. "Rate optimal estimation with the integration method in the presence of many covariates," Journal of Multivariate Analysis, Elsevier, vol. 95(2), pages 246-272, August.
    85. Mammen, Enno & Martínez Miranda, María Dolores & Nielsen, Jens Perch, 2015. "In-sample forecasting applied to reserving and mesothelioma mortality," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 76-86.
    86. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2010. "Nonparametric regression with nonparametrically generated covariates," SFB 649 Discussion Papers 2010-059, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    87. Byeong U. Park & Enno Mammen & Young K. Lee & Eun Ryung Lee, 2015. "Varying Coefficient Regression Models: A Review and New Developments," International Statistical Review, International Statistical Institute, vol. 83(1), pages 36-64, April.
    88. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.
    89. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    90. Fernández, Ana I. & Rodríguez-Póo, Juan M. & Sperlich, Stefan, 1998. "Semiparametric three step estimation methods in labor supply models," SFB 373 Discussion Papers 1998,71, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    91. Mammen, Enno & Martínez-Miranda, María Dolores & Nielsen, Jens Perch & Vogt, Michael, 2021. "Calendar effect and in-sample forecasting," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 31-52.
    92. Han, Kyunghee & Lee, Young K. & Park, Byeong U., 2020. "Smooth backfitting for errors-in-variables varying coefficient regression models," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
    93. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.
    94. Andrew Jeffrey, 2004. "Nonparametric Estimation of a Multifactor Heath-Jarrow-Morton Model: An Integrated Approach," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 251-289.
    95. Hu, Lixia & Huang, Tao & You, Jinhong, 2019. "Two-step estimation of time-varying additive model for locally stationary time series," Computational Statistics & Data Analysis, Elsevier, vol. 130(C), pages 94-110.

  122. Arthur Lewbel & Oliver Linton, 2000. "Nonparametric Censored and Truncated Regression," Boston College Working Papers in Economics 439, Boston College Department of Economics.

    Cited by:

    1. Chen, Xiaohong & Linton, Oliver & Van Keilegom, Ingrid, 2003. "Estimation of semiparametric models when the criterion function is not smooth," LSE Research Online Documents on Economics 2167, London School of Economics and Political Science, LSE Library.
    2. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    3. Lu, Xuewen & Burke, M.D., 2005. "Censored multiple regression by the method of average derivatives," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 182-205, July.
    4. Dubois, Pierre & de Mouzon, Olivier & Scott Morton, Fiona & Seabright, Paul, 2011. "Market Size and Pharmaceutical Innovation," IDEI Working Papers 670, Institut d'Économie Industrielle (IDEI), Toulouse, revised Mar 2014.
    5. Chrysovalantis Gaganis & Fotios Pasiouras & Menelaos Tasiou & Constantin Zopounidis, 2021. "CISEF: A composite index of social, environmental and financial performance," Post-Print hal-03113006, HAL.
    6. Joseph G. Altonji & Hidehiko Ichimura & Taisuke Otsu, 2008. "Estimating Derivatives in Nonseparable Models with Limited Dependent Variables," Cowles Foundation Discussion Papers 1668R, Cowles Foundation for Research in Economics, Yale University, revised May 2011.
    7. Susanne M. Schennach, 2015. "A bias bound approach to nonparametric inference," CeMMAP working papers 71/15, Institute for Fiscal Studies.
    8. Anil Kumar, 2012. "Nonparametric estimation of the impact of taxes on female labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(3), pages 415-439, April.
    9. Dahl, Christian M. & Effraimidis, Georgios & Pedersen, Mikkel H., 2019. "Nonparametric wind power forecasting under fixed and random censoring," Energy Economics, Elsevier, vol. 84(C).
    10. Chen, Songnian & Khan, Shakeeb, 2003. "Rates of convergence for estimating regression coefficients in heteroskedastic discrete response models," Journal of Econometrics, Elsevier, vol. 117(2), pages 245-278, December.
    11. Luke Taylor & Taisuke Otsu, 2019. "Estimation of nonseparable models with censored dependent variables and endogenous regressors," Econometric Reviews, Taylor & Francis Journals, vol. 38(1), pages 4-24, January.
    12. Lu, Xuewen, 2010. "Asymptotic distributions of two "synthetic data" estimators for censored single-index models," Journal of Multivariate Analysis, Elsevier, vol. 101(4), pages 999-1015, April.
    13. Karlsson, Maria & Cantoni, Eva & de Luna, Xavier, 2009. "Local polynomial regression with truncated or censored response," Working Paper Series 2009:25, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    14. Park, Byeong U. & Simar, Léopold & Zelenyuk, Valentin, 2008. "Local likelihood estimation of truncated regression and its partial derivatives: Theory and application," Journal of Econometrics, Elsevier, vol. 146(1), pages 185-198, September.
    15. Marcela Munizaga & Sergio Jara-Díaz & Paulina Greeven & Chandra Bhat, 2008. "Econometric Calibration of the Joint Time Assignment--Mode Choice Model," Transportation Science, INFORMS, vol. 42(2), pages 208-219, May.
    16. Oberhofer, Walter & Haupt, Harry, 2005. "Consistency of nonlinear regression quantiles under Type I censoring weak dependence and general covariate design," University of Regensburg Working Papers in Business, Economics and Management Information Systems 406, University of Regensburg, Department of Economics.
    17. Cao, Ricardo & Gonzalez-Manteiga, Wenceslao, 2008. "Goodness-of-fit tests for conditional models under censoring and truncation," Journal of Econometrics, Elsevier, vol. 143(1), pages 166-190, March.
    18. Feve, Frederique & Florens, Jean-Pierre & Van Keilegom, Ingrid, 2012. "Estimation of conditional ranks and tests of exogeneity in nonparametric nonseparable models," LIDAM Discussion Papers ISBA 2012036, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    19. Florens, Jean-Pierre & Simar, Leopold & Van Keilegom, Ingrid, 2013. "Frontier estimation in nonparametric location-scale models," LIDAM Reprints ISBA 2013035, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    20. Čížek, Pavel, 2012. "Semiparametric robust estimation of truncated and censored regression models," Journal of Econometrics, Elsevier, vol. 168(2), pages 347-366.
    21. Moral-Arce, Ignacio & Rodríguez-Póo, Juan M. & Sperlich, Stefan, 2011. "Low dimensional semiparametric estimation in a censored regression model," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 118-129, January.
    22. Stéphane Girard & Gilles Claude Stupfler & Antoine Usseglio-Carleve, 2021. "Extreme Conditional Expectile Estimation in Heavy-Tailed Heteroscedastic Regression Models," Post-Print hal-03306230, HAL.
    23. Sujica, Aleksandar & Van Keilegom, Ingrid, 2018. "The copula-graphic estimator in censored nonparametric location-scale regression models," Econometrics and Statistics, Elsevier, vol. 7(C), pages 89-114.
    24. Anastasia Semykina & Jeffrey M. Wooldridge, 2018. "Binary response panel data models with sample selection and self‐selection," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(2), pages 179-197, March.
    25. Chesher, Andrew, 2009. "Excess heterogeneity, endogeneity and index restrictions," Journal of Econometrics, Elsevier, vol. 152(1), pages 37-45, September.
    26. Ai, Chunrong & Li, Hongjun & Lin, Zhongjian & Meng, Meixia, 2015. "Estimation of panel data partly specified Tobit regression with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 316-326.
    27. Lu, Xuewen & Cheng, Tsung-Lin, 2007. "Randomly censored partially linear single-index models," Journal of Multivariate Analysis, Elsevier, vol. 98(10), pages 1895-1922, November.
    28. Matzkin, Rosa L., 2012. "Identification in nonparametric limited dependent variable models with simultaneity and unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 166(1), pages 106-115.
    29. Jinzhi Bu & David Simchi-Levi & Li Wang, 2023. "Offline Pricing and Demand Learning with Censored Data," Management Science, INFORMS, vol. 69(2), pages 885-903, February.
    30. Maria Karlsson & Thomas Laitila, 2014. "Finite mixture modeling of censored regression models," Statistical Papers, Springer, vol. 55(3), pages 627-642, August.
    31. Jing Cheng & Dylan S. Small, 2021. "Semiparametric models and inference for the effect of a treatment when the outcome is nonnegative with clumping at zero," Biometrics, The International Biometric Society, vol. 77(4), pages 1187-1201, December.
    32. Elias Ould-Saïd & Mohamed Lemdani, 2006. "Asymptotic Properties of a Nonparametric Regression Function Estimator with Randomly Truncated Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(2), pages 357-378, June.
    33. Rodriguez Poo, Juan M. & Sperlich, Stefan & Vieu, Philippe, 2000. "Semiparametric estimation of weak and strong separable models," DES - Working Papers. Statistics and Econometrics. WS 10064, Universidad Carlos III de Madrid. Departamento de Estadística.
    34. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    35. Chen, Songnian & Zhou, Yahong, 2010. "Semiparametric and nonparametric estimation of sample selection models under symmetry," Journal of Econometrics, Elsevier, vol. 157(1), pages 143-150, July.
    36. Efang Kong & Oliver Linton & Yingcun Xia, 2011. "Global Bahadur representation for nonparametric censored regression quantiles and its applications," CeMMAP working papers CWP33/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    37. Koul, Hira L. & Song, Weixing & Liu, Shan, 2014. "Model checking in Tobit regression via nonparametric smoothing," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 36-49.

  123. Oliver Linton, 2000. "Edgeworth Approximations for Semiparametric Instrumental Variable Estimators and Test Statistics," STICERD - Econometrics Paper Series 399, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Kundhi, Gubhinder & Rilstone, Paul, 2012. "Edgeworth expansions for GEL estimators," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 118-146.
    2. Carrasco, Marine, 2012. "A regularization approach to the many instruments problem," Journal of Econometrics, Elsevier, vol. 170(2), pages 383-398.
    3. Chen, Songnian & Zhang, Hanghui, 2015. "Binary quantile regression with local polynomial smoothing," Journal of Econometrics, Elsevier, vol. 189(1), pages 24-40.
    4. Paul Rilstone, 2021. "Higher-Order Stochastic Expansions and Approximate Moments for Non-linear Models with Heterogeneous Observations," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 99-120, December.
    5. Marine Carrasco & Rachidi Kotchoni, 2013. "Efficient Estimation Using the Characteristic Function," Working Papers hal-00867850, HAL.
    6. Matsushita, Yukitoshi & Otsu, Taisuke, 2020. "Likelihood inference on semiparametric models with generated regressors," LSE Research Online Documents on Economics 102696, London School of Economics and Political Science, LSE Library.
    7. Juan Carlos Escanciano, 2010. "The Integrated Instrumental Variables Estimator: Exploiting Nonlinearities for Identification of Linear Models," CAEPR Working Papers 2010-001, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.

  124. Oliver Linton & Gregory Connor, 2000. "Semiparametric Estimation of a Characteristic-Based Factor Model of Stock Returns," FMG Discussion Papers dp346, Financial Markets Group.

    Cited by:

    1. Fengler, Matthias R. & Härdle, Wolfgang Karl & Mammen, Enno, 2005. "A dynamic semiparametric factor model for implied volatility string dynamics," SFB 649 Discussion Papers 2005-020, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  125. Douglas J Hodgson & Oliver Linton & Keith Vorkink, 2000. "Testing the Capital Asset Pricing Model Efficiently under Elliptical Symmetry: A Semiparametric Approach," STICERD - Econometrics Paper Series 398, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    2. Sima M. Fortsch & Jeong Hoon Choi & Elena A. Khapalova, 2022. "Competition can help predict sales," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 331-344, March.
    3. Bao, Te & Diks, Cees & Li, Hao, 2018. "A generalized CAPM model with asymmetric power distributed errors with an application to portfolio construction," Economic Modelling, Elsevier, vol. 68(C), pages 611-621.
    4. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2004. "Testing forward exchange rate unbiasedness efficiently: a semiparametric approach," Journal of Applied Economics, Universidad del CEMA, vol. 7, pages 325-353, November.
    5. Hallin, M. & Werker, B.J.M. & van den Akker, R., 2015. "Optimal Pseudo-Gaussian and Rank-based Tests of the Cointegration Rank in Semiparametric Error-correction Models," Discussion Paper 2015-001, Tilburg University, Center for Economic Research.
    6. Amengual, Dante & Sentana, Enrique, 2010. "A comparison of mean-variance efficiency tests," Journal of Econometrics, Elsevier, vol. 154(1), pages 16-34, January.
    7. Taras Bodnar & Yarema Okhrin & Valdemar Vitlinskyy & Taras Zabolotskyy, 2018. "Determination and estimation of risk aversion coefficients," Computational Management Science, Springer, vol. 15(2), pages 297-317, June.
    8. Bodnar, Taras & Reiß, Markus, 2016. "Exact and asymptotic tests on a factor model in low and large dimensions with applications," Journal of Multivariate Analysis, Elsevier, vol. 150(C), pages 125-151.
    9. Gabriele Fiorentini & Enrique Sentana, 2018. "Consistent Non-Gaussian Pseudo Maximum Likelihood Estimators," Working Papers wp2018_1802, CEMFI.
    10. Sladana Babic & Laetitia Gelbgras & Marc Hallin & Christophe Ley, 2019. "Optimal tests for elliptical symmetry: specified and unspecified location," Working Papers ECARES 2019-26, ULB -- Universite Libre de Bruxelles.
    11. Marie-Claude Beaulieu & Jean-Marie Dufour & Lynda Khalaf, 2005. "Exact Multivariate Tests of Asset Pricing Models with Stable Asymmetric Distributions," CIRANO Working Papers 2005s-03, CIRANO.
    12. Gabriele Fiorentini & Enrique Sentana, 2007. "On the efficiency and consistency of likelihood estimation in multivariate conditionally heteroskedastic dynamic regression models," Working Paper series 38_07, Rimini Centre for Economic Analysis.
    13. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2010. "Asset-pricing anomalies and spanning: Multivariate and multifactor tests with heavy-tailed distributions," Journal of Empirical Finance, Elsevier, vol. 17(4), pages 763-782, September.
    14. Hailong Qian & Heather L. Bednarek, 2015. "Partial efficient estimation of SUR models," Economics Bulletin, AccessEcon, vol. 35(1), pages 338-348.
    15. Vitali Alexeev & Alex Maynard, 2010. "Localized Level Crossing Random Walk Test Robust to the Presence of Structural Breaks," Working Papers 1001, University of Guelph, Department of Economics and Finance.
    16. Asimit, Alexandru V. & Jones, Bruce L., 2007. "Extreme behavior of bivariate elliptical distributions," Insurance: Mathematics and Economics, Elsevier, vol. 41(1), pages 53-61, July.
    17. Dawood Ashraf, 2016. "Does Shari’ah Screening Cause Abnormal Returns? Empirical Evidence from Islamic Equity Indices," Journal of Business Ethics, Springer, vol. 134(2), pages 209-228, March.
    18. Vintilă Georgeta & Păunescu Radu Alin, 2015. "Econometric Tests of the CAPM Model for a Portfolio Composed of Companies Listed on Nasdaq and Dow Jones Components," Scientific Annals of Economics and Business, Sciendo, vol. 62(3), pages 453-480, November.
    19. Hallin, Marc & van den Akker, Ramon & Werker, Bas J.M., 2016. "Semiparametric error-correction models for cointegration with trends: Pseudo-Gaussian and optimal rank-based tests of the cointegration rank," Journal of Econometrics, Elsevier, vol. 190(1), pages 46-61.
    20. Hafner, C.M. & Rombouts, J.V.K., 2004. "Semiparametric multivariate volatility models," Econometric Institute Research Papers EI 2004-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    21. Manuel Galea & David Cademartori & Roberto Curci & Alonso Molina, 2020. "Robust Inference in the Capital Asset Pricing Model Using the Multivariate t -distribution," JRFM, MDPI, vol. 13(6), pages 1-22, June.
    22. Enrique Sentana, 2009. "The econometrics of mean-variance efficiency tests: a survey," Econometrics Journal, Royal Economic Society, vol. 12(3), pages 65-101, November.
    23. Guermat, Cherif & Freeman, Mark C., 2010. "A net beta test of asset pricing models," International Review of Financial Analysis, Elsevier, vol. 19(1), pages 1-9, January.
    24. Sakhanenko, Lyudmila, 2008. "Testing for ellipsoidal symmetry: A comparison study," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 565-581, December.
    25. Danilo Leal & Rodrigo Jiménez & Marco Riquelme & Víctor Leiva, 2023. "Elliptical Capital Asset Pricing Models: Formulation, Diagnostics, Case Study with Chilean Data, and Economic Rationale," Mathematics, MDPI, vol. 11(6), pages 1-27, March.
    26. Hodgson, Douglas J & Vorkink, Keith P, 2003. "Efficient Estimation of Conditional Asset-Pricing Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 269-283, April.
    27. Taras Bodnar & Arjun K. Gupta & Valdemar Vitlinskyi & Taras Zabolotskyy, 2019. "Statistical Inference for the Beta Coefficient," Risks, MDPI, vol. 7(2), pages 1-14, May.
    28. Douglas Hodgson & Barrett Slade & Keith Vorkink, 2006. "Constructing Commercial Indices: A Semiparametric Adaptive Estimator Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 32(2), pages 151-168, March.
    29. Peremans, Kris & Van Aelst, Stefan, 2018. "Robust inference for seemingly unrelated regression models," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 212-224.
    30. Francq, C. & Jiménez-Gamero, M.D. & Meintanis, S.G., 2017. "Tests for conditional ellipticity in multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 196(2), pages 305-319.
    31. Zheyuan Zhang & Huiying Wu & Sammy Xiaoyan Ying & Jiaxing You, 2023. "Corporate Innovation and Disclosure Strategy," Abacus, Accounting Foundation, University of Sydney, vol. 59(1), pages 76-133, March.

  126. Oliver Linton & Enno Mammen & Jens Perch Nielsen & C Tanggaard, 2000. "Yield Curve Estimation by Kernel Smoothing Methods," STICERD - Econometrics Paper Series 385, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. David Bolder & Scott Gusba, 2002. "Exponentials, Polynomials, and Fourier Series: More Yield Curve Modelling at the Bank of Canada," Staff Working Papers 02-29, Bank of Canada.
    2. Oleksandr Castello & Marina Resta, 2025. "Optimal Time Varying Parameters in Yield Curve Modeling and Forecasting: A Simulation Study on BRICS Countries," Computational Economics, Springer;Society for Computational Economics, vol. 65(4), pages 2081-2113, April.
    3. Yan Liu & Jing Cynthia Wu, 2020. "Reconstructing the Yield Curve," NBER Working Papers 27266, National Bureau of Economic Research, Inc.
    4. Andreasen, Martin M. & Christensen, Bent Jesper, 2015. "The SR approach: A new estimation procedure for non-linear and non-Gaussian dynamic term structure models," Journal of Econometrics, Elsevier, vol. 184(2), pages 420-451.
    5. Victor A. Lapshin & Vadim Ya. Kaushanskiy, 2014. "A Nonparametric Method For Term Structure Fitting With Automatic Smoothing," HSE Working papers WP BRP 39/FE/2014, National Research University Higher School of Economics.
    6. Lorenčič Eva, 2016. "Testing the Performance of Cubic Splines and Nelson-Siegel Model for Estimating the Zero-coupon Yield Curve," Naše gospodarstvo/Our economy, Sciendo, vol. 62(2), pages 42-50, June.
    7. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    8. Thomas A. Severini & Gautam Tripathi, 2005. "Some Identification Issues in Nonparametric Linear Models with Endogenous Regressors," Working papers 2005-12, University of Connecticut, Department of Economics.
    9. Andrew Jeffrey & Oliver Linton & Thong Nguyen, 2001. "Flexible Term Structure Estimation: Which Method Is Preferred?," Yale School of Management Working Papers ysm171, Yale School of Management, revised 01 Oct 2001.
    10. Tatyana Krivobokova & Göran Kauermann & Theofanis Archontakis, 2006. "Estimating the term structure of interest rates using penalized splines," Statistical Papers, Springer, vol. 47(3), pages 443-459, June.
    11. Oliver Linton & Enno Mammen, 2003. "Estimating Semiparametric ARCH (8) Models by Kernel Smoothing Methods," STICERD - Econometrics Paper Series 453, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    12. Hiroyuki Kawakatsu, 2020. "Recovering Yield Curves from Dynamic Term Structure Models with Time-Varying Factors," Stats, MDPI, vol. 3(3), pages 1-46, August.
    13. Tong, Xiaojun & He, Zhuoqiong Chong & Sun, Dongchu, 2018. "Estimating Chinese Treasury yield curves with Bayesian smoothing splines," Econometrics and Statistics, Elsevier, vol. 8(C), pages 94-124.
    14. Wali Ullah & Yasumasa Matsuda & Yoshihiko Tsukuda, 2014. "Dynamics of the term structure of interest rates and monetary policy: is monetary policy effective during zero interest rate policy?," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(3), pages 546-572, March.
    15. Laurini, Márcio Poletti & Hotta, Luiz Koodi, 2010. "Bayesian extensions to Diebold-Li term structure model," International Review of Financial Analysis, Elsevier, vol. 19(5), pages 342-350, December.
    16. Mammen, Enno & Park, Byeong U. & Schienle, Melanie, 2012. "Additive models: Extensions and related models," SFB 649 Discussion Papers 2012-045, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    17. Dennis Schroers, 2024. "Robust Functional Data Analysis for Stochastic Evolution Equations in Infinite Dimensions," Papers 2401.16286, arXiv.org, revised Sep 2025.
    18. Fengler, Matthias R. & Härdle, Wolfgang & Mammen, Enno, 2003. "Implied volatility string dynamics," SFB 373 Discussion Papers 2003,54, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    19. Ivailo Arsov & Matthew Brooks & Mitch Kosev, 2013. "New Measures of Australian Corporate Credit Spreads," RBA Bulletin (Print copy discontinued), Reserve Bank of Australia, pages 15-26, December.
    20. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.
    21. Cai, Junyang & Zhou, Jian, 2022. "How many asymptomatic cases were unconfirmed in the US COVID-19 pandemic? The evidence from a serological survey," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    22. Michiel De Pooter, 2007. "Examining the Nelson-Siegel Class of Term Structure Models," Tinbergen Institute Discussion Papers 07-043/4, Tinbergen Institute.

  127. Steve Berry & Oliver Linton & Ariel Pakes, 2000. "Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems," STICERD - Econometrics Paper Series 400, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    Cited by:

    1. Patrick Bayer & Fernando Ferreira & Robert McMillan, 2007. "A Unified Framework for Measuring Preferences for Schools and Neighborhoods," Working Papers 07-27, Center for Economic Studies, U.S. Census Bureau.
    2. Nicolai V. Kuminoff & V. Kerry Smith & Christopher Timmins, 2013. "The New Economics of Equilibrium Sorting and Policy Evaluation Using Housing Markets," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1007-1062, December.
    3. Freyberger, Joachim, 2015. "Asymptotic theory for differentiated products demand models with many markets," Journal of Econometrics, Elsevier, vol. 185(1), pages 162-181.
    4. Livy, Mitchell R. & Klaiber, H. Allen, 2014. "Preference Tradeoffs Across Spatial Scales: Developing a Micro Level Sorting Model," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169990, Agricultural and Applied Economics Association.
    5. Pietro Tebaldi & Alexander Torgovitsky & Hanbin Yang, 2019. "Nonparametric Estimates of Demand in the California Health Insurance Exchange," NBER Working Papers 25827, National Bureau of Economic Research, Inc.
    6. Lapo Filistrucchi & Tobias J. Klein, 2013. "Price Competition in Two-Sided Markets with Heterogeneous Consumers and Network Effects," Working Papers 13-20, NET Institute.
    7. Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," Cowles Foundation Discussion Papers 2312, Cowles Foundation for Research in Economics, Yale University.
    8. Gregory Verdugo, 2016. "Public housing magnets: public housing supply and immigrants’ location choices," Journal of Economic Geography, Oxford University Press, vol. 16(1), pages 237-265.
    9. Richards, Timothy J. & Allender, William J. & Hamilton, Stephen F., 2012. "Commodity price inflation, retail pass-through and market power," International Journal of Industrial Organization, Elsevier, vol. 30(1), pages 50-57.
    10. Thomas W. Quan & Kevin R. Williams, 2017. "Product Variety, Across-Market Demand Heterogeneity, and the Value of Online Retail," Cowles Foundation Discussion Papers 2054R3, Cowles Foundation for Research in Economics, Yale University, revised Jun 2018.
    11. Patrick Bayer & Robert McMillan & Kim Rueben, 2004. "An Equilibrium Model of Sorting in an Urban Housing Market," NBER Working Papers 10865, National Bureau of Economic Research, Inc.
    12. Patrick Bayer & Christopher Timmins, 2003. "Estimating Equilibrium Models of Sorting across Locations," Working Papers 862, Economic Growth Center, Yale University.
    13. Murdock, Jennifer, 2006. "Handling unobserved site characteristics in random utility models of recreation demand," Journal of Environmental Economics and Management, Elsevier, vol. 51(1), pages 1-25, January.
    14. Mattia Girotti & Richard Meade, 2017. "U.S. Savings Banks' Demutualization and Depositor Welfare," Working papers 639, Banque de France.
    15. Dede Long & David Lewis & Christian Langpap, 2021. "Negative Traffic Externalities and Infant Health: The Role of Income Heterogeneity and Residential Sorting," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 80(3), pages 637-674, November.
    16. Bayer, Patrick & McMillan, Robert & Rueben, Kim, 2003. "An Equilibrium Model of Sorting in an Urban Housing Market: The Causes and Consequences of Residential Segregation," Center Discussion Papers 28503, Yale University, Economic Growth Center.
    17. Christos Genakos, 2004. "DIFFERENTIAL MERGER EFFECTS: The Case of the Personal Computer Industry," STICERD - Economics of Industry Papers 39, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    18. Sinha, Paramita & Caulkins, Martha & Cropper, Maureen L., 2018. "Do Discrete Choice Approaches to Valuing Urban Amenities Yield Different Results Than Hedonic Models?," RFF Working Paper Series 18-02, Resources for the Future.
    19. Reiss, Peter C. & Wolak, Frank A., 2003. "Structural Econometric Modeling: Rationales and Examples from Industrial Organization," Research Papers 1831, Stanford University, Graduate School of Business.
    20. Kühn, Kai-Uwe & Van Reenen, John & Genakos, Christos, 2011. "Leveraging Monopoly Power by Degrading Interoperability: Theory and evidence from computer markets," CEPR Discussion Papers 8502, C.E.P.R. Discussion Papers.
    21. Stépahne Auray & Nicolas Lepage-Saucier & Purevdorj Tuvaandor, 2018. "Doubly Robust GMM Inference and Differentiated Products Demand Models," Working Papers 2018-13, Center for Research in Economics and Statistics.
    22. Maija Gao & Ari Hyytinen & Otto Toivanen, 2014. "Problems in Launching the Mobile Internet: Evidence From a Pricing Experiment," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 23(3), pages 483-506, September.
    23. Escobari, Diego, 2017. "Airport, airline and departure time choice and substitution patterns: An empirical analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 198-210.
    24. Irene Brambilla, 2005. "A Customs Union with Multinational Firms: The Automobile Market in Argentina and Brazil," NBER Working Papers 11745, National Bureau of Economic Research, Inc.
    25. Kandelhardt, Johannes, 2023. "Flexible estimation of random coefficient logit models of differentiated product demand," DICE Discussion Papers 399, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    26. Jinhyuk Lee & Kyoungwon Seo, 2015. "A computationally fast estimator for random coefficients logit demand models using aggregate data," RAND Journal of Economics, RAND Corporation, vol. 46(1), pages 86-102, March.
    27. Steven T. Berry & Philip A. Haile, 2009. "Nonparametric Identification of Multinomial Choice Demand Models with Heterogeneous Consumers," NBER Working Papers 15276, National Bureau of Economic Research, Inc.
    28. Sinha, Paramita & Cropper, Maureen L., 2013. "The Value of Climate Amenities: Evidence from US Migration Decisions," RFF Working Paper Series dp-13-01, Resources for the Future.
    29. Oliver Linton & Jens Perch Nielsen & Søren Feodor Nielsen, 2009. "Non-parametric regression with a latent time series," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 187-207, July.
    30. Amit Gandhi & Zhentong Lu & Xiaoxia Shi, 2023. "Estimating demand for differentiated products with zeroes in market share data," Quantitative Economics, Econometric Society, vol. 14(2), pages 381-418, May.
    31. Patrick Bayer & Robert McMillan & Kim Rueben, 2004. "Residential Segregation in General Equilibrium," Working Papers 885, Economic Growth Center, Yale University.
    32. Bartosz Olesiński, 2020. "The Analysis of the Tobacco Product Bans Using a Random Coefficients Logit Model," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(2), pages 113-144, June.
    33. Ali Hortaçsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2023. "Demand estimation with infrequent purchases and small market sizes," Quantitative Economics, Econometric Society, vol. 14(4), pages 1251-1294, November.
    34. Patrick Bayer & Robert McMillan, 2005. "Racial Sorting and Neighborhood Quality," NBER Working Papers 11813, National Bureau of Economic Research, Inc.
    35. Patrick Bayer & Robert McMillan & Kim Rueben, 2003. "An Equilibrium Model of Sorting in an Urban Housing Market: A Study of the Causes and Consequences of Residential Segregation," Working Papers 03-01, Center for Economic Studies, U.S. Census Bureau.
    36. Thomas W. Quan & Kevin R. Williams, 2017. "Product Variety, Across-Market Demand Heterogeneity, and the Value of Online Retail," Cowles Foundation Discussion Papers 2054R, Cowles Foundation for Research in Economics, Yale University.
    37. Tra, Constant I., 2007. "Equilibrium Welfare Impacts of the 1990 Clean Air Act Amendments in the Los Angeles Area," Working Papers 7341, University of Maryland, Department of Agricultural and Resource Economics.
    38. Sungho Park & Sachin Gupta, 2012. "Comparison of SML and GMM estimators for the random coefficient logit model using aggregate data," Empirical Economics, Springer, vol. 43(3), pages 1353-1372, December.
    39. Susan Athey & Guido Imbens, 2006. "Discrete Choice Models with Multiple Unobserved Choice Characteristics," Levine's Bibliography 122247000000001040, UCLA Department of Economics.
    40. Hyungsik Roger Moon & Matthew Shum & Martin Weidner, 2017. "Estimation of random coefficients logit demand models with interactive fixed effects," CeMMAP working papers 12/17, Institute for Fiscal Studies.
    41. Hyungsik Roger Roger Moon & Matthew Shum & Martin Weidner, 2012. "Estimation of random coefficients logit demand models with interactive fixed effects," CeMMAP working papers 08/12, Institute for Fiscal Studies.
    42. Kenneth L. Judd & Ben Skrainka, 2011. "High performance quadrature rules: how numerical integration affects a popular model of product differentiation," CeMMAP working papers CWP03/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    43. Jong-Shi Pang & Che-Lin Su & Yu-Ching Lee, 2015. "A Constructive Approach to Estimating Pure Characteristics Demand Models with Pricing," Operations Research, INFORMS, vol. 63(3), pages 639-659, June.
    44. Yonezawa, Koichi & Richards, Timothy J., 2016. "Competitive Package Size Decisions," Journal of Retailing, Elsevier, vol. 92(4), pages 445-469.
    45. McFadden, Daniel, 2022. "Instability in mixed logit demand models," Journal of choice modelling, Elsevier, vol. 43(C).
    46. Carolina Caetano & Gregorio Caetano & Hao Fe & Eric R. Nielsen, 2021. "A Dummy Test of Identification in Models with Bunching," Finance and Economics Discussion Series 2021-068, Board of Governors of the Federal Reserve System (U.S.).
    47. Qiang Guo & Christopher Koch & Aiyong Zhu, 2017. "Joint audit, audit market structure, and consumer surplus," Review of Accounting Studies, Springer, vol. 22(4), pages 1595-1627, December.
    48. Allen Klaiber, H. & Phaneuf, Daniel J., 2010. "Valuing open space in a residential sorting model of the Twin Cities," Journal of Environmental Economics and Management, Elsevier, vol. 60(2), pages 57-77, September.
    49. Brunner, Daniel & Heiss, Florian & Romahn, André & Weiser, Constantin, 2025. "Simulation error and numerical instability in estimating random coefficient logit demand models," Journal of Econometrics, Elsevier, vol. 247(C).
    50. Ricardo Ribeiro, 2008. "Market Dominance and Barriers to Competition in Financial Trading Venues," Working Papers 08-35, NET Institute, revised Oct 2008.
    51. Bayer, Patrick & Timmins, Christopher, 2003. "Estimating Equilibrium Models of Sorting Across Locations," Center Discussion Papers 28448, Yale University, Economic Growth Center.
    52. Philipp Ketz, 2019. "On asymptotic size distortions in the random coefficients logit model," PSE-Ecole d'économie de Paris (Postprint) halshs-02302067, HAL.
    53. Sinha, Paramita & Caulkins, Martha & Cropper, Maureen, 2021. "The value of climate amenities: A comparison of hedonic and discrete choice approaches," Journal of Urban Economics, Elsevier, vol. 126(C).
    54. Sun, Yutec & Ishihara, Masakazu, 2019. "A computationally efficient fixed point approach to dynamic structural demand estimation," Journal of Econometrics, Elsevier, vol. 208(2), pages 563-584.
    55. Laura Grigolon, 2017. "Blurred boundaries: a flexible approach for segmentation applied to the car market," Department of Economics Working Papers 2017-17, McMaster University.
    56. Hyungsik Roger Moon & Matthew Shum & Martin Weidner, 2012. "Estimation of random coefficients logit demand models with interactive fixed effects," CeMMAP working papers CWP08/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    57. Satoshi Myojo & Yuichiro Kanazawa, 2010. "On Asymptotic Properties of the Parameters of Differentiated Product Demand and Supply Systems When Demographically-Categorized Purchasing Pattern Data are Available," Discussion Papers 1009, Graduate School of Economics, Kobe University.
    58. Ali Hortacsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Incorporating Search and Sales Information in Demand Estimation," Cowles Foundation Discussion Papers 2313R1, Cowles Foundation for Research in Economics, Yale University, revised Mar 2023.
    59. Jacek Białek & Natalia Pawelec & Sylwia Roszkowska, 2024. "Estimating the elasticity of substitution when compiling the CES cost of living index on scanner data," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(6), pages 5997-6021, December.
    60. Charles Romeo, 2007. "A Gibbs sampler for mixed logit analysis of differentiated product markets using aggregate data," Computational Economics, Springer;Society for Computational Economics, vol. 29(1), pages 33-68, February.
    61. , 2023. "Price Competition and Endogenous Product Choice in Networks: Evidence from the US airline Industry," Working Papers 950, Queen Mary University of London, School of Economics and Finance.
    62. John Yinger, 2009. "Hedonic Markets and Explicit Demands: Bid-Function Envelopes for Public Services, Neighborhood Amenities, and Commuting Costs," Center for Policy Research Working Papers 114, Center for Policy Research, Maxwell School, Syracuse University.
    63. Sinha, Paramita & Caulkins, Martha & Cropper, Maureen, 2018. "Do Discrete Choice Approaches to Valuing Urban Amenities Yield Different Results Than Hedonic Models?," National Center for Environmental Economics-NCEE Working Papers 280947, United States Environmental Protection Agency (EPA).
    64. Amit Gandhi Gandhi & Zhentong Lu & Xiaoxia Shi, 2013. "Estimating demand for differentiated products with error in market shares," CeMMAP working papers CWP03/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    65. davis, peter, 2006. "The Discrete Choice Analytically Flexible (DCAF) Model of Demand for Differentiated Products," CEPR Discussion Papers 5880, C.E.P.R. Discussion Papers.
    66. Gao, Maija & Hyytinen, Ari & Toivanen, Otto, 2005. "Demand for Mobile Internet: Evidence from a Real-World Pricing Experiment," Discussion Papers 964, The Research Institute of the Finnish Economy.
    67. Alexander Konovalov & Zsolt Sándor, 2010. "On price equilibrium with multi-product firms," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 44(2), pages 271-292, August.
    68. Minjae Song, 2015. "A Hybrid Discrete Choice Model Of Differentiated Product Demand With An Application To Personal Computers," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(1), pages 265-301, February.
    69. Carlos Perez Montes, 2012. "Regulatory bias in the price structure of local telephone services," Working Papers 1201, Banco de España.
    70. Masayuki Sawada & Kohei Kawaguchi, 2020. "Estimating High-Dimensional Discrete Choice Model of Differentiated Products with Random Coefficients," Papers 2004.08791, arXiv.org.
    71. Lu, Zhentong & Shi, Xiaoxia & Tao, Jing, 2023. "Semi-nonparametric estimation of random coefficients logit model for aggregate demand," Journal of Econometrics, Elsevier, vol. 235(2), pages 2245-2265.
    72. Cao, Xiang & Boyle, Kevin J. & Siriwardena, Shyamani D. & Holmes, Thomas P., "undated". "Estimating Demand for Urban Tree Cover Using a Residential Sorting Model," 2018 Annual Meeting, August 5-7, Washington, D.C. 274020, Agricultural and Applied Economics Association.
    73. Joachim Freyberger, 2012. "Asymptotic theory for differentiated products demand models with many markets," CeMMAP working papers 19/12, Institute for Fiscal Studies.
    74. Brown, Zachary S. & Connor, Lawson & Rejesus, Roderick M. & Yorobe Jr., Jose M., "undated". "Bioeconomic feedbacks from large-scale adoption of transgenic pesticidal corn in the Philippines," CEnREP Working Papers 272080, North Carolina State University, Department of Agricultural and Resource Economics.
    75. Daniel L. McFadden, 2013. "The New Science of Pleasure," NBER Working Papers 18687, National Bureau of Economic Research, Inc.
    76. Qin Fan & Meri Davlasheridze, 2016. "Flood Risk, Flood Mitigation, and Location Choice: Evaluating the National Flood Insurance Program's Community Rating System," Risk Analysis, John Wiley & Sons, vol. 36(6), pages 1125-1147, June.
    77. Holmes, Thomas J. & Sieg, Holger, 2015. "Structural Estimation in Urban Economics," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 69-114, Elsevier.
    78. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    79. Iaria, Alessandro & ,, 2020. "Identification and Estimation of Demand for Bundles," CEPR Discussion Papers 14363, C.E.P.R. Discussion Papers.
    80. Fan, Qin & Klaiber, H. Allen & Fisher-Vanden, Karen, 2012. "Climate Change Impacts on U.S. Migration and Household Location Choice," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124588, Agricultural and Applied Economics Association.
    81. Fan, Qin & Davlasheridze, Meri, 2014. "Evaluating the Effectiveness of Flood Mitigation Policies in the U.S," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169399, Agricultural and Applied Economics Association.
    82. Hyungsik Roger Roger Moon & Matthew Shum & Martin Weidner, 2014. "Estimation of random coefficients logit demand models with interactive fixed effects," CeMMAP working papers 20/14, Institute for Fiscal Studies.
    83. Fernández-Antolín, Anna & Guevara, C. Angelo & de Lapparent, Matthieu & Bierlaire, Michel, 2016. "Correcting for endogeneity due to omitted attitudes: Empirical assessment of a modified MIS method using RP mode choice data," Journal of choice modelling, Elsevier, vol. 20(C), pages 1-15.
    84. Kevin YC Chung & Timothy P. Derdenger & Kannan Srinivasan, 2013. "Economic Value of Celebrity Endorsements: Tiger Woods' Impact on Sales of Nike Golf Balls," Marketing Science, INFORMS, vol. 32(2), pages 271-293, March.
    85. Doi, Naoshi, 2022. "A simple method to estimate discrete-type random coefficients logit models," International Journal of Industrial Organization, Elsevier, vol. 81(C).

  128. Nielsen, Jens P. & Linton, Oliver & Bickel, Peter J., 1998. "On a semiparametric survival model with flexible covariate effect," LSE Research Online Documents on Economics 301, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Xuewen Lu & Jie Sun & Yongcheng Qi, 2008. "Empirical likelihood for average derivatives of hazard regression functions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 67(1), pages 93-112, January.
    2. Lu, Xuewen, 2010. "Asymptotic distributions of two "synthetic data" estimators for censored single-index models," Journal of Multivariate Analysis, Elsevier, vol. 101(4), pages 999-1015, April.
    3. Tang, Xingyu & Li, Jianbo & Lian, Heng, 2013. "Empirical likelihood for partially linear proportional hazards models with growing dimensions," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 22-32.
    4. Sun, Jie & Kopciuk, Karen A. & Lu, Xuewen, 2008. "Polynomial spline estimation of partially linear single-index proportional hazards regression models," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 176-188, September.
    5. van den Berg, Gerard. J. & Janys, Lena & Mammen, Enno & Nielsen, Jens Perch, 2021. "A general semiparametric approach to inference with marker-dependent hazard rate models," Journal of Econometrics, Elsevier, vol. 221(1), pages 43-67.
    6. Spierdijk, Laura, 2008. "Nonparametric conditional hazard rate estimation: A local linear approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2419-2434, January.
    7. Li, Jianbo & Zhang, Riquan, 2011. "Partially varying coefficient single index proportional hazards regression models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 389-400, January.

  129. Oliver Linton & E. Mammen & J. Nielsen & C. Tanggaard, 1998. "Estimating Yield Curves by Kernel Smoothing Methods," Cowles Foundation Discussion Papers 1205, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Andrew Jeffrey & Linton, Oliver Linton & Thong Nguyen & Peter C.B. Phillips, 2001. "Nonparametric Estimation of a Multifactor Heath-Jarrow-Morton Model: An Integrated Approach," Cowles Foundation Discussion Papers 1311, Cowles Foundation for Research in Economics, Yale University.

  130. Sperlich, Stefan & Hardle, Wolfgang & Linton, Oliver, 1998. "Integration and Backfitting methods in additive models: finite sample properties and comparison," DES - Working Papers. Statistics and Econometrics. WS 6270, Universidad Carlos III de Madrid. Departamento de Estadística.

    Cited by:

    1. Sukjin Han, 2012. "Nonparametric Estimation of Triangular Simultaneous Equations Models under Weak Identification," Department of Economics Working Papers 140414, The University of Texas at Austin, Department of Economics, revised Apr 2014.
    2. Graciela Boente & Alejandra Martínez, 2017. "Marginal integration M-estimators for additive models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 231-260, June.
    3. Scholz, Michael & Sperlich, Stefan & Nielsen, Jens Perch, 2016. "Nonparametric long term prediction of stock returns with generated bond yields," Insurance: Mathematics and Economics, Elsevier, vol. 69(C), pages 82-96.
    4. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    5. Guo, Zheng-Feng & Shintani, Mototsugu, 2011. "Nonparametric lag selection for nonlinear additive autoregressive models," Economics Letters, Elsevier, vol. 111(2), pages 131-134, May.
    6. Müller, Ursula U. & Schick, Anton & Wefelmeyer, Wolfgang, 2014. "Testing for additivity in partially linear regression with possibly missing responses," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 51-61.
    7. Martins-Filho, Carlos & yang, ke, 2007. "Finite sample performance of kernel-based regression methods for non-parametric additive models under common bandwidth selection criterion," MPRA Paper 39295, University Library of Munich, Germany.
    8. Yang, Lijian & Sperlich, Stefan & Hardle, Wolfgang, 2000. "Derivative estimation and testing in generalized additive models," DES - Working Papers. Statistics and Econometrics. WS 10084, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. Su, Liangjun & Ullah, Aman, 2008. "Local polynomial estimation of nonparametric simultaneous equations models," Journal of Econometrics, Elsevier, vol. 144(1), pages 193-218, May.
    10. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 2001. "Bootstrap Inference in Semiparametric Generalized Additive Models," Finance Working Papers 01-3, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    11. Jing Dai & Stefan Sperlich & Walter Zucchini, 2011. "Estimating and predicting the distribution of the number of visits to the medical doctor," MAGKS Papers on Economics 201148, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    12. Wolfgang Karl Hardle & Elena Silyakova, 2020. "Implied Basket Correlation Dynamics," Papers 2009.09770, arXiv.org.
    13. Härdle Wolfgang Karl & Silyakova Elena, 2016. "Implied basket correlation dynamics," Statistics & Risk Modeling, De Gruyter, vol. 33(1-2), pages 1-20, September.
    14. Berthold R. Haag, 2008. "Non‐parametric Regression Tests Using Dimension Reduction Techniques," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 35(4), pages 719-738, December.
    15. Grasshoff, Ulrike & Schwalbach, Joachim & Sperlich, Stefan, 1999. "Executive pay and corporate financial performance. An exploratiove data analysis," DES - Working Papers. Statistics and Econometrics. WS 6382, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Graciela Boente & Alejandra Martínez & Matías Salibián-Barrera, 2017. "Robust estimators for additive models using backfitting," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(4), pages 744-767, October.
    17. Rodriguez Poo, Juan M. & Sperlich, Stefan & Vieu, Philippe, 2000. "Semiparametric estimation of weak and strong separable models," DES - Working Papers. Statistics and Econometrics. WS 10064, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Hengartner, Nicolas W. & Sperlich, Stefan, 2005. "Rate optimal estimation with the integration method in the presence of many covariates," Journal of Multivariate Analysis, Elsevier, vol. 95(2), pages 246-272, August.
    19. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.
    20. Fernández, Ana I. & Rodríguez-Póo, Juan M. & Sperlich, Stefan, 1998. "Semiparametric three step estimation methods in labor supply models," SFB 373 Discussion Papers 1998,71, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  131. Arthur Lewbel & Linton, Oliver Linton, 1998. "Nonparametric Censored Regression," Cowles Foundation Discussion Papers 1186, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Inês Figueira & Rayan Succar & Roni Barak Ventura & Maurizio Porfiri, 2025. "Urban scaling with censored data," PLOS Complex Systems, Public Library of Science, vol. 2(1), pages 1-22, January.
    2. Chen, Songnian & Khan, Shakeeb, 2000. "Estimating censored regression models in the presence of nonparametric multiplicative heteroskedasticity," Journal of Econometrics, Elsevier, vol. 98(2), pages 283-316, October.
    3. Richard Blundell & James L. Powell, 2001. "Endogeneity in semiparametric binary response models," CeMMAP working papers 05/01, Institute for Fiscal Studies.

  132. Oliver Linton, 1997. "Second Order Approximation in a Linear Regression with Heteroskedasticity for Unknown Form," Cowles Foundation Discussion Papers 1151, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Oliver Linton & Douglas G. Steigerwald, 1995. "Adaptive Testing in ARCH Models," Cowles Foundation Discussion Papers 1105, Cowles Foundation for Research in Economics, Yale University.
    2. Peter C.B. Phillips & Binbin Guo & Zhijie Xiao, 2002. "Efficient Regression in Time Series Partial Linear Models," Cowles Foundation Discussion Papers 1363, Cowles Foundation for Research in Economics, Yale University.

  133. Yanqin Fan & Oliver Linton, 1997. "Some Higher Order Theory for a Consistent Nonparametric Model Specification Test," Cowles Foundation Discussion Papers 1148, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Fernandes, Marcelo, 2001. "Nonparametric entropy-based tests of independence between stochastic processes," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 413, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Marcelo Fernandes & Joachim Grammig, 2000. "Non-Parametric Specification Tests For Conditional Duration Models," Computing in Economics and Finance 2000 40, Society for Computational Economics.
    3. Gao, Jiti & Casas, Isabel, 2006. "Specification testing in discretized diffusion models: Theory and practice," MPRA Paper 11980, University Library of Munich, Germany, revised Aug 2007.
    4. Patrick Marsh, "undated". "Nonparametric Likelihood Ratio Tests," Discussion Papers 00/56, Department of Economics, University of York.
    5. Gao, Jiti & Gijbels, Irene, 2005. "Bandwidth selection for nonparametric kernel testing," MPRA Paper 11982, University Library of Munich, Germany, revised Jun 2007.
    6. Oliver Linton & Pedro Gozalo, 1995. "Testing Additivity in Generalized Nonparametric Regression Models," Cowles Foundation Discussion Papers 1106, Cowles Foundation for Research in Economics, Yale University.
    7. Joao Amaro de Matos & Marcelo Fernandes, 2004. "Testing the Markov property with ultra-high frequency financial data," Nova SBE Working Paper Series wp462, Universidade Nova de Lisboa, Nova School of Business and Economics.

  134. Arthur Lewbel & Daniel McFadden & Oliver Linton, 1997. "Estimating Features of a Distribution from Binomial Data," Boston College Working Papers in Economics 442, Boston College Department of Economics, revised 01 Jul 2010.

    Cited by:

    1. Arthur Lewbel & Xun Tang, 2012. "Identification and Estimation of Games with Incomplete Information Using Excluded Regressors," Boston College Working Papers in Economics 808, Boston College Department of Economics, revised 05 Mar 2013.
    2. Thierry Kalisa & Mary Riddel & W. Douglass Shaw, 2016. "Willingness to pay to avoid arsenic-related risks: a special regressor approach," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 5(2), pages 143-162, July.
    3. Bontemps, Christian & Magnac, Thierry & Maurin, Eric, 2007. "Set Identified Linear Models," IDEI Working Papers 494, Institut d'Économie Industrielle (IDEI), Toulouse.
    4. Arthur Lewbel & Oliver Linton, 2003. "Nonparametric estimation of homothetic and homothetically separable functions," CeMMAP working papers CWP14/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Bo E. Honore & Arthur Lewbel, 1998. "Semiparametric Binary Choice Panel Data Models without Strictly Exogeneous Regressors," Boston College Working Papers in Economics 455, Boston College Department of Economics, revised 22 Sep 2001.
    6. Jones, Benjamin A. & Ripberger, Joseph & Jenkins-Smith, Hank & Silva, Carol, 2017. "Estimating willingness to pay for greenhouse gas emission reductions provided by hydropower using the contingent valuation method," Energy Policy, Elsevier, vol. 111(C), pages 362-370.
    7. Mogens Fosgerau, 2004. "Investigating the distribution of the value of travel time savings," Urban/Regional 0411006, University Library of Munich, Germany.
    8. Yingying Dong & Arthur Lewbel, 2012. "A Simple Estimator for Binary Choice Models With Endogenous Regressors," Boston College Working Papers in Economics 807, Boston College Department of Economics.
    9. Arthur Lewbel, 2002. "Ordered Response Threshold Estimation," Boston College Working Papers in Economics 535, Boston College Department of Economics, revised 29 Oct 2003.
    10. Arthur Lewbel & Yingying Dong & Thomas Tao Yang, 2012. "Viewpoint: Comparing features of convenient estimators for binary choice models with endogenous regressors," Canadian Journal of Economics, Canadian Economics Association, vol. 45(3), pages 809-829, August.
    11. Arthur Lewbel, 2000. "Endogenous Selection Or Treatment Model Estimation," Boston College Working Papers in Economics 462, Boston College Department of Economics, revised 13 Jun 2007.
    12. Arthur Lewbel & Yingying Dong & Thomas Tao Yang, 2012. "Comparing features of convenient estimators for binary choice models with endogenous regressors," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 45(3), pages 809-829, August.
    13. Chu, Ba & Jacho-Chávez, David T., 2012. "k-NEAREST NEIGHBOR ESTIMATION OF INVERSE-DENSITY-WEIGHTED EXPECTATIONS WITH DEPENDENT DATA," Econometric Theory, Cambridge University Press, vol. 28(4), pages 769-803, August.
    14. Mogens Fosgerau, 2005. "Specification Of A Model To Measure - The Value Of Travel Time Savings From Binomial Data," ERSA conference papers ersa05p77, European Regional Science Association.
    15. Bravo, Francesco & Escanciano, Juan Carlos & Van Keilegom, Ingrid, 2015. "Wilks' Phenomenon in Two-Step Semiparametric Empirical Likelihood Inference," LIDAM Discussion Papers ISBA 2015016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    16. Fosgerau, Mogens & Hjort, Katrine & Vincent Lyk-Jensen, Stéphanie, 2007. "An approach to the estimation of the distribution of marginal valuations from discrete choice data," MPRA Paper 3907, University Library of Munich, Germany.
    17. Arthur Lewbel, 2005. "Simple Endogenous Binary Choice and Selection Panel Model Estimators," Boston College Working Papers in Economics 613, Boston College Department of Economics, revised 04 Sep 2006.
    18. Michael Hanemann & Jon Krosnick & Lisanne Wichgers & Jeffrey Wooldridge & Stephanie Lampron & Daniel Schneider & Eric M. Shaeffer & Trevor Tompson & Penny Visser, 2025. "Ben Franklin’s Whistle, Cost Expectations, and the Choice of Valuation Format," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 88(5), pages 1375-1406, May.
    19. Mogens Fosgerau, 2024. "Nonparametric approaches to describing heterogeneity," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 11, pages 308-318, Edward Elgar Publishing.
    20. Arthur Lewbel & Xun Tang, 2010. "Identification and Estimation of Games with Incomplete Information Using Excluded Regressors, Second Version," PIER Working Paper Archive 12-018, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 20 Mar 2012.
    21. Magnac, Thierry & Maurin, Eric, 2007. "Identification and information in monotone binary models," Journal of Econometrics, Elsevier, vol. 139(1), pages 76-104, July.
    22. Cheng Chou & Vineet Kumar, 2024. "Estimating Demand for Subscription Products: Identification of Willingness to Pay Without Price Variation," Marketing Science, INFORMS, vol. 43(4), pages 797-816, July.
    23. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
    24. Arthur Lewbel, 2006. "Modeling Heterogeneity," Boston College Working Papers in Economics 650, Boston College Department of Economics.
    25. Arthur Lewbel, 2012. "An Overview of the Special Regressor Method," Boston College Working Papers in Economics 810, Boston College Department of Economics.
    26. Matzkin, Rosa L., 2012. "Identification in nonparametric limited dependent variable models with simultaneity and unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 166(1), pages 106-115.
    27. Kim, Sooil, 2006. "Bias and Efficiency of Uniform Bid Design in Contingent Valuation," 2006 Annual meeting, July 23-26, Long Beach, CA 21335, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    28. Robert J. Johnston & Kevin J. Boyle & Wiktor (Vic) Adamowicz & Jeff Bennett & Roy Brouwer & Trudy Ann Cameron & W. Michael Hanemann & Nick Hanley & Mandy Ryan & Riccardo Scarpa & Roger Tourangeau & Ch, 2017. "Contemporary Guidance for Stated Preference Studies," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(2), pages 319-405.
    29. Lewbel, Arthur, 2000. "Semiparametric qualitative response model estimation with unknown heteroscedasticity or instrumental variables," Journal of Econometrics, Elsevier, vol. 97(1), pages 145-177, July.
    30. Daniel McFadden, 2008. "Semiparametric analysis (in Russian)," Quantile, Quantile, issue 5, pages 29-40, September.
    31. Arthur Lewbel, 2018. "The Identification Zoo - Meanings of Identification in Econometrics," Boston College Working Papers in Economics 957, Boston College Department of Economics, revised 14 Dec 2019.
    32. Arthur Lewbel & Susanne M. Schennach, 2003. "A Simple Ordered Data Estimator For Inverse Density Weighted Functions," Boston College Working Papers in Economics 557, Boston College Department of Economics, revised 01 May 2005.
    33. Arthur Lewbel & Oliver Linton, 2003. "Nonparametric Matching and Efficient Estimators of Homothetically Separable Functions," Boston College Working Papers in Economics 585, Boston College Department of Economics, revised 04 Sep 2006.
    34. Jones, Benjamin A. & Berrens, Robert P. & Jenkins-Smith, Hank & Silva, Carol & Ripberger, Joe & Carlson, Deven & Gupta, Kuhika & Wehde, Wesley, 2018. "In search of an inclusive approach: Measuring non-market values for the effects of complex dam, hydroelectric and river system operations," Energy Economics, Elsevier, vol. 69(C), pages 225-236.

  135. Sperlich, S. & Linton, O. & Härdle, Wolfgang, 1997. "A Simulation Comparison between Integration and Backfitting Methods of Estimating Separable Nonparametric Regression Models," SFB 373 Discussion Papers 1997,66, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Gozalo, Pedro L. & Linton, Oliver B., 2001. "Testing additivity in generalized nonparametric regression models with estimated parameters," Journal of Econometrics, Elsevier, vol. 104(1), pages 1-48, August.
    2. Profit, Stefan & Sperlich, Stefan, 1999. "Non-uniformity of job-matching in a transition economy- a nonparametric analysis for the czech republic," DES - Working Papers. Statistics and Econometrics. WS 6287, Universidad Carlos III de Madrid. Departamento de Estadística.

  136. Yoon-Jae Whang & Oliver Linton, 1997. "The Asymptotic Distribution of Nonparametric Estimates of the Lyapunov Exponent for Stochastic Time Series," Cowles Foundation Discussion Papers 1130R, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. J. Barkley Rosser, 1999. "On the Complexities of Complex Economic Dynamics," Journal of Economic Perspectives, American Economic Association, vol. 13(4), pages 169-192, Fall.
    2. Park, Joon Y. & Whang, Yoon-Jae, 2012. "Random walk or chaos: A formal test on the Lyapunov exponent," Journal of Econometrics, Elsevier, vol. 169(1), pages 61-74.
    3. Kyrtsou, Catherine & Serletis, Apostolos, 2006. "Univariate tests for nonlinear structure," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 154-168, March.
    4. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
    5. Mototsugu Shintani, 2004. "A Dynamic Factor Approach to Nonlinear Stability Analysis," Vanderbilt University Department of Economics Working Papers 0418, Vanderbilt University Department of Economics.
    6. Park Joon Y. & Whang Yoon-Jae, 2005. "A Test of the Martingale Hypothesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(2), pages 1-32, June.
    7. Mototsugu Shintani & Oliver Linton, 2001. "Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors," Vanderbilt University Department of Economics Working Papers 0111, Vanderbilt University Department of Economics.
    8. Orzeszko, Witold, 2008. "The new method of measuring the effects of noise reduction in chaotic data," Chaos, Solitons & Fractals, Elsevier, vol. 38(5), pages 1355-1368.
    9. Charles-Cadogan, G., 2021. "Market Instability, Investor Sentiment, And Probability Judgment Error in Index Option Prices," CRETA Online Discussion Paper Series 71, Centre for Research in Economic Theory and its Applications CRETA.
    10. Oliver Linton & Mototsugu Shintani, 2002. "Nonparametric Neutral Network Estimation of Lyapunov Exponents and a Direct Test for Chaos," STICERD - Econometrics Paper Series 434, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    11. Serletis, Apostolos & Shahmoradi, Asghar, 2007. "Chaos, self-organized criticality, and SETAR nonlinearity: An analysis of purchasing power parity between Canada and the United States," Chaos, Solitons & Fractals, Elsevier, vol. 33(5), pages 1437-1444.
    12. Bask, Mikael & de Luna, Xavier, 2001. "EMU and the Stability and Volatility of Foreign Exchange: Some Empirical Evidence," Umeå Economic Studies 565, Umeå University, Department of Economics.
    13. Serletis, Apostolos & Uritskaya, Olga Y., 2007. "Detecting signatures of stochastic self-organization in US money and velocity measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 281-291.
    14. Serletis, Apostolos & Shahmoradi, Asghar & Serletis, Demitre, 2007. "Effect of noise on estimation of Lyapunov exponents from a time series," Chaos, Solitons & Fractals, Elsevier, vol. 32(2), pages 883-887.
    15. Bask, Mikael & de Luna, Xavier, 2001. "Characterizing the degree of stability of non-linear dynamic models," Umeå Economic Studies 564, Umeå University, Department of Economics.
    16. Kyrtsou, Catherine & Malliaris, Anastasios G. & Serletis, Apostolos, 2009. "Energy sector pricing: On the role of neglected nonlinearity," Energy Economics, Elsevier, vol. 31(3), pages 492-502, May.
    17. Serletis, Apostolos & He, Mingyu & Chowdhury, M.M. Islam, 2023. "Chaos in long-maturity real rates," Economics Letters, Elsevier, vol. 225(C).
    18. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Testing Chaotic Dynamics via Lyapunov Exponents," Working Papers 2000-07, FEDEA.
    19. Sandubete, Julio E. & Escot, Lorenzo, 2020. "Chaotic signals inside some tick-by-tick financial time series," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    20. Jorge Belaire-Franch & Kwaku Opong, 2013. "A Time Series Analysis of U.K. Construction and Real Estate Indices," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 516-542, April.
    21. Serletis, Apostolos & Shintani, Mototsugu, 2006. "Chaotic monetary dynamics with confidence," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 228-252, March.
    22. Wolff, Rodney C. & Yao, Qiwei & Tong, Howell, 2004. "Statistical tests for Lyapunov exponents of deterministic systems," LSE Research Online Documents on Economics 154, London School of Economics and Political Science, LSE Library.
    23. Escot, Lorenzo & Sandubete, Julio E., 2023. "Estimating Lyapunov exponents on a noisy environment by global and local Jacobian indirect algorithms," Applied Mathematics and Computation, Elsevier, vol. 436(C).
    24. Giannerini Simone & Rosa Rodolfo, 2004. "Assessing Chaos in Time Series: Statistical Aspects and Perspectives," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-25, May.
    25. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "A New Test for Chaotic Dynamics Using Lyapunov Exponents," Working Papers 2003-09, FEDEA.

  137. Oliver Linton & Pedro Gozalo, 1996. "Conditional Independence Restrictions: Testing and Estimation," Cowles Foundation Discussion Papers 1140, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Poirier, Alexandre, 2017. "Efficient estimation in models with independence restrictions," Journal of Econometrics, Elsevier, vol. 196(1), pages 1-22.
    2. Guido Imbens & Jeffrey M. Wooldridge, 2008. "Recent developments in the econometrics of program evaluation," CeMMAP working papers CWP24/08, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Cheng, Yu-Hsiang & Huang, Tzee-Ming, 2012. "A conditional independence test for dependent data based on maximal conditional correlation," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 210-226.
    4. Yanqin Fan & Oliver Linton, 1997. "Some Higher Order Theory for a Consistent Nonparametric Model Specification Test," Cowles Foundation Discussion Papers 1148, Cowles Foundation for Research in Economics, Yale University.
    5. Oliver Linton & Yoon-Jae Whang & Yu-Min Yen, 2012. "A nonparametric test of the leverage hypothesis," CeMMAP working papers CWP24/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Joeri Smits & Jeffrey S. Racine, 2013. "Testing Exclusion Restrictions in Nonseparable Triangular Models," Department of Economics Working Papers 2013-02, McMaster University.
    7. Xu, Kai & Cheng, Qing, 2024. "Test of conditional independence in factor models via Hilbert–Schmidt independence criterion," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    8. Joao Amaro de Matos & Marcelo Fernandes, 2004. "Testing the Markov property with ultra-high frequency financial data," Nova SBE Working Paper Series wp462, Universidade Nova de Lisboa, Nova School of Business and Economics.
    9. Györfi, László & Walk, Harro, 2012. "Strongly consistent nonparametric tests of conditional independence," Statistics & Probability Letters, Elsevier, vol. 82(6), pages 1145-1150.

  138. Nielsen, J. P. & Linton, O. B., 1996. "An Optimization Interpretation of Integration and Backfitting Estimators for Separable Nonparametric Models," SFB 373 Discussion Papers 1996,88, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Oliver B. Linton & Enno Mammen & J. Nielsen & Carsten Tanggaard, 2000. "Yield Curve Estimation by Kernel Smoothing Methods," Econometric Society World Congress 2000 Contributed Papers 0235, Econometric Society.
    2. Graciela Boente & Alejandra Martínez, 2017. "Marginal integration M-estimators for additive models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 231-260, June.
    3. Patrick Saart & Jiti Gao & Nam Hyun Kim, 2014. "Semiparametric methods in nonlinear time series analysis: a selective review," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(1), pages 141-169, March.
    4. Abe, Makoto & Boztuæg, Yasemin & Hildebrandt, Lutz, 2000. "Investigation of the stochastic utility maximization process of consumer brand choice by semiparametric modeling," SFB 373 Discussion Papers 2000,84, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. Nathalie Chèze & Jean-Michel Poggi & Bruno Portier, 2003. "Partial and Recombined Estimators for Nonlinear Additive Models," Statistical Inference for Stochastic Processes, Springer, vol. 6(2), pages 155-197, May.
    6. Degui Li & Oliver Linton & Zudi Lu, 2012. "A flexible semiparametric model for time series," CeMMAP working papers CWP28/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Makoto Abe & Yasemin Boztug & Lutz Hildebrandt, 2004. "Investigating the competitive assumption of Multinomial Logit models of brand choice by nonparametric modeling," Computational Statistics, Springer, vol. 19(4), pages 635-657, December.
    8. Oliver Linton & E. Mammen & J. Nielsen & C. Tanggaard, 1998. "Estimating Yield Curves by Kernel Smoothing Methods," Cowles Foundation Discussion Papers 1205, Cowles Foundation for Research in Economics, Yale University.
    9. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    10. Lawrence Dacuycuy, 2006. "Explaining male wage inequality in the Philippines: non-parametric and semiparametric approaches," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2497-2511.
    11. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.
    12. Li, Qi & Hsiao, Cheng & Zinn, Joel, 2003. "Consistent specification tests for semiparametric/nonparametric models based on series estimation methods," Journal of Econometrics, Elsevier, vol. 112(2), pages 295-325, February.
    13. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    14. Mammen, Enno & Martínez Miranda, María Dolores & Nielsen, Jens Perch, 2015. "In-sample forecasting applied to reserving and mesothelioma mortality," Insurance: Mathematics and Economics, Elsevier, vol. 61(C), pages 76-86.

  139. Oliver Linton, 1996. "An Asymptotic Expansion in the Garch(1,1) Model," Cowles Foundation Discussion Papers 1118, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Demos, Antonis & Arvanitis, Stelios, 2010. "Stochastic Expansions and Moment Approximations for Three Indirect Estimators," MPRA Paper 122369, University Library of Munich, Germany.
    2. Emma M. Iglesias & Garry D. A. Phillips, 2012. "Estimation, Testing, and Finite Sample Properties of Quasi-Maximum Likelihood Estimators in GARCH-M Models," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 532-557, September.
    3. Dietmar P. J. Leisen, 2017. "The shape of small sample biases in pricing kernel estimations," Quantitative Finance, Taylor & Francis Journals, vol. 17(6), pages 943-958, June.
    4. Yong Bao, 2013. "On Sample Skewness and Kurtosis," Econometric Reviews, Taylor & Francis Journals, vol. 32(4), pages 415-448, December.
    5. Rodrigo Alfaro & Carmen Gloria Silva, 2008. "Measuring Equity Volatility: the case of Chilean Stock Index," Working Papers Central Bank of Chile 462, Central Bank of Chile.

  140. Härdle, Wolfgang & Linton, O., 1995. "Nonparametric Regression," SFB 373 Discussion Papers 1995,29, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Severance-Lossin, E. & Sperlich, Stefan, 1997. "Estimation of derivates for additive separable models," SFB 373 Discussion Papers 1997,30, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    2. Susumu Imai & Neelam Jain, 2005. "Bayesian Estimation of Dynamic Discrete Choice Models," 2005 Meeting Papers 432, Society for Economic Dynamics.
    3. Profit, Stefan & Sperlich, Stefan, 1999. "Non-uniformity of job-matching in a transition economy- a nonparametric analysis for the czech republic," DES - Working Papers. Statistics and Econometrics. WS 6287, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Sperlich, Stefan & Tjøstheim, Dag & Yang, Lijian, 2002. "Nonparametric Estimation And Testing Of Interaction In Additive Models," Econometric Theory, Cambridge University Press, vol. 18(2), pages 197-251, April.
    5. Arthur Lewbel & Oliver Linton, 2002. "Nonparametric Censored and Truncated Regression," Econometrica, Econometric Society, vol. 70(2), pages 765-779, March.
    6. Schimek, Michael G. & Turlach, Berwin A., 1998. "Additive and generalized additive models: A survey," SFB 373 Discussion Papers 1998,97, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Richard Blundell & Martin Browning & Ian Crawford, 1997. "Non-parametric Engel curves and revealed preferences," IFS Working Papers W97/14, Institute for Fiscal Studies.
    8. Christine A. Ribic & Thomas W. Miller, 1998. "Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART," Journal of Applied Statistics, Taylor & Francis Journals, vol. 25(5), pages 685-698, June.
    9. Wichert, Laura & Wilke, Ralf A., 2005. "Application of a simple nonparametric conditional quantile function estimator in unemployment duration analysis," ZEW Discussion Papers 05-67, ZEW - Leibniz Centre for European Economic Research.
    10. Oliver Linton & Pedro Gozalo, 1995. "Testing Additivity in Generalized Nonparametric Regression Models," Cowles Foundation Discussion Papers 1106, Cowles Foundation for Research in Economics, Yale University.
    11. Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 1998. "Semiparametric additive indices for binary response and generalized additive models," SFB 373 Discussion Papers 1998,95, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    12. Fernández, Ana I. & Rodríguez-Póo, Juan M. & Sperlich, Stefan, 1998. "Semiparametric three step estimation methods in labor supply models," SFB 373 Discussion Papers 1998,71, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  141. Linton, O. B. & Härdle, Wolfgang, 1995. "Estimation of Additive Regression Models with Links," SFB 373 Discussion Papers 1995,48, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Yang, Lijian & Park, Byeong U. & Xue, Lan & Hardle, Wolfgang, 2006. "Estimation and Testing for Varying Coefficients in Additive Models With Marginal Integration," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1212-1227, September.
    2. Schimek, Michael G. & Turlach, Berwin A., 1998. "Additive and generalized additive models: A survey," SFB 373 Discussion Papers 1998,97, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    3. Kempe, Wolfram, 1997. "Das Arbeitsangebot verheirateter Frauen in den neuen und alten Bundesländern: Eine semiparametrische Regressionsanalyse," SFB 373 Discussion Papers 1997,3, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. Yang, Lijian & Härdle, Wolfgang & Nielsen, Jens P., 1998. "Nonparametric autoregression with multiplicative volatility and additive mean," SFB 373 Discussion Papers 1998,107, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    6. Efang Kong & Oliver Linton & Yingcun Xia, 2011. "Global Bahadur representation for nonparametric censored regression quantiles and its applications," CeMMAP working papers CWP33/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Härdle, Wolfgang & Sperlich, Stefan & Spokoiny, Vladimir G., 1997. "Component analysis for additive models," SFB 373 Discussion Papers 1997,52, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

  142. Linton, O. B. & Chen, R. & Härdle, Wolfgang, 1995. "An Analysis of Transformations for Additive Nonparanetric Regression," SFB 373 Discussion Papers 1995,68, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Chen, Xiaohong & Linton, Oliver & Van Keilegom, Ingrid, 2003. "Estimation of semiparametric models when the criterion function is not smooth," LSE Research Online Documents on Economics 2167, London School of Economics and Political Science, LSE Library.
    2. Hess, Sebastian & Cramon-Taubadel, Stephan von & Sperlich, 2010. "Numbers for Pascal: Explaining differences in the Estimated Benefited of the Doha Developing Agenda," Department of Agricultural and Rural Development (DARE) Discussion Papers 187311, Georg-August-Universitaet Goettingen, Department of Agricultural Economics and Rural Development (DARE).
    3. Gozalo, Pedro L. & Linton, Oliver B., 2001. "Testing additivity in generalized nonparametric regression models with estimated parameters," Journal of Econometrics, Elsevier, vol. 104(1), pages 1-48, August.
    4. Kim, Woocheol & Linton, Oliver, 2004. "A local instrumental variable estimation method for generalized additive volatility models," LSE Research Online Documents on Economics 24758, London School of Economics and Political Science, LSE Library.
    5. Stefan Sperlich & Oliver Linton & Wolfgang Härdle, 1999. "Integration and backfitting methods in additive models-finite sample properties and comparison," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 8(2), pages 419-458, December.
    6. Lawrence Dacuycuy, 2006. "Explaining male wage inequality in the Philippines: non-parametric and semiparametric approaches," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2497-2511.
    7. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
    8. J. S. Allison & M. Hušková & S. G. Meintanis, 2018. "Testing the adequacy of semiparametric transformation models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 70-94, March.
    9. Fryzlewicz, Piotr & Delouille, V´eronique & Nason, Guy P., 2007. "GOES-8 X-ray sensor variance stabilization using the multiscale data-driven Haar-Fisz transform," LSE Research Online Documents on Economics 25221, London School of Economics and Political Science, LSE Library.

  143. Oliver Linton & Pedro Gozalo, 1995. "Testing Additivity in Generalized Nonparametric Regression Models," Cowles Foundation Discussion Papers 1106, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Joris Pinkse, 2000. "Feasible Multivariate Nonparametric Estimation Using Weak Separability," Econometric Society World Congress 2000 Contributed Papers 1241, Econometric Society.

  144. Chen, R. & Härdle, Wolfgang & Linton, O. B. & Severance-Lossin, E., 1995. "Nonparametric Estimation of Additive Seperable Regression Models," SFB 373 Discussion Papers 1995,50, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.

    Cited by:

    1. Graciela Boente & Alejandra Martínez, 2017. "Marginal integration M-estimators for additive models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(2), pages 231-260, June.
    2. Avalos, Marta & Grandvalet, Yves & Ambroise, Christophe, 2007. "Parsimonious additive models," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2851-2870, March.
    3. Morteza Haghiri & James Nolan & Kien Tran, 2004. "Assessing the impact of economic liberalization across countries: a comparison of dairy industry efficiency in Canada and the USA," Applied Economics, Taylor & Francis Journals, vol. 36(11), pages 1233-1243.
    4. Damian Kozbur, 2013. "Inference in additively separable models with a high-dimensional set of conditioning variables," ECON - Working Papers 284, Department of Economics - University of Zurich, revised Apr 2018.
    5. Kempe, Wolfram, 1997. "Das Arbeitsangebot verheirateter Frauen in den neuen und alten Bundesländern: Eine semiparametrische Regressionsanalyse," SFB 373 Discussion Papers 1997,3, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. Chèze-Payaud, Nathalie & Poggi, Jean-Michel & Portier, Bruno, 1998. "Estimation and test of linearity for a class of additive nonlinear models," Statistics & Probability Letters, Elsevier, vol. 40(2), pages 189-201, September.
    7. Morteza Haghiri & Alireza Simchi, 2005. "An application of the residual deviance analysis in testing input separability restrictions," Applied Economics Letters, Taylor & Francis Journals, vol. 12(12), pages 755-758.
    8. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.

  145. Oliver Linton & Douglas G. Steigerwald, 1995. "Adaptive Testing in ARCH Models," Cowles Foundation Discussion Papers 1105, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Broze, Laurence & Gourieroux, Christian, 1998. "Pseudo-maximum likelihood method, adjusted pseudo-maximum likelihood method and covariance estimators," Journal of Econometrics, Elsevier, vol. 85(1), pages 75-98, July.
    2. Gabriele Fiorentini & Enrique Sentana, 2018. "New Testing Approaches for Mean-Variance Predictability," Working Papers wp2018_1814, CEMFI.
    3. Gabriele Fiorentini & Enrique Sentana, 2007. "On the efficiency and consistency of likelihood estimation in multivariate conditionally heteroskedastic dynamic regression models," Working Paper series 38_07, Rimini Centre for Economic Analysis.
    4. Hodgson, Douglas J & Vorkink, Keith P, 2003. "Efficient Estimation of Conditional Asset-Pricing Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 269-283, April.

  146. Pedro Gozalo & Oliver Linton, 1994. "Local Nonlinear Least Squares Estimation: Using Parametric Information Nonparametrically," Cowles Foundation Discussion Papers 1075, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Arthur Lewbel & Oliver Linton, 2003. "Nonparametric estimation of homothetic and homothetically separable functions," CeMMAP working papers CWP14/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Mittelhammer, Ron C. & Judge, George, 2011. "A family of empirical likelihood functions and estimators for the binary response model," Journal of Econometrics, Elsevier, vol. 164(2), pages 207-217, October.
    3. Bossaerts, P.L.M. & Hillion, P., 1995. "Local Parametric Analysis of Hedging in Discrete Time," Discussion Paper 1995-23, Tilburg University, Center for Economic Research.
    4. Arthur Lewbel, 2007. "Estimation of Average Treatment Effects with Misclassification," Econometrica, Econometric Society, vol. 75(2), pages 537-551, March.
    5. Rosa Bernardini Papalia, 1999. "Local generalized method of moments estimation based on kernel weights: An application to panel data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 1005-1015.
    6. Gozalo, Pedro L., 1997. "Nonparametric bootstrap analysis with applications to demographic effects in demand functions," Journal of Econometrics, Elsevier, vol. 81(2), pages 357-393, December.
    7. Bossaerts, P.L.M. & Hillion, P., 1995. "Local Parametric Analysis of Hedging in Discrete Time," Other publications TiSEM 77cdfe27-8732-4f09-bf89-f, Tilburg University, School of Economics and Management.
    8. Claudia PIGINI, 2012. "Of Butterflies and Caterpillars: Bivariate Normality in the Sample Selection Model," Working Papers 377, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    9. Mittelhammer, Ronald C. & Judge, George G., 2008. "A Minimum Power Divergence Class of CDFs and Estimators for Binary Choice Models," CUDARE Working Papers 37759, University of California, Berkeley, Department of Agricultural and Resource Economics.
    10. Bossaerts, Peter & Hillion, Pierre, 1997. "Local parametric analysis of hedging in discrete time," Journal of Econometrics, Elsevier, vol. 81(1), pages 243-272, November.
    11. Arthur Lewbel & Oliver Linton, 2003. "Nonparametric Matching and Efficient Estimators of Homothetically Separable Functions," Boston College Working Papers in Economics 585, Boston College Department of Economics, revised 04 Sep 2006.

  147. Wolfgang Hardle & Oliver Linton, 1994. "Applied Nonparametric Methods," Cowles Foundation Discussion Papers 1069, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Herwartz, Helmut & Reimers, Hans-Eggert, 2006. "Modelling the Fisher hypothesis: World wide evidence," Economics Working Papers 2006-04, Christian-Albrechts-University of Kiel, Department of Economics.
    2. Burak Saltoglu, 2003. "Comparing forecasting ability of parametric and non-parametric methods: an application with Canadian monthly interest rates," Applied Financial Economics, Taylor & Francis Journals, vol. 13(3), pages 169-176.
    3. Severance-Lossin, E. & Sperlich, Stefan, 1997. "Estimation of derivates for additive separable models," SFB 373 Discussion Papers 1997,30, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    4. Liang, Hua & Härdle, Wolfgang, 1997. "Large sample theory of the estimation of the error distribution for a semiparametric model," SFB 373 Discussion Papers 1997,101, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    5. Das, J.W.M. & Donkers, A.C.D., 1997. "How Certain are Dutch Households about Future Income? An Empirical Analysis," Other publications TiSEM d8aabd66-ddc7-4834-a157-e, Tilburg University, School of Economics and Management.
    6. Matthew Pritsker, 1997. "Nonparametric density estimation and tests of continuous time interest rate models," Finance and Economics Discussion Series 1997-26, Board of Governors of the Federal Reserve System (U.S.).
    7. Hjalmarsson, Erik, 2003. "Does the Black-Scholes formula work for electricity markets? A nonparametric approach," Working Papers in Economics 101, University of Gothenburg, Department of Economics.
    8. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    9. Martin Evans and David Lyons, 2001. "Time-Varying Liquidity in Foreign Exchange," Working Papers gueconwpa~01-01-11, Georgetown University, Department of Economics.
    10. Geng, Xin & Janssens, Wendy & Kramer, Berber, "undated". "Liquid milk: Cash Constraints and Recurring Savings among Dairy Farmers in Kenya," 2018 Annual Meeting, August 5-7, Washington, D.C. 273823, Agricultural and Applied Economics Association.
    11. Mark Broadie & Jérôme Detemple & Eric Ghysels & Olivier Torrès, 1996. "Nonparametric Estimation of American Options Exercise Boundaries and Call Prices," CIRANO Working Papers 96s-24, CIRANO.
    12. Michel Lubrano, 2004. "Modélisation bayésienne non linéaire du taux d’intérêt de court terme américain : l’aide des outils non paramétriques," L'Actualité Economique, Société Canadienne de Science Economique, vol. 80(2), pages 465-499.
    13. Taoufik Bouezmarni & Jeroen V.K. Rombouts, 2006. "Nonparametric Density Estimation for Positive Time Series," Cahiers de recherche 06-09, HEC Montréal, Institut d'économie appliquée.
    14. BERTINELLI, Luisito & STROBL, Eric, 2003. "Urbanization, urban concentration and economic growth in developing countries," LIDAM Discussion Papers CORE 2003076, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Koo, Bonsoo & Linton, Oliver, 2010. "Semiparametric estimation of locally stationary diffusion models," LSE Research Online Documents on Economics 58186, London School of Economics and Political Science, LSE Library.
    16. Raymond J Carroll & Oliver Linton & Enno Mammen & Zhijie Xiao, 2002. "More Efficient Kernel Estimation in Nonparametric Regression with Autocorrelated Errors," STICERD - Econometrics Paper Series 435, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    17. Sophie DABO-NIANG & Christian FRANCQ & Jean-Michel ZAKOIAN, 2009. "Combining Nonparametric and Optimal Linear Time Series Predictions," Working Papers 2009-18, Center for Research in Economics and Statistics.
    18. Sabino da Silva Porto Junior & Eduardo Pontual Ribeiro, 2003. "Dinâmica Espacial da Renda Per capita e Crescimento Entre os Municípios da Região Nordeste do Brasil - uma Análise Markoviana," Anais do XXXI Encontro Nacional de Economia [Proceedings of the 31st Brazilian Economics Meeting] e54, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    19. Fousekis, Panos & Lazaridis, Panagiotis, 2001. "Food Expenditure Patterns of the Urban and the Rural Households in Greece. A Kernel Regression Analysis," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 2(01), pages 1-16, January.
    20. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    21. McCrary, Justin, 2008. "Manipulation of the running variable in the regression discontinuity design: A density test," Journal of Econometrics, Elsevier, vol. 142(2), pages 698-714, February.
    22. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-079, New York University, Leonard N. Stern School of Business-.
    23. Evenett, S. J. & Keller, W., 1994. "On Theories Explaining the Success of the Gravity Equation," Working papers 9713, Wisconsin Madison - Social Systems.
    24. Labandeira, Xavier & Labeaga, José M. & López-Otero, Xiral, 2017. "A meta-analysis on the price elasticity of energy demand," Energy Policy, Elsevier, vol. 102(C), pages 549-568.
    25. Heisz, Andrew & Corak, Miles, 1998. "The Intergenerational Earnings and Income Mobility of Canadian Men: Evidence from Longitudinal Income Tax Data," Analytical Studies Branch Research Paper Series 1998113e, Statistics Canada, Analytical Studies Branch.
    26. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    27. Oliver Linton, 1996. "An Asymptotic Expansion in the Garch(1,1) Model," Cowles Foundation Discussion Papers 1118, Cowles Foundation for Research in Economics, Yale University.
    28. Emmanuel Saez, 2010. "Do Taxpayers Bunch at Kink Points?," American Economic Journal: Economic Policy, American Economic Association, vol. 2(3), pages 180-212, August.
    29. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2004. "Testing forward exchange rate unbiasedness efficiently: a semiparametric approach," Journal of Applied Economics, Universidad del CEMA, vol. 7, pages 325-353, November.
    30. Oliver Linton, 1993. "Second Order Approximation in the Partially Linear Regression Model," Cowles Foundation Discussion Papers 1065, Cowles Foundation for Research in Economics, Yale University.
    31. Oliver Linton & Pedro Gozalo, 1996. "Conditional Independence Restrictions: Testing and Estimation," Cowles Foundation Discussion Papers 1140, Cowles Foundation for Research in Economics, Yale University.
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    Cited by:

    1. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.
    2. Dennis Kristensen, 2009. "Semiparametric modelling and estimation (in Russian)," Quantile, Quantile, issue 7, pages 53-83, September.
    3. Miller, Steve & Startz, Richard, 2019. "Feasible generalized least squares using support vector regression," Economics Letters, Elsevier, vol. 175(C), pages 28-31.
    4. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey & James Robins, 2017. "Double/debiased machine learning for treatment and structural parameters," CeMMAP working papers CWP28/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2014. "Program evaluation with high-dimensional data," CeMMAP working papers CWP33/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Hidehiko Ichimura & Oliver Linton, 2003. "Asymptotic Expansions for Some Semiparametric Program Evaluation Estimators," STICERD - Econometrics Paper Series 451, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    7. Linton, Oliver, 2002. "Edgeworth approximations for semiparametric instrumental variable estimators and test statistics," Journal of Econometrics, Elsevier, vol. 106(2), pages 325-368, February.
    8. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney K. Newey, 2016. "Double machine learning for treatment and causal parameters," CeMMAP working papers CWP49/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Yanqin Fan & Oliver Linton, 1997. "Some Higher Order Theory for a Consistent Nonparametric Model Specification Test," Cowles Foundation Discussion Papers 1148, Cowles Foundation for Research in Economics, Yale University.
    10. Dennis Kristensen, 2009. "Semiparametric Modelling and Estimation: A Selective Overview," CREATES Research Papers 2009-44, Department of Economics and Business Economics, Aarhus University.
    11. Agboola, Oluwagbenga David & Yu, Han, 2023. "Neighborhood-based cross fitting approach to treatment effects with high-dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 186(C).
    12. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2016. "Double/Debiased Machine Learning for Treatment and Causal Parameters," Papers 1608.00060, arXiv.org, revised Nov 2024.
    13. Dennis Kristensen & Bernard Salanié, 2010. "Higher Order Improvements for Approximate Estimators," CAM Working Papers 2010-04, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    14. Y Nishiyama & Peter M Robinson, 1999. "Studentization in Edgworth Expansions for Estimates of Semiparametric Index Models - (Now published in C Hsiao, K Morimune and J Powell (eds): Nonlinear Statistical Modeling (Festschrift for Takeshi A," STICERD - Econometrics Paper Series 374, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    15. Nishiyama, Y & Robinson, Peter, 1999. "Studentization in Edgworth expansions for estimates of semiparametric index models," LSE Research Online Documents on Economics 2095, London School of Economics and Political Science, LSE Library.

  149. Oliver Linton, 1993. "Second Order Approximation in the Partially Linear Regression Model," Cowles Foundation Discussion Papers 1065, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    2. Dennis Kristensen, 2009. "Semiparametric modelling and estimation (in Russian)," Quantile, Quantile, issue 7, pages 53-83, September.
    3. Liu, Yan & Zhang, Sanguo & Ma, Shuangge & Zhang, Qingzhao, 2020. "Tests for regression coefficients in high dimensional partially linear models," Statistics & Probability Letters, Elsevier, vol. 163(C).
    4. Florens, Jean-Pierre & Johannes, Jan & Van Bellegem, Sébastien, 2009. "Instrumental Regression in Partially Linear Models," TSE Working Papers 10-167, Toulouse School of Economics (TSE).
    5. Kotlyarova, Yulia & Schafgans, Marcia M.A. & Zinde-Walsh, Victoria, 2021. "Rates of expansions for functional estimators," LSE Research Online Documents on Economics 113436, London School of Economics and Political Science, LSE Library.
    6. Phillips, Peter C.B., 2014. "Optimal estimation of cointegrated systems with irrelevant instruments," Journal of Econometrics, Elsevier, vol. 178(P2), pages 210-224.
    7. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2004. "Testing forward exchange rate unbiasedness efficiently: a semiparametric approach," Journal of Applied Economics, Universidad del CEMA, vol. 7, pages 325-353, November.
    8. Zhijie Xiao & Peter C.B. Phillips, 1998. "Higher Order Approximations for Wald Statistics in Cointegrating Regressions," Cowles Foundation Discussion Papers 1192, Cowles Foundation for Research in Economics, Yale University.
    9. Byunghoon Kang, 2018. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Working Papers 240829404, Lancaster University Management School, Economics Department.
    10. Xiaohong Chen & Demian Pouzo, 2008. "Efficient Estimation of Semiparametric Conditional Moment Models with Possibly Nonsmooth Residuals," Cowles Foundation Discussion Papers 1640R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2009.
    11. Hardle, Wolfgang & Xia, Yingcun & Linton, Oliver, 2009. "Optimal smoothing for a computationally and statistically efficient single index estimator," LSE Research Online Documents on Economics 58173, London School of Economics and Political Science, LSE Library.
    12. Aneiros-Perez, G. & Vilar-Fernandez, J.M., 2008. "Local polynomial estimation in partial linear regression models under dependence," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2757-2777, January.
    13. Tizheng Li & Yuping Wang, 2024. "Higher-order spatial autoregressive varying coefficient model: estimation and specification test," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 33(4), pages 1258-1299, December.
    14. Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2019. "A Unified Framework for Efficient Estimation of General Treatment Models," CeMMAP working papers CWP64/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Xia, Yingcun & Härdle, Wolfgang, 2002. "Semi-parametric estimation of generalized partially linear single-index models," SFB 373 Discussion Papers 2002,56, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    16. Oliver Linton & Douglas G. Steigerwald, 1995. "Adaptive Testing in ARCH Models," Cowles Foundation Discussion Papers 1105, Cowles Foundation for Research in Economics, Yale University.
    17. Hidehiko Ichimura & Oliver Linton, 2003. "Asymptotic Expansions for Some Semiparametric Program Evaluation Estimators," STICERD - Econometrics Paper Series 451, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    18. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
    19. Alexandra Soberon & Irene D’Hers, 2020. "The Environmental Kuznets Curve: A Semiparametric Approach with Cross-Sectional Dependence," JRFM, MDPI, vol. 13(11), pages 1-23, November.
    20. Yulia Kotlyarova & Marcia M. A. Schafgans & Victoria Zinde-Walsh, 2022. "Correction to: Rates of Expansions for Functional Estimators," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(2), pages 487-487, June.
    21. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2001. "Testing the Capital Asset Pricing Model Efficiently Under Elliptical Symmetry: A Semiparametric Approach," Cahiers de recherche CREFE / CREFE Working Papers 143, CREFE, Université du Québec à Montréal.
    22. Hongjie Wei & Yan Sun, 2017. "Heteroskedasticity-robust semi-parametric GMM estimation of a spatial model with space-varying coefficients," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(1), pages 113-128, January.
    23. Mototsugu Shintani & Oliver Linton, 2001. "Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors," Vanderbilt University Department of Economics Working Papers 0111, Vanderbilt University Department of Economics.
    24. Peter C.B. Phillips & Binbin Guo & Zhijie Xiao, 2002. "Efficient Regression in Time Series Partial Linear Models," Cowles Foundation Discussion Papers 1363, Cowles Foundation for Research in Economics, Yale University.
    25. Haotian Chen & Xibin Zhang, 2014. "Bayesian Estimation for Partially Linear Models with an Application to Household Gasoline Consumption," Monash Econometrics and Business Statistics Working Papers 28/14, Monash University, Department of Econometrics and Business Statistics.
    26. Wang Q. & Linton O. & Hardle W., 2004. "Semiparametric Regression Analysis With Missing Response at Random," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 334-345, January.
    27. Chen, Songnian & Zhang, Hanghui, 2015. "Binary quantile regression with local polynomial smoothing," Journal of Econometrics, Elsevier, vol. 189(1), pages 24-40.
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    37. Byunghoon Kang, 2019. "Inference in Nonparametric Series Estimation with Specification Searches for the Number of Series Terms," Papers 1909.12162, arXiv.org, revised Feb 2020.
    38. Chaohua Dong & Jiti Gao & Oliver Linton, 2022. "Chaohua Dong, Jiti Gao and Oliver Linton’s contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 707-708, July.
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    Cited by:

    1. Thanasis Stengos & Ximing Wu, 2005. "Partially Adaptive Estimation via Maximum Entropy Densities," University of Cyprus Working Papers in Economics 6-2005, University of Cyprus Department of Economics.
    2. Sentana, Enrique & Fiorentini, Gabriele, 2018. "Specification tests for non-Gaussian maximum likelihood estimators," CEPR Discussion Papers 12934, C.E.P.R. Discussion Papers.
    3. Iglesias, Emma M. & Linton, Oliver, 2009. "Estimation of tail thickness parameters from GJR-GARCH models," UC3M Working papers. Economics we094726, Universidad Carlos III de Madrid. Departamento de Economía.
    4. W. K. Li & Shiqing Ling & Michael McAleer, 2001. "A Survey of Recent Theoretical Results for Time Series Models with GARCH Errors," ISER Discussion Paper 0545, Institute of Social and Economic Research, The University of Osaka.
    5. Oliver Linton & Dajing Shang & Yang Yan, 2012. "Efficient estimation of conditional risk measures in a semiparametric GARCH model," CeMMAP working papers 25/12, Institute for Fiscal Studies.
    6. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    7. Amengual, Dante & Fiorentini, Gabriele & Sentana, Enrique, 2013. "Sequential estimation of shape parameters in multivariate dynamic models," Journal of Econometrics, Elsevier, vol. 177(2), pages 233-249.
    8. Thanasis Stengos & Yiguo Sun, 2005. "The Absolute Health Income Hypothesis Revisited : A Semiparametric Quantile Regression Approach," University of Cyprus Working Papers in Economics 7-2005, University of Cyprus Department of Economics.
    9. Gabriele Fiorentini & Enrique Sentana, 2018. "New Testing Approaches for Mean-Variance Predictability," Working Papers wp2018_1814, CEMFI.
    10. Xibin Zhang & Maxwell L. King, 2011. "Bayesian semiparametric GARCH models," Monash Econometrics and Business Statistics Working Papers 24/11, Monash University, Department of Econometrics and Business Statistics.
    11. Francq, Christian & Zakoian, Jean-Michel, 2021. "Local asymptotic normality of general conditionally heteroskedastic and score-driven time-series models," MPRA Paper 106542, University Library of Munich, Germany.
    12. Peter Hall, 2007. "Comments on: Nonparametric inference with generalized likelihood ratio tests," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(3), pages 448-449, December.
    13. Drost, F.C. & Klaassen, C.A.J. & Werker, B.J.M., 1994. "Adaptive estimation in time-series models," Discussion Paper 1994-88, Tilburg University, Center for Economic Research.
    14. Oliver Linton & Douglas G. Steigerwald, 1995. "Adaptive Testing in ARCH Models," Cowles Foundation Discussion Papers 1105, Cowles Foundation for Research in Economics, Yale University.
    15. Xibin Zhang & Maxwell L. King, 2013. "Gaussian kernel GARCH models," Monash Econometrics and Business Statistics Working Papers 19/13, Monash University, Department of Econometrics and Business Statistics.
    16. Hallin, Marc & La Vecchia, Davide, 2017. "R-estimation in semiparametric dynamic location-scale models," Journal of Econometrics, Elsevier, vol. 196(2), pages 233-247.
    17. Mimoto, Nao, 2008. "Convergence in distribution for the sup-norm of a kernel density estimator for GARCH innovations," Statistics & Probability Letters, Elsevier, vol. 78(7), pages 915-923, May.
    18. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2001. "Testing the Capital Asset Pricing Model Efficiently Under Elliptical Symmetry: A Semiparametric Approach," Cahiers de recherche CREFE / CREFE Working Papers 143, CREFE, Université du Québec à Montréal.
    19. Drost, F.C. & Klaassen, C.A.J., 1997. "Efficient estimation in semiparametric GARCH models," Other publications TiSEM c7de3f1c-c456-433e-a1c6-2, Tilburg University, School of Economics and Management.
    20. Safarian, Mher, 2013. "On portfolio risk estimation," Working Paper Series in Economics 52, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    21. Drost, F.C. & Werker, B.J.M., 2004. "Semiparametric duration models," Other publications TiSEM a1895e3e-f720-454b-9613-f, Tilburg University, School of Economics and Management.
    22. Drost, Feike C. & Werker, Bas J. M., 1996. "Closing the GARCH gap: Continuous time GARCH modeling," Journal of Econometrics, Elsevier, vol. 74(1), pages 31-57, September.
    23. Andreou, E. & Werker, B.J.M., 2003. "A Simple Asymptotic Analysis of Residual-Based Statistics," Other publications TiSEM 9fe68e51-a026-4660-b6e7-8, Tilburg University, School of Economics and Management.
    24. Gabriele Fiorentini & Enrique Sentana, 2007. "On the efficiency and consistency of likelihood estimation in multivariate conditionally heteroskedastic dynamic regression models," Working Paper series 38_07, Rimini Centre for Economic Analysis.
    25. O. Linton & E. Mammen, 2005. "Estimating Semiparametric ARCH(∞) Models by Kernel Smoothing Methods," Econometrica, Econometric Society, vol. 73(3), pages 771-836, May.
    26. Douglas Hodgson, 2002. "Semiparametric Efficient Estimation of the Mean of a Time Series in the Presence of Conditional Heterogeneity of Unknown Form," Cahiers de recherche CREFE / CREFE Working Papers 146, CREFE, Université du Québec à Montréal.
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    30. Hafner, C.M. & Rombouts, J.V.K., 2004. "Semiparametric multivariate volatility models," Econometric Institute Research Papers EI 2004-21, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    31. Oliver Linton & Enno Mammen, 2003. "Estimating Semiparametric ARCH (8) Models by Kernel Smoothing Methods," STICERD - Econometrics Paper Series 453, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    32. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    33. Chen, Songnian, 2000. "Rank estimation of a location parameter in the binary choice model," Journal of Econometrics, Elsevier, vol. 98(2), pages 317-334, October.
    34. Linton, Oliver, 1996. "Edgeworth Approximation for MINPIN Estimators in Semiparametric Regression Models," Econometric Theory, Cambridge University Press, vol. 12(1), pages 30-60, March.
    35. Andreou, Elena & Werker, Bas J.M., 2015. "Residual-based rank specification tests for AR–GARCH type models," Journal of Econometrics, Elsevier, vol. 185(2), pages 305-331.
    36. Hu, Shuowen & Poskitt, D.S. & Zhang, Xibin, 2021. "Bayesian estimation for a semiparametric nonlinear volatility model," Economic Modelling, Elsevier, vol. 98(C), pages 361-370.
    37. Andreou, E. & Werker, B.J.M., 2004. "An Alternative Asymptotic Analysis of Residual-Based Statistics," Discussion Paper 2004-56, Tilburg University, Center for Economic Research.
    38. HAFNER, Christian & ROMBOUTS, Jeroen, 2003. "Semiparametric multivariate GARCH models," LIDAM Discussion Papers CORE 2003003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    39. Elena Andreou & Bas J.M. Werker, 2014. "Residual-based Rank Specification Tests for AR-GARCH type models," University of Cyprus Working Papers in Economics 02-2014, University of Cyprus Department of Economics.
    40. Christian Francq & Jean-Michel Zakoïan, 2008. "A Tour in the Asymptotic Theory of GARCH Estimation," Working Papers 2008-03, Center for Research in Economics and Statistics.
    41. Calzolari, Giorgio & Fiorentini, Gabriele, 1994. "Conditional heteroskedasticity in nonlinear simultaneous equations," MPRA Paper 24428, University Library of Munich, Germany.
    42. Hodgson, Douglas J & Vorkink, Keith P, 2003. "Efficient Estimation of Conditional Asset-Pricing Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 269-283, April.
    43. MEDDAHI, Nour & RENAULT, Éric, 1998. "Quadratic M-Estimators for ARCH-Type Processes," Cahiers de recherche 9814, Universite de Montreal, Departement de sciences economiques.
    44. Andreou, E. & Werker, B.J.M., 2004. "An Alternative Asymptotic Analysis of Residual-Based Statistics," Other publications TiSEM 93fe16c1-9f21-4dab-9b73-4, Tilburg University, School of Economics and Management.
    45. Eduardo Rossi, 2010. "Univariate GARCH models: a survey (in Russian)," Quantile, Quantile, issue 8, pages 1-67, July.
    46. Hodgson, Douglas J., 1998. "Adaptive estimation of cointegrating regressions with ARMA errors," Journal of Econometrics, Elsevier, vol. 85(2), pages 231-267, August.
    47. Drost, F.C. & Klaassen, C.A.J., 1996. "Efficient Estimation in Semiparametric GARCH Models," Other publications TiSEM 3da5ac9e-1f93-41b2-aaa0-5, Tilburg University, School of Economics and Management.
    48. Bai, Jushan & Ng, Serena, 2001. "A consistent test for conditional symmetry in time series models," Journal of Econometrics, Elsevier, vol. 103(1-2), pages 225-258, July.
    49. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    50. Jianqing Fan & Lei Qi & Dacheng Xiu, 2014. "Quasi-Maximum Likelihood Estimation of GARCH Models With Heavy-Tailed Likelihoods," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 178-191, April.
    51. Douglas Hodgson & Barrett Slade & Keith Vorkink, 2006. "Constructing Commercial Indices: A Semiparametric Adaptive Estimator Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 32(2), pages 151-168, March.
    52. Werker, Bas J M & Andreou, Elena, 2013. "Residual-based Rank Specification Tests for AR-GARCH type models," CEPR Discussion Papers 9583, C.E.P.R. Discussion Papers.
    53. Shiqing Ling & Michael McAleer, 2001. "On Adaptive Estimation in Nonstationary ARMA Models with GARCH Errors," ISER Discussion Paper 0548, Institute of Social and Economic Research, The University of Osaka.
    54. Chen, Songnian & Zhou, Yahong, 2010. "Semiparametric and nonparametric estimation of sample selection models under symmetry," Journal of Econometrics, Elsevier, vol. 157(1), pages 143-150, July.
    55. Marc Hallin & Davide La Vecchia, 2014. "Semiparametrically Efficient R-Estimation for Dynamic Location-Scale Models," Working Papers ECARES ECARES 2014-45, ULB -- Universite Libre de Bruxelles.
    56. Ciccarelli Nicola, 2018. "Semiparametric efficient adaptive estimation of the GJR-GARCH model," Statistics & Risk Modeling, De Gruyter, vol. 35(3-4), pages 141-160, July.
    57. Xuejie Feng & Chiping Zhang, 2020. "A Perturbation Method to Optimize the Parameters of Autoregressive Conditional Heteroscedasticity Model," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 1021-1044, March.
    58. Andreou, E. & Werker, B.J.M., 2003. "A Simple Asymptotic Analysis of Residual-Based Statistics," Discussion Paper 2003-118, Tilburg University, Center for Economic Research.

  151. Lee, L. & Linton, O. & Whang, Y-J., 0000. "Quantilograms under Strong Dependence," Cambridge Working Papers in Economics 1936, Faculty of Economics, University of Cambridge.

    Cited by:

    1. Alex Maynard & Katsumi Shimotsu & Nina Kuriyama, 2023. "Inference in Predictive Quantile Regressions," Papers 2306.00296, arXiv.org, revised May 2024.

  152. Oliver LINTON, "undated". "Kernel estimation in a nonparametric marker dependent Hazard Model," Statistic und Oekonometrie 9313, Humboldt Universitaet Berlin.

    Cited by:

    1. Toshio Honda, 2005. "Estimation in additive cox models by marginal integration," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(3), pages 403-423, September.
    2. Tue Gorgens, 2000. "Semiparametric Estimation of Single-Index Transition Intensities," Econometric Society World Congress 2000 Contributed Papers 0596, Econometric Society.
    3. Ingrid Van Keilegom & Noël Veraverbeke, 2001. "Hazard Rate Estimation in Nonparametric Regression with Censored Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(4), pages 730-745, December.
    4. Perch Nielsen, Jens, 2000. "Super-Efficient Prediction Based on High-Quality Marker Information," Finance Working Papers 00-5, University of Aarhus, Aarhus School of Business, Department of Business Studies.

Articles

  1. Christian M. Hafner & Oliver B. Linton & Linqi Wang, 2024. "Dynamic Autoregressive Liquidity (DArLiQ)," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 774-785, April.
    See citations under working paper version above.
  2. Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad‐Díaz & Menachem (Meni) Abudy , 2024. "Nonstandard Errors," Journal of Finance, American Finance Association, vol. 79(3), pages 2339-2390, June.
    • Utz Weitzel & Michael Razen & Sebastian Neussüs & Michael Kirchler & Magnus Johannesson & Juergen Huber & Felix Holzmeister & Anna Dreber & Albert J. Menkveld & Javier Gil-Bazo, 2021. "Non-Standard Errors," Working Papers 1303, Barcelona School of Economics.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," IWH Discussion Papers 11/2021, Halle Institute for Economic Research (IWH).
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neussüs & Michael Razen & Utz Weitzel & Christian T. Brownlees & Javier Gil-Baz, 2021. "Non-standard errors," Economics Working Papers 1807, Department of Economics and Business, Universitat Pompeu Fabra.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Mena, 2021. "Non-Standard Errors," Working Papers 2021:17, Lund University, Department of Economics.
    • Albert J. et al. Menkveld, 2021. "Non-Standard Errors," CESifo Working Paper Series 9453, CESifo.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Post-Print halshs-03500882, HAL.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neus ss & Michael Razen & Utz Weitzel & Edwin Baidoo & Michael Fr mmel & et al, 2021. "Non-Standard Errors," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 21/1032, Ghent University, Faculty of Economics and Business Administration.
    • Francesco Franzoni & Roxana Mihet & Markus Leippold & Per Ostberg & Olivier Scaillet & Norman Schürhoff & Oksana Bashchenko & Nicola Mano & Michele Pelli, 2022. "Non-Standard Errors," Swiss Finance Institute Research Paper Series 22-09, Swiss Finance Institute.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Cambridge Working Papers in Economics 2182, Faculty of Economics, University of Cambridge.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Hasse, Jean-Baptiste & e.a.,, 2023. "Non-Standard Errors," LIDAM Reprints LFIN 2023002, Université catholique de Louvain, Louvain Finance (LFIN).
    • Moinas, Sophie & Declerck, Fany & Menkveld, Albert J. & Dreber, Anna, 2023. "Non-Standard Errors," TSE Working Papers 23-1451, Toulouse School of Economics (TSE).
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüß, Sebastian & Razen, Michael & Weitzel, Utz & Abad-Díaz, David & Abudy, Menac, 2024. "Nonstandard errors," LSE Research Online Documents on Economics 123002, London School of Economics and Political Science, LSE Library.
    • Albert Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad-Díaz & Tobias Adrian & Yacine Ai, 2024. "Nonstandard Errors," Post-Print hal-04676112, HAL.
    • Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Jürgen & Johannesson, Magnus & Kirchler, Michael & Neusüss, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-standard errors," SAFE Working Paper Series 327, Leibniz Institute for Financial Research SAFE.
    • Albert J. Menkveld & Anna Dreber & Felix Holzmeister & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & David Abad-Dí­az & Menachem Abudy & Tobi, 2021. "Non-Standard Errors," Working Papers 2021-31, Faculty of Economics and Statistics, Universität Innsbruck.
    • Gerardo Ferrara & Simon Jurkatis, 2021. "Non-standard errors," Bank of England working papers 955, Bank of England.
    • Albert Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad-Díaz & Tobias Adrian & Yacine Ai, 2024. "Nonstandard Errors," Post-Print hal-05077550, HAL.
    • Albert J Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard & David Abad-Dí, 2021. "Non-Standard Errors," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03500882, HAL.
    • Albert Menkveld & Anna Dreber & Felix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüß & Michael Razen & Utz Weitzel & David Abad-Díaz & Tobias Adrian & Yacine Ai, 2024. "Nonstandard Errors," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-05077550, HAL.
    • Ciril Bosch-Rosa & Bernhard Kassner, 2023. "Non-Standard Errors," Rationality and Competition Discussion Paper Series 385, CRC TRR 190 Rationality and Competition.
    • Menkveld, A. & Dreber, A. & Holzmeister, F. & Huber, J. & Johannesson, M. & Kirchler, M. & Neusüss, S. & Razen, M. & Neusüss, S. & Neusüss, S., 2021. "Non-Standard Errors," Janeway Institute Working Papers 2112, Faculty of Economics, University of Cambridge.
    • Wolff, Christian & Menkveld, Albert J. & Dreber, Anna & Holzmeister, Felix & Huber, Juergen & Johannesson, Magnus & Kirchler, Michael & Neusüess, Sebastian & Razen, Michael & Weitzel, Utz, 2021. "Non-Standard Errors," CEPR Discussion Papers 16751, C.E.P.R. Discussion Papers.
    • Albert J. Menkveld & Anna Dreber & Félix Holzmeister & Juergen Huber & Magnus Johannesson & Michael Kirchler & Sebastian Neusüss & Michael Razen & Utz Weitzel & Gunther Capelle-Blancard, 2021. "Non-Standard Errors," Documents de travail du Centre d'Economie de la Sorbonne 21033, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    See citations under working paper version above.
  3. Cheng, Tingting & Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2024. "GMM estimation for high-dimensional panel data models," Journal of Econometrics, Elsevier, vol. 244(1).
    See citations under working paper version above.
  4. Hong, Yongmiao & Linton, Oliver & McCabe, Brendan & Sun, Jiajing & Wang, Shouyang, 2024. "Kolmogorov–Smirnov type testing for structural breaks: A new adjusted-range based self-normalization approach," Journal of Econometrics, Elsevier, vol. 238(2).
    See citations under working paper version above.
  5. Lee, Kyungho & Linton, Oliver & Whang, Yoon-Jae, 2023. "Testing for time stochastic dominance," Journal of Econometrics, Elsevier, vol. 235(2), pages 352-371.
    See citations under working paper version above.
  6. Ge, Shuyi & Li, Shaoran & Linton, Oliver, 2023. "News-implied linkages and local dependency in the equity market," Journal of Econometrics, Elsevier, vol. 235(2), pages 779-815.

    Cited by:

    1. Marcus Gawronsky & Chun-Sung Huang, 2024. "Continuous Risk Factor Models: Analyzing Asset Correlations through Energy Distance," Papers 2410.23447, arXiv.org.

  7. Dong, Chaohua & Gao, Jiti & Linton, Oliver, 2023. "High dimensional semiparametric moment restriction models," Journal of Econometrics, Elsevier, vol. 232(2), pages 320-345.
    See citations under working paper version above.
  8. Linton, Oliver & Seo, Myung Hwan & Whang, Yoon-Jae, 2023. "Testing stochastic dominance with many conditioning variables," Journal of Econometrics, Elsevier, vol. 235(2), pages 507-527.
    See citations under working paper version above.
  9. Lena Boneva & David Elliott & Iryna Kaminska & Oliver Linton & Nick McLaren & Ben Morley, 2022. "The Impact of Corporate QE on Liquidity: Evidence from the UK," The Economic Journal, Royal Economic Society, vol. 132(648), pages 2615-2643.
    See citations under working paper version above.
  10. Sun, Jiajing & Hong, Yongmiao & Linton, Oliver & Zhao, Xiaolu, 2022. "Adjusted-range self-normalized confidence interval construction for censored dependent data," Economics Letters, Elsevier, vol. 220(C).

    Cited by:

    1. Christis Katsouris, 2023. "Limit Theory under Network Dependence and Nonstationarity," Papers 2308.01418, arXiv.org, revised Aug 2023.

  11. Z. Merrick Li & Oliver Linton, 2022. "A ReMeDI for Microstructure Noise," Econometrica, Econometric Society, vol. 90(1), pages 367-389, January.
    See citations under working paper version above.
  12. Linton, Oliver B. & Tang, Haihan, 2022. "Estimation Of The Kronecker Covariance Model By Quadratic Form," Econometric Theory, Cambridge University Press, vol. 38(5), pages 1014-1067, October.
    See citations under working paper version above.
  13. Ai, Chunrong & Linton, Oliver & Zhang, Zheng, 2022. "Estimation and inference for the counterfactual distribution and quantile functions in continuous treatment models," Journal of Econometrics, Elsevier, vol. 228(1), pages 39-61.

    Cited by:

    1. Zequn Jin & Lihua Lin & Zhengyu Zhang, 2022. "Identification and Auto-debiased Machine Learning for Outcome Conditioned Average Structural Derivatives," Papers 2211.07903, arXiv.org.
    2. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    3. Yu-Chin Hsu & Martin Huber & Yu-Min Yen, 2023. "Doubly Robust Estimation of Direct and Indirect Quantile Treatment Effects with Machine Learning," Papers 2307.01049, arXiv.org.

  14. Gordon Anderson & Oliver Linton & Maria Grazia Pittau & Yoon-Jae Whang & Roberto Zelli, 2021. "On unit free assessment of the extent of multilateral distributional variation," The Econometrics Journal, Royal Economic Society, vol. 24(3), pages 502-518.
    See citations under working paper version above.
  15. Li, Shaoran & Linton, Oliver, 2021. "When will the Covid-19 pandemic peak?," Journal of Econometrics, Elsevier, vol. 220(1), pages 130-157.
    See citations under working paper version above.
  16. Oliver Linton & Yoon Jae Whang & Yu-Min Yen, 2021. "The lower regression function and testing expectation dependence dominance hypotheses," Econometric Reviews, Taylor & Francis Journals, vol. 40(8), pages 709-727, September.
    See citations under working paper version above.
  17. Ma, Shujie & Linton, Oliver & Gao, Jiti, 2021. "Estimation and inference in semiparametric quantile factor models," Journal of Econometrics, Elsevier, vol. 222(1), pages 295-323.
    See citations under working paper version above.
  18. Dong, Chaohua & Linton, Oliver & Peng, Bin, 2021. "A weighted sieve estimator for nonparametric time series models with nonstationary variables," Journal of Econometrics, Elsevier, vol. 222(2), pages 909-932.

    Cited by:

    1. Dong, Chaohua & Chen, Rong & Xiao, Zhijie & Liu, Weiyi, 2024. "Functional quantile autoregression," Journal of Econometrics, Elsevier, vol. 244(2).
    2. Dong, C. & Li, S., 2021. "Specification Lasso and an Application in Financial Markets," Cambridge Working Papers in Economics 2139, Faculty of Economics, University of Cambridge.
    3. Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP69/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Monash Econometrics and Business Statistics Working Papers 18/21, Monash University, Department of Econometrics and Business Statistics.
    5. Wang, Peng & Wang, Xi, 2025. "Adjusted principal component estimation for binary factor model," MPRA Paper 123844, University Library of Munich, Germany.
    6. Jungbin Hwang & Yixiao Sun, 2025. "Asymptotic F and t Tests in Cointegrating Regressions with Asymptotically Homogeneous Functions," Working papers 2025-01, University of Connecticut, Department of Economics.
    7. Difang Huang & Jiti Gao & Tatsushi Oka, 2025. "Semiparametric single-index estimation for average treatment effects," Econometric Reviews, Taylor & Francis Journals, vol. 44(6), pages 843-885, July.
    8. Chaohua Dong & Jiti Gao & Bin Peng & Yundong Tu, 2021. "Multiple-index Nonstationary Time Series Models: Robust Estimation Theory and Practice," Papers 2111.02023, arXiv.org.
    9. Cheng, T. & Dong, C. & Gao, J. & Linton, O., 2022. "GMM Estimation for High-Dimensional Panel Data Models," Cambridge Working Papers in Economics 2245, Faculty of Economics, University of Cambridge.
    10. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.
    11. Lin, Yingqian & Tu, Yundong, 2024. "Functional coefficient cointegration models with Box–Cox transformation," Economics Letters, Elsevier, vol. 234(C).
    12. Peng, Zhen & Dong, Chaohua, 2022. "Augmented cointegrating linear models with possibly strongly correlated stationary and nonstationary regressors," Finance Research Letters, Elsevier, vol. 47(PB).

  19. Escanciano, Juan Carlos & Hoderlein, Stefan & Lewbel, Arthur & Linton, Oliver & Srisuma, Sorawoot, 2021. "Nonparametric Euler Equation Identification And Estimation," Econometric Theory, Cambridge University Press, vol. 37(5), pages 851-891, October.
    See citations under working paper version above.
  20. Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2021. "A unified framework for efficient estimation of general treatment models," Quantitative Economics, Econometric Society, vol. 12(3), pages 779-816, July.
    See citations under working paper version above.
  21. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.
    See citations under working paper version above.
  22. Hafner, Christian M. & Linton, Oliver B. & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," Journal of Econometrics, Elsevier, vol. 217(2), pages 431-470.
    See citations under working paper version above.
  23. Vogt, Michael & Linton, Oliver, 2020. "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, vol. 216(1), pages 305-325.
    See citations under working paper version above.
  24. Hong, Seok Young & Linton, Oliver, 2020. "Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff," Journal of Econometrics, Elsevier, vol. 219(2), pages 389-424.
    See citations under working paper version above.
  25. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.

    Cited by:

    1. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
    2. Masuhr Andreas & Trede Mark, 2023. "Mutual volatility transmission between assets and trading places," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-15.
    3. Tianyi Wang & Sicong Cheng & Fangsheng Yin & Mei Yu, 2022. "Overnight volatility, realized volatility, and option pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(7), pages 1264-1283, July.
    4. Enzo D'Innocenzo & Alessandra Luati & Mario Mazzocchi, 2020. "A Robust Score-Driven Filter for Multivariate Time Series," Papers 2009.01517, arXiv.org, revised Aug 2022.
    5. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    6. Lai, Yu-Sheng, 2025. "Trading-hour and nontrading-hour volatility in crude oil and U.S. dollar markets and its implications for portfolio optimization," Journal of Commodity Markets, Elsevier, vol. 38(C).
    7. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
    8. Insana, Alessandra, 2023. "Betting against beta with intraday and overnight signals," International Review of Financial Analysis, Elsevier, vol. 86(C).
    9. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    10. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.

  26. Gao, Jiti & Linton, Oliver & Peng, Bin, 2020. "Inference On A Semiparametric Model With Global Power Law And Local Nonparametric Trends," Econometric Theory, Cambridge University Press, vol. 36(2), pages 223-249, April.
    See citations under working paper version above.
  27. Lee, Ji Hyung & Linton, Oliver & Whang, Yoon-Jae, 2020. "Quantilograms Under Strong Dependence," Econometric Theory, Cambridge University Press, vol. 36(3), pages 457-487, June.
    See citations under working paper version above.
  28. Ba M. Chu & David T. Jacho-Chávez & Oliver B. Linton, 2020. "Standard Errors for Nonparametric Regression," Econometric Reviews, Taylor & Francis Journals, vol. 39(7), pages 674-690, August.

    Cited by:

    1. Gonçalves, Sílvia & Herrera, Ana María & Kilian, Lutz & Pesavento, Elena, 2024. "State-dependent local projections," Journal of Econometrics, Elsevier, vol. 244(2).
    2. Zhang, Anan & Zheng, Yadi & Huang, Huang & Ding, Ning & Zhang, Chengqian, 2022. "Co-integration theory-based cluster time-varying load optimization control model of regional integrated energy system," Energy, Elsevier, vol. 260(C).

  29. Linton, Oliver & Xiao, Zhijie, 2019. "Efficient estimation of nonparametric regression in the presence of dynamic heteroskedasticity," Journal of Econometrics, Elsevier, vol. 213(2), pages 608-631.
    See citations under working paper version above.
  30. Chen, Jia & Li, Degui & Linton, Oliver, 2019. "A new semiparametric estimation approach for large dynamic covariance matrices with multiple conditioning variables," Journal of Econometrics, Elsevier, vol. 212(1), pages 155-176.
    See citations under working paper version above.
  31. Auld, Tom & Linton, Oliver, 2019. "The behaviour of betting and currency markets on the night of the EU referendum," International Journal of Forecasting, Elsevier, vol. 35(1), pages 371-389.
    See citations under working paper version above.
  32. Jia Chen & Degui Li & Oliver Linton & Zudi Lu, 2018. "Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(522), pages 919-932, April.

    Cited by:

    1. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    2. Wei, Jie & Chen, Hui, 2020. "Determining the number of factors in approximate factor models by twice K-fold cross validation," Economics Letters, Elsevier, vol. 191(C).
    3. Peng, Rong & Lu, Zudi, 2024. "Semiparametric Averaging of Nonlinear Marginal Logistic Regressions and Forecasting for Time Series Classification," Econometrics and Statistics, Elsevier, vol. 31(C), pages 19-37.
    4. Hong, S-Y. & Linton, O., 2018. "Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff," Cambridge Working Papers in Economics 1877, Faculty of Economics, University of Cambridge.
    5. Yongmiao Hong & Tae-Hwy Lee & Yuying Sun & Shouyang Wang & Xinyu Zhang, 2017. "Time-varying Model Averaging," Working Papers 202001, University of California at Riverside, Department of Economics.
    6. De Gooijer, Jan G. & Zerom, Dawit, 2019. "Semiparametric quantile averaging in the presence of high-dimensional predictors," International Journal of Forecasting, Elsevier, vol. 35(3), pages 891-909.
    7. Lin, Boqiang & Xu, Bin, 2019. "How to effectively stabilize China's commodity price fluctuations?," Energy Economics, Elsevier, vol. 84(C).
    8. Haowen Bao & Zongwu Cai & Yuying Sun & Shouyang Wang, 2023. "Penalized Optimal Forecast Combination for Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202514, University of Kansas, Department of Economics, revised May 2025.
    9. Liao, Jun & Wan, Alan T.K. & He, Shuyuan & Zou, Guohua, 2022. "Optimal model averaging for multivariate regression models," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    10. Jia Chen & Degui Li & Oliver Linton, 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Discussion Papers 18/14, Department of Economics, University of York.
    11. Liao, Jun & Zou, Guohua, 2020. "Corrected Mallows criterion for model averaging," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    12. Fang, Fang & Li, Jialiang & Xia, Xiaochao, 2022. "Semiparametric model averaging prediction for dichotomous response," Journal of Econometrics, Elsevier, vol. 229(2), pages 219-245.
    13. Yuying Sun & Shaoxin Hong & Zongwu Cai, 2023. "Optimal Local Model Averaging for Divergent-Dimensional Functional-Coefficient Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202309, University of Kansas, Department of Economics, revised Sep 2023.
    14. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    15. Guo, Chaohui & Lv, Jing & Wu, Jibo, 2021. "Composite quantile regression for ultra-high dimensional semiparametric model averaging," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
    16. Chen, J. & Li, Y. & Linton, O. B., 2025. "Estimation of Large Dynamic Precision Matrices with a Latent Semiparametric Structure," Janeway Institute Working Papers 2514, Faculty of Economics, University of Cambridge.
    17. Jingwen Tu & Hu Yang & Chaohui Guo & Jing Lv, 2021. "Model averaging marginal regression for high dimensional conditional quantile prediction," Statistical Papers, Springer, vol. 62(6), pages 2661-2689, December.
    18. Daouia, Abdelaati & Stupfler, Gilles & Usseglio-Carleve, Antoine, 2022. "Inference for extremal regression with dependent heavy-tailed data," TSE Working Papers 22-1324, Toulouse School of Economics (TSE), revised 29 Aug 2023.
    19. Yuan, Chaoxia & Fang, Fang & Ni, Lyu, 2022. "Mallows model averaging with effective model size in fragmentary data prediction," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    20. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2019. "On the Forecast Combination Puzzle," Econometrics, MDPI, vol. 7(3), pages 1-26, September.
    21. Haowen Bao & Zongwu Cai & Yuying Sun & Shouyang Wang, 2023. "Penalized Model Averaging for High Dimensional Quantile Regressions," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202302, University of Kansas, Department of Economics.
    22. Liao, Jun & Zong, Xianpeng & Zhang, Xinyu & Zou, Guohua, 2019. "Model averaging based on leave-subject-out cross-validation for vector autoregressions," Journal of Econometrics, Elsevier, vol. 209(1), pages 35-60.
    23. De Gooijer Jan G. & Zerom Dawit, 2020. "Penalized Averaging of Parametric and Non-Parametric Quantile Forecasts," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-15, January.

  33. Oliver Linton & Soheil Mahmoodzadeh, 2018. "Implications of High-Frequency Trading for Security Markets," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 237-259, August.
    See citations under working paper version above.
  34. Dong, Chaohua & Linton, Oliver, 2018. "Additive nonparametric models with time variable and both stationary and nonstationary regressors," Journal of Econometrics, Elsevier, vol. 207(1), pages 212-236.
    See citations under working paper version above.
  35. Chen, Xiaohong & Linton, Oliver & Yi, Yanping, 2017. "Semiparametric identification of the bid–ask spread in extended Roll models," Journal of Econometrics, Elsevier, vol. 200(2), pages 312-325.

    Cited by:

    1. Chen, Xiaohong & Linton, Oliver & Schneeberger, Stefan & Yi, Yanping, 2019. "Semiparametric estimation of the bid–ask spread in extended roll models," Journal of Econometrics, Elsevier, vol. 208(1), pages 160-178.
    2. Schennach, Susanne M., 2020. "Mismeasured and unobserved variables," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 487-565, Elsevier.
    3. Jaros{l}aw Duda & Robert Syrek & Henryk Gurgul, 2019. "Modelling bid-ask spread conditional distributions using hierarchical correlation reconstruction," Papers 1911.02361, arXiv.org.

  36. Hafner, Christian M. & Linton, Oliver, 2017. "An Almost Closed Form Estimator For The Egarch Model," Econometric Theory, Cambridge University Press, vol. 33(4), pages 1013-1038, August.
    See citations under working paper version above.
  37. Gordon Anderson & Oliver Linton & Jasmin Thomas, 2017. "Similarity, dissimilarity and exceptionality: generalizing Gini’s transvariation to measure “differentness” in many distributions," METRON, Springer;Sapienza Università di Roma, vol. 75(2), pages 161-180, August.

    Cited by:

    1. Anderson, G. & Linton, O. & Pittau, M G. & Whang, Y-J. & Zelli, R., 2020. "On Unit Free Assessment of The Extent of Multilateral Distributional Variation," Cambridge Working Papers in Economics 20123, Faculty of Economics, University of Cambridge.
    2. Gordon Anderson, Alessio Farcomeni, Maria Grazia Pittau and Roberto Zelli, 2019. "Multidimensional Nation Wellbeing, More Equal yet More Polarized: An Analysis of the Progress of Human Development Since 1990," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 44(1), pages 1-22, March.
    3. Gordon Anderson & Maria Grazia Pittau & Roberto Zelli & Jasmin Thomas, 2018. "Income Inequality, Cohesiveness and Commonality in the Euro Area: A Semi-Parametric Boundary-Free Analysis," Econometrics, MDPI, vol. 6(2), pages 1-20, March.
    4. C.J. O’Donnell, 2025. "Accounting for Environmental Variables and Bad Outputs in DEA," CEPA Working Papers Series WP032025, School of Economics, University of Queensland, Australia.
    5. Gordon Anderson & Tongtong Hao & Maria Grazia Pittau, 2019. "More unequal yet more alike, the changing patterns of family formation, generational mobility and household income inequality in China: a counter-factual analysis," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 17(3), pages 359-378, September.
    6. Gordon Anderson & Jasmin Thomas, 2019. "Measuring Multi-group Polarization, Segmentation and Ambiguity: Increasingly Unequal Yet Similar Constituent Canadian Income Distributions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(3), pages 1001-1032, October.
    7. Gordon Anderson, 2018. "Measuring Aspects of Mobility, Polarization and Convergence in the Absence of Cardinality: Indices Based Upon Transitional Typology," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 139(3), pages 887-907, October.

  38. Michael Vogt & Oliver Linton, 2017. "Classification of non-parametric regression functions in longitudinal data models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 5-27, January.

    Cited by:

    1. Zhongnan Jin & Jie Min & Yili Hong & Pang Du & Qingyu Yang, 2024. "Multivariate Functional Clustering with Variable Selection and Application to Sensor Data from Engineering Systems," INFORMS Joural on Data Science, INFORMS, vol. 3(2), pages 203-218, October.
    2. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2024. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 1026-1040, July.
    3. Zixuan Han & Tao Li & Jinhong You & Narayanaswamy Balakrishnan, 2025. "Individual Homogeneity Learning in Density Data Response Additive Models," Stats, MDPI, vol. 8(3), pages 1-27, August.
    4. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2023. "Inference of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers 5/23, Monash University, Department of Econometrics and Business Statistics.
    5. Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2025. "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Working Papers 202526, University of Macau, Faculty of Business Administration.
    6. Tsubasa Ito & Shonosuke Sugasawa, 2023. "Grouped generalized estimating equations for longitudinal data analysis," Biometrics, The International Biometric Society, vol. 79(3), pages 1868-1879, September.
    7. Zhentao Shi & Liangjun Su & Tian Xie, 2020. "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," Papers 2010.09477, arXiv.org, revised Aug 2022.
    8. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    9. Vogt, Michael & Linton, Oliver, 2020. "Multiscale clustering of nonparametric regression curves," Journal of Econometrics, Elsevier, vol. 216(1), pages 305-325.
    10. Wang, Wei & Xiao, Zhijie & Ren, Yanyan & Yan, Xiaodong, 2023. "A bi-integrative analysis of two-dimensional heterogeneous panel data models," Economics Letters, Elsevier, vol. 230(C).
    11. Liebl, Dominik & Walders, Fabian, 2019. "Parameter regimes in partial functional panel regression," Econometrics and Statistics, Elsevier, vol. 11(C), pages 105-115.
    12. Ge, S. & Li, S. & Linton, O., 2020. "A Dynamic Network of Arbitrage Characteristics," Cambridge Working Papers in Economics 2060, Faculty of Economics, University of Cambridge.
    13. Jia Chen, 2018. "Estimating Latent Group Structure in Time-Varying Coefficient Panel Data Models," Discussion Papers 18/15, Department of Economics, University of York.
    14. Xi Chen & Ye Luo & Martin Spindler, 2019. "Adaptive Discrete Smoothing for High-Dimensional and Nonlinear Panel Data," Papers 1912.12867, arXiv.org, revised Jan 2020.
    15. Bian, Yulin & Su, Liangjun, 2025. "A note on factor models with latent group structures," Economics Letters, Elsevier, vol. 252(C).
    16. Gao, Jiti & Xia, Kai & Zhu, Huanjun, 2020. "Heterogeneous panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 219(2), pages 329-353.
    17. Paul Haimerl & Stephan Smeekes & Ines Wilms, 2025. "Estimation of Latent Group Structures in Time-Varying Panel Data Models," Papers 2503.23165, arXiv.org, revised Nov 2025.
    18. Chengwang Liao & Zhentao Shi & Yapeng Zheng, 2025. "A Relaxation Approach to Synthetic Control," Papers 2508.01793, arXiv.org.
    19. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    20. Pionati, Alessandro, 2025. "Latent grouped structures in panel data: a review," MPRA Paper 123954, University Library of Munich, Germany.

  39. Lena Boneva & Oliver Linton, 2017. "A discrete†choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants of corporate bond issuance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(7), pages 1226-1243, November.

    Cited by:

    1. Francesco Bartolucci & Claudia Pigini & Francesco Valentini, 2024. "MCMC conditional maximum likelihood for the two-way fixed-effects logit," Econometric Reviews, Taylor & Francis Journals, vol. 43(6), pages 379-404, July.
    2. Andrea Zaghini, 2017. "The CSPP at work: yield heterogeneity and the portfolio rebalancing channel," Temi di discussione (Economic working papers) 1157, Bank of Italy, Economic Research and International Relations Area.
    3. Gao, J. & Linton, O. & Peng, B., 2022. "A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation," Janeway Institute Working Papers 2215, Faculty of Economics, University of Cambridge.
    4. Chen, Mingli & Fernández-Val, Iván & Weidner, Martin, 2021. "Nonlinear factor models for network and panel data," Journal of Econometrics, Elsevier, vol. 220(2), pages 296-324.
    5. Eberhardt, Markus, 2018. "(At Least) Four Theories for Sovereign Default," CEPR Discussion Papers 13084, C.E.P.R. Discussion Papers.
    6. Wang, Peng & Wang, Xi, 2025. "Adjusted principal component estimation for binary factor model," MPRA Paper 123844, University Library of Munich, Germany.
    7. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    8. Rodolphe Desbordes & Markus Eberhardt & Mario Larch, 2025. "A democratic dividend in trade? Evidence from a flexible empirical implementation," Discussion Papers 2025-02, University of Nottingham, GEP.
    9. Liang Chen & Minyuan Zhang, 2023. "Common Correlated Effects Estimation of Nonlinear Panel Data Models," Papers 2304.13199, arXiv.org.
    10. Jie Wei & Yonghui Zhang, 2022. "Panel Probit Models with Time‐Varying Individual Effects: Reestimating the Effects of Fertility on Female Labour Participation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 799-829, August.
    11. Qu Feng, 2019. "Common Factors and Common Breaks in Panels: An Empirical Investigation," Economic Growth Centre Working Paper Series 1905, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    12. Feng, Guohua & Peng, Bin & Su, Liangjun & Yang, Thomas Tao, 2019. "Semi-parametric single-index panel data models with interactive fixed effects: Theory and practice," Journal of Econometrics, Elsevier, vol. 212(2), pages 607-622.
    13. De Vos, Ignace & Stauskas, Ovidijus, 2024. "Cross-section bootstrap for CCE regressions," Journal of Econometrics, Elsevier, vol. 240(1).
    14. Ando, Tomohiro & Bai, Jushan & Li, Kunpeng, 2022. "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 230(1), pages 20-38.
    15. Ando, Tomohiro & Bai, Jushan, 2021. "Large-scale generalized linear longitudinal data models with grouped patterns of unobserved heterogeneity," MPRA Paper 111431, University Library of Munich, Germany.
    16. Williams, Benjamin, 2020. "Nonparametric identification of discrete choice models with lagged dependent variables," Journal of Econometrics, Elsevier, vol. 215(1), pages 286-304.
    17. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    18. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    19. Jiti Gao & Fei Liu & Bin peng, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Monash Econometrics and Business Statistics Working Papers 44/20, Monash University, Department of Econometrics and Business Statistics.
    20. Ye, Xiaoqing & Xu, Juan & Wu, Xiangjun, 2018. "Estimation of an unbalanced panel data Tobit model with interactive effects," Journal of choice modelling, Elsevier, vol. 28(C), pages 108-123.
    21. Mugnier, Martin & Wang, Ao, 2024. "Fixed Effects Nonlinear Panel Models with Heterogeneous Slopes : Identification and Consistency," The Warwick Economics Research Paper Series (TWERPS) 1531, University of Warwick, Department of Economics.
    22. Nicola Borri & Denis Chetverikov & Yukun Liu & Aleh Tsyvinski, 2024. "One Factor to Bind the Cross-Section of Returns," NBER Working Papers 32365, National Bureau of Economic Research, Inc.
    23. Mugnier, Martin & Wang, Ao, 2022. "Identification and (Fast) Estimation of Large Nonlinear Panel Models with Two-Way Fixed Effects," The Warwick Economics Research Paper Series (TWERPS) 1422, University of Warwick, Department of Economics.
    24. Mr. Markus Eberhardt & Mr. Andrea F Presbitero, 2018. "Commodity Price Movements and Banking Crises," IMF Working Papers 2018/153, International Monetary Fund.
    25. Rachel Cho & Rodolphe Desbordes & Markus Eberhardt, 2022. "The causal effects of the darker side of financial development," Discussion Papers 2022-04, University of Nottingham, GEP.
    26. Rodolphe Desbordes & Markus Eberhardt, 2019. "Gravity," Discussion Papers 2019-02, University of Nottingham, GEP.
    27. Lee, Yoonseok & Sul, Donggyu, 2023. "Depth-weighted means of noisy data: An application to estimating the average effect in heterogeneous panels," Journal of Multivariate Analysis, Elsevier, vol. 196(C).
    28. Chen, Jia & Shin, Yongcheol & Zheng, Chaowen, 2022. "Estimation and inference in heterogeneous spatial panels with a multifactor error structure," Journal of Econometrics, Elsevier, vol. 229(1), pages 55-79.

  40. Chen, Xiaohong & Jacho-Chávez, David T. & Linton, Oliver, 2016. "Averaging Of An Increasing Number Of Moment Condition Estimators," Econometric Theory, Cambridge University Press, vol. 32(1), pages 30-70, February.

    Cited by:

    1. Frank Windmeijer, 2019. "Two-stage least squares as minimum distance," The Econometrics Journal, Royal Economic Society, vol. 22(1), pages 1-9.
    2. Linton, O. & Xiao, Z., 2019. "Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity," Cambridge Working Papers in Economics 1907, Faculty of Economics, University of Cambridge.
    3. Cizek, P. & Lei, J., 2013. "Identification and Estimation of Nonseparable Single-Index Models in Panel Data with Correlated Random Effects," Other publications TiSEM 73e394eb-6799-4c79-af23-8, Tilburg University, School of Economics and Management.
    4. Matthew Harding & Carlos Lamarche & Chris Muris, 2022. "Estimation of a Factor-Augmented Linear Model with Applications Using Student Achievement Data," Papers 2203.03051, arXiv.org.
    5. Boneva, L. & Linton, O., 2017. "A Discrete Choice Model For Large Heterogeneous Panels with Interactive Fixed Effects with an Application to the Determinants of Corporate Bond Issuance," Cambridge Working Papers in Economics 1703, Faculty of Economics, University of Cambridge.
    6. S. Boragan Aruoba & Ronel Elul & Sebnem Kalemli Ozcan, 2022. "Housing Wealth and Consumption: The Role of Heterogeneous Credit Constraints," Working Papers 22-34, Federal Reserve Bank of Philadelphia.
    7. Chaudhuri, Saraswata & Renault, Eric, 2023. "Efficient estimation of regression models with user-specified parametric model for heteroskedasticty," The Warwick Economics Research Paper Series (TWERPS) 1473, University of Warwick, Department of Economics.
    8. Yoonseok Lee & Yu Zhou, 2015. "Averaged Instrumental Variables Estimators," Center for Policy Research Working Papers 180, Center for Policy Research, Maxwell School, Syracuse University.
    9. Mengli Zhang & Yang Bai, 2021. "On the use of repeated measurement errors in linear regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(5), pages 779-803, July.
    10. Zhu, Qianqian & Zheng, Yao & Li, Guodong, 2018. "Linear double autoregression," Journal of Econometrics, Elsevier, vol. 207(1), pages 162-174.

  41. Han, Heejoon & Linton, Oliver & Oka, Tatsushi & Whang, Yoon-Jae, 2016. "The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series," Journal of Econometrics, Elsevier, vol. 193(1), pages 251-270.
    See citations under working paper version above.
  42. Linton, Oliver & Whang, Yoon-Jae & Yen, Yu-Min, 2016. "A nonparametric test of a strong leverage hypothesis," Journal of Econometrics, Elsevier, vol. 194(1), pages 153-186.
    See citations under working paper version above.
  43. Chen, Jia & Li, Degui & Linton, Oliver & Lu, Zudi, 2016. "Semiparametric dynamic portfolio choice with multiple conditioning variables," Journal of Econometrics, Elsevier, vol. 194(2), pages 309-318.
    See citations under working paper version above.
  44. Park, Sujin & Hong, Seok Young & Linton, Oliver, 2016. "Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error," Journal of Econometrics, Elsevier, vol. 191(2), pages 325-347.

    Cited by:

    1. Jianqing Fan & Donggyu Kim & Minseok Shin & Yazhen Wang, 2024. "Factor and Idiosyncratic VAR-Ito Volatility Models for Heavy-Tailed High-Frequency Financial Data," Working Papers 202415, University of California at Riverside, Department of Economics.
    2. Bu, R. & Li, D. & Linton, O. & Wang, H., 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Janeway Institute Working Papers 2208, Faculty of Economics, University of Cambridge.
    3. Hafner, Christian & Linton, Oliver & Tang, Haihan, 2020. "Estimation of a multiplicative correlation structure in the large dimensional case," LIDAM Reprints ISBA 2020028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Jianqing Fan & Donggyu Kim & Minseok Shin, 2024. "Adaptive Robust Large Volatility Matrix Estimation Based on High-Frequency Financial Data," Working Papers 202419, University of California at Riverside, Department of Economics.
    5. Shin, Minseok & Kim, Donggyu & Fan, Jianqing, 2023. "Adaptive robust large volatility matrix estimation based on high-frequency financial data," Journal of Econometrics, Elsevier, vol. 237(1).
    6. Fan, Jianqing & Kim, Donggyu, 2019. "Structured volatility matrix estimation for non-synchronized high-frequency financial data," Journal of Econometrics, Elsevier, vol. 209(1), pages 61-78.
    7. Richard Y. Chen, 2019. "The Fourier Transform Method for Volatility Functional Inference by Asynchronous Observations," Papers 1911.02205, arXiv.org.
    8. Cui, Wenhao & Hu, Jie & Wang, Jiandong, 2024. "Nonparametric estimation for high-frequency data incorporating trading information," Journal of Econometrics, Elsevier, vol. 240(1).
    9. Maria Elvira Mancino & Tommaso Mariotti & Giacomo Toscano, 2022. "Asymptotic Normality for the Fourier spot volatility estimator in the presence of microstructure noise," Papers 2209.08967, arXiv.org.
    10. Markus Bibinger & Per A. Mykland, 2016. "Inference for Multi-dimensional High-frequency Data with an Application to Conditional Independence Testing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(4), pages 1078-1102, December.
    11. Mykland, Per A. & Zhang, Lan & Chen, Dachuan, 2019. "The algebra of two scales estimation, and the S-TSRV: High frequency estimation that is robust to sampling times," Journal of Econometrics, Elsevier, vol. 208(1), pages 101-119.

  45. Linton, Oliver & Wang, Qiying, 2016. "Nonparametric Transformation Regression With Nonstationary Data," Econometric Theory, Cambridge University Press, vol. 32(1), pages 1-29, February.
    See citations under working paper version above.
  46. Linton, Oliver & Smetanina, Ekaterina, 2016. "Testing the martingale hypothesis for gross returns," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 664-689.

    Cited by:

    1. Andrey Shternshis & Piero Mazzarisi & Stefano Marmi, 2022. "Efficiency of the Moscow Stock Exchange before 2022," Papers 2207.10476, arXiv.org, revised Jul 2022.

  47. Lena Boneva & Oliver Linton & Michael Vogt, 2016. "The Effect of Fragmentation in Trading on Market Quality in the UK Equity Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 192-213, January.
    See citations under working paper version above.
  48. Koo, Bonsoo & Linton, Oliver, 2015. "Let’S Get Lade: Robust Estimation Of Semiparametric Multiplicative Volatility Models," Econometric Theory, Cambridge University Press, vol. 31(4), pages 671-702, August.
    See citations under working paper version above.
  49. Boneva, Lena & Linton, Oliver & Vogt, Michael, 2015. "A semiparametric model for heterogeneous panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 327-345.
    See citations under working paper version above.
  50. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.

    Cited by:

    1. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    2. Kotlyarova, Yulia & Schafgans, Marcia M.A. & Zinde-Walsh, Victoria, 2021. "Rates of expansions for functional estimators," LSE Research Online Documents on Economics 113436, London School of Economics and Political Science, LSE Library.
    3. Peng, Rong & Lu, Zudi, 2024. "Semiparametric Averaging of Nonlinear Marginal Logistic Regressions and Forecasting for Time Series Classification," Econometrics and Statistics, Elsevier, vol. 31(C), pages 19-37.
    4. Jia Chen & Degui Li & Oliver Linton & Zudi Lu, 2015. "Semiparametric dynamic portfolio choice with multiple conditioning variables," CeMMAP working papers CWP07/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Zhang, Xinyu & Ullah, Aman & Zhao, Shangwei, 2016. "On the dominance of Mallows model averaging estimator over ordinary least squares estimator," Economics Letters, Elsevier, vol. 142(C), pages 69-73.
    6. De Gooijer, Jan G. & Zerom, Dawit, 2019. "Semiparametric quantile averaging in the presence of high-dimensional predictors," International Journal of Forecasting, Elsevier, vol. 35(3), pages 891-909.
    7. Zishu Zhan & Yang Li & Yuhong Yang & Cunjie Lin, 2023. "Model averaging for semiparametric varying coefficient quantile regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(4), pages 649-681, August.
    8. Yulia Kotlyarova & Marcia M. A. Schafgans & Victoria Zinde-Walsh, 2022. "Correction to: Rates of Expansions for Functional Estimators," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(2), pages 487-487, June.
    9. Aman Ullah & Xinyu Zhang, 2015. "Grouped Model Averaging for Finite Sample Size," Working Papers 201501, University of California at Riverside, Department of Economics.
    10. Jia Chen & Degui Li & Oliver Linton, 2018. "A New Semiparametric Estimation Approach for Large Dynamic Covariance Matrices with Multiple Conditioning Variables," Discussion Papers 18/14, Department of Economics, University of York.
    11. Tao Huang & Jialiang Li, 2018. "Semiparametric model average prediction in panel data analysis," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 125-144, January.
    12. Fang, Fang & Li, Jialiang & Xia, Xiaochao, 2022. "Semiparametric model averaging prediction for dichotomous response," Journal of Econometrics, Elsevier, vol. 229(2), pages 219-245.
    13. Jia Chen & Degui Li & Oliver Linton & Zudi Lu, 2015. "Semiparametric model averaging of ultra-high dimensional time series," CeMMAP working papers 62/15, Institute for Fiscal Studies.
    14. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    15. Guo, Chaohui & Lv, Jing & Wu, Jibo, 2021. "Composite quantile regression for ultra-high dimensional semiparametric model averaging," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
    16. Fang, Fang & Yu, Zhou, 2020. "Model averaging assisted sufficient dimension reduction," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    17. Chen, J. & Li, Y. & Linton, O. B., 2025. "Estimation of Large Dynamic Precision Matrices with a Latent Semiparametric Structure," Janeway Institute Working Papers 2514, Faculty of Economics, University of Cambridge.
    18. Tu, Yundong & Yi, Yanping, 2017. "Forecasting cointegrated nonstationary time series with time-varying variance," Journal of Econometrics, Elsevier, vol. 196(1), pages 83-98.
    19. Jingwen Tu & Hu Yang & Chaohui Guo & Jing Lv, 2021. "Model averaging marginal regression for high dimensional conditional quantile prediction," Statistical Papers, Springer, vol. 62(6), pages 2661-2689, December.
    20. Michele Battisti & Massimo Del Gatto & Christopher F. Parmeter, 2018. "Labor productivity growth: disentangling technology and capital accumulation," Journal of Economic Growth, Springer, vol. 23(1), pages 111-143, March.
    21. Tommaso Proietti & Alessandro Giovannelli, 2020. "Nowcasting Monthly GDP with Big Data: a Model Averaging Approach," CEIS Research Paper 482, Tor Vergata University, CEIS, revised 12 May 2020.
    22. Jialiang Li & Tonghui Yu & Jing Lv & Mei‐Ling Ting Lee, 2021. "Semiparametric model averaging prediction for lifetime data via hazards regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1187-1209, November.
    23. Yuan, Chaoxia & Fang, Fang & Ni, Lyu, 2022. "Mallows model averaging with effective model size in fragmentary data prediction," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    24. Xiaochao Xia, 2021. "Model averaging prediction for nonparametric varying-coefficient models with B-spline smoothing," Statistical Papers, Springer, vol. 62(6), pages 2885-2905, December.

  51. Oliver Linton & Thierry Post & Yoon‐Jae Whang, 2014. "Testing for the stochastic dominance efficiency of a given portfolio," Econometrics Journal, Royal Economic Society, vol. 17(2), pages 59-74, June.
    See citations under working paper version above.
  52. Michael Vogt & Oliver Linton, 2014. "Nonparametric estimation of a periodic sequence in the presence of a smooth trend," Biometrika, Biometrika Trust, vol. 101(1), pages 121-140.
    See citations under working paper version above.
  53. Battey, Heather & Linton, Oliver, 2014. "Nonparametric estimation of multivariate elliptic densities via finite mixture sieves," Journal of Multivariate Analysis, Elsevier, vol. 123(C), pages 43-67.
    See citations under working paper version above.
  54. Oliver Linton & Pedro Gozalo, 2014. "Testing Conditional Independence Restrictions," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 523-552, August.

    Cited by:

    1. Yu-Chin Hsu & Ta-Cheng Huang & Haiqing Xu, 2018. "Testing for Unobserved Heterogeneous Treatment Effects with Observational Data," Papers 1803.07514, arXiv.org, revised Aug 2021.
    2. Dai, Shengtao & Song, Xiaojun, 2025. "Consistent tests for semiparametric conditional independence," Statistics & Probability Letters, Elsevier, vol. 216(C).
    3. Wang, Hongfei & Liu, Binghui & Feng, Long & Ma, Yanyuan, 2024. "Rank-based max-sum tests for mutual independence of high-dimensional random vectors," Journal of Econometrics, Elsevier, vol. 238(1).
    4. Su, Liangjun & Zheng, Xin, 2017. "A martingale-difference-divergence-based test for specification," Economics Letters, Elsevier, vol. 156(C), pages 162-167.
    5. Xiaojun Song & Haoyu Wei, 2021. "Nonparametric Tests of Conditional Independence for Time Series," Papers 2110.04847, arXiv.org.
    6. Ai, Chunrong & Sun, Li-Hsien & Zhang, Zheng & Zhu, Liping, 2024. "Testing unconditional and conditional independence via mutual information," Journal of Econometrics, Elsevier, vol. 240(2).
    7. Xuehu Zhu & Jun Lu & Jun Zhang & Lixing Zhu, 2021. "Testing for conditional independence: A groupwise dimension reduction‐based adaptive‐to‐model approach," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(2), pages 549-576, June.

  55. Linton, Oliver & Xiao, Zhijie, 2013. "Estimation Of And Inference About The Expected Shortfall For Time Series With Infinite Variance," Econometric Theory, Cambridge University Press, vol. 29(4), pages 771-807, August.

    Cited by:

    1. Steven Kou & Xianhua Peng, 2014. "On the Measurement of Economic Tail Risk," Papers 1401.4787, arXiv.org, revised Aug 2015.
    2. Chen, An & Nguyen, Thai & Stadje, Mitja, 2018. "Optimal investment under VaR-Regulation and Minimum Insurance," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 194-209.
    3. Trapani, Lorenzo, 2016. "Testing for (in)finite moments," Journal of Econometrics, Elsevier, vol. 191(1), pages 57-68.
    4. Xu, Ke-Li, 2020. "Inference of local regression in the presence of nuisance parameters," Journal of Econometrics, Elsevier, vol. 218(2), pages 532-560.
    5. Le-Yu Chen & Yu-Min Yen, 2021. "Estimations of the Local Conditional Tail Average Treatment Effect," Papers 2109.08793, arXiv.org, revised May 2024.
    6. Yuri Goegebeur & Armelle Guillou & Jing Qin, 2024. "Estimation of the conditional tail moment for Weibull‐type distributions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 51(4), pages 1782-1815, December.
    7. Oliver Linton & YOON-JAE WHANG & Yu-Min Yen, 2018. "The Lower Regression Function and Testing Expectation Dependence Dominance Hypotheses," Working Paper Series no110, Institute of Economic Research, Seoul National University.
    8. Catania, Leopoldo & Luati, Alessandra, 2025. "Quasi Maximum Likelihood Estimation of Value at Risk and Expected Shortfall," Econometrics and Statistics, Elsevier, vol. 33(C), pages 23-34.
    9. Steven Kou & Xianhua Peng, 2016. "On the Measurement of Economic Tail Risk," Operations Research, INFORMS, vol. 64(5), pages 1056-1072, October.
    10. Gery Geenens & Richard Dunn, 2017. "A nonparametric copula approach to conditional Value-at-Risk," Papers 1712.05527, arXiv.org, revised Oct 2019.
    11. Daouia, Abdelaati & Stupfler, Gilles & Usseglio-Carleve, Antoine, 2022. "Inference for extremal regression with dependent heavy-tailed data," TSE Working Papers 22-1324, Toulouse School of Economics (TSE), revised 29 Aug 2023.
    12. Hill, Jonathan B. & Prokhorov, Artem, 2016. "GEL estimation for heavy-tailed GARCH models with robust empirical likelihood inference," Journal of Econometrics, Elsevier, vol. 190(1), pages 18-45.
    13. Geenens, Gery & Dunn, Richard, 2022. "A nonparametric copula approach to conditional Value-at-Risk," Econometrics and Statistics, Elsevier, vol. 21(C), pages 19-37.
    14. Juan Carlos Escanciano, 2020. "Uniform Rates for Kernel Estimators of Weakly Dependent Data," Papers 2005.09951, arXiv.org.
    15. Tomasz Olma, 2021. "Nonparametric Estimation of Truncated Conditional Expectation Functions," Papers 2109.06150, arXiv.org.

  56. Kong, Efang & Linton, Oliver & Xia, Yingcun, 2013. "Global Bahadur Representation For Nonparametric Censored Regression Quantiles And Its Applications," Econometric Theory, Cambridge University Press, vol. 29(5), pages 941-968, October.
    See citations under working paper version above.
  57. Gordon Anderson & Oliver Linton & Teng Leo, 2012. "A polarization-cohesion perspective on cross-country convergence," Journal of Economic Growth, Springer, vol. 17(1), pages 49-69, March.

    Cited by:

    1. Gordon Anderson, Alessio Farcomeni, Maria Grazia Pittau and Roberto Zelli, 2019. "Multidimensional Nation Wellbeing, More Equal yet More Polarized: An Analysis of the Progress of Human Development Since 1990," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 44(1), pages 1-22, March.
    2. Davide Fiaschi & Andrea Mario Lavezzi & Angela Parenti, 2013. "On the Determinants of Distribution Dynamics," Discussion Papers 2013/165, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    3. Thanasis Stengos & M. Ege Yazgan & Harun Özkan, 2018. "Persistence In Convergence And Club Formation," Bulletin of Economic Research, Wiley Blackwell, vol. 70(2), pages 119-138, April.
    4. Khan, Haider & Schettino, Francesco & Gabriele, Alberto, 2017. "Polarization and the Middle Class in China: a Non-Parametric Evaluation Using CHNS and CHIP Data," MPRA Paper 85555, University Library of Munich, Germany.
    5. Fiaschi, Davide & Gianmoena, Lisa & Parenti, Angela, 2018. "Spatial club dynamics in European regions," Regional Science and Urban Economics, Elsevier, vol. 72(C), pages 115-130.
    6. Breinlich, Holger & Ottaviano, Gianmarco I P & Temple, Jonathan R, 2013. "Regional Growth and Regional Decline," Economics Discussion Papers 8977, University of Essex, Department of Economics.
    7. Clementi, F. & Schettino, F., 2013. "Income polarization in Brazil, 2001-2011: A distributional analysis using PNAD data," 2013 Second Congress, June 6-7, 2013, Parma, Italy 149891, Italian Association of Agricultural and Applied Economics (AIEAA).
    8. Christophe Muller, 2017. "Ethnic Horizontal Inequity in Indonesia," AMSE Working Papers 1715, Aix-Marseille School of Economics, France.
    9. F. Clementi & A. L. Dabalen & V. Molini & F. Schettino, 2017. "When the Centre Cannot Hold: Patterns of Polarization in Nigeria," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(4), pages 608-632, December.
    10. Gordon Anderson & Alessio Farcomeni & Grazia Pittau & Roberto Zelli, 2014. "A new approach to measuring and studying the characteristics of class membership: The progress of poverty, inequality and polarization of income classes in urban China," Working Papers tecipa-521, University of Toronto, Department of Economics.
    11. Khan, Haider & Schettino, Francesco, 2018. "Income Polarization in the USA (1983-2016): what happened to the middle class?," MPRA Paper 85554, University Library of Munich, Germany.
    12. Gordon Anderson & Maria Pittau & Roberto Zelli, 2014. "Poverty status probability: a new approach to measuring poverty and the progress of the poor," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(4), pages 469-488, December.
    13. Anderson, Gordon & Farcomeni, Alessio & Pittau, Maria Grazia & Zelli, Roberto, 2016. "A new approach to measuring and studying the characteristics of class membership: Examining poverty, inequality and polarization in urban China," Journal of Econometrics, Elsevier, vol. 191(2), pages 348-359.
    14. Park, Seonyoung & Shin, Donggyun, 2020. "Recent Changes in the Nature of Distribution Dynamics of US County Incomes," Working Paper Series 20926, Victoria University of Wellington, School of Economics and Finance.
    15. Davide Fiaschi & Lisa Gianmoena & Angela Parenti, 2015. "Spatial Clubs in European Regions," Discussion Papers 2015/196, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    16. Gordon Anderson & Teng Wah Leo, 2014. "Ranking Alternative Non-Combinable Prospects: A Stochastic Dominance Based Route to the Second Best Solution," Working Papers tecipa-520, University of Toronto, Department of Economics.
    17. Schettino, Francesco & Khan, Haider A., 2020. "Income polarization in the USA: What happened to the middle class in the last few decades?," Structural Change and Economic Dynamics, Elsevier, vol. 53(C), pages 149-161.
    18. Gordon Anderson, 2018. "Measuring Aspects of Mobility, Polarization and Convergence in the Absence of Cardinality: Indices Based Upon Transitional Typology," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 139(3), pages 887-907, October.
    19. Christophe Muller, 2016. "Ethnic inequality and community activities in Indonesia," WIDER Working Paper Series wp-2016-170, World Institute for Development Economic Research (UNU-WIDER).

  58. Anderson, Gordon & Linton, Oliver & Whang, Yoon-Jae, 2012. "Nonparametric estimation and inference about the overlap of two distributions," Journal of Econometrics, Elsevier, vol. 171(1), pages 1-23.

    Cited by:

    1. Anderson, G. & Linton, O. & Pittau, M G. & Whang, Y-J. & Zelli, R., 2020. "On Unit Free Assessment of The Extent of Multilateral Distributional Variation," Cambridge Working Papers in Economics 20123, Faculty of Economics, University of Cambridge.
    2. Sokbae (Simon) Lee & Kyungchui (Kevin) Song & Yoon-Jae Whang, 2014. "Testing for a general class of functional inequalities," CeMMAP working papers CWP09/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Liu, Shen & Maharaj, Elizabeth Ann & Inder, Brett, 2014. "Polarization of forecast densities: A new approach to time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 345-361.
    4. Toru Kitagawa, 2013. "A bootstrap test for instrument validity in heterogeneous treatment effect models," CeMMAP working papers 53/13, Institute for Fiscal Studies.
    5. Beare, Brendan K. & Shi, Xiaoxia, 2019. "An improved bootstrap test of density ratio ordering," Econometrics and Statistics, Elsevier, vol. 10(C), pages 9-26.
    6. Lee, Sokbae & Song, Kyungchul & Whang, Yoon-Jae, 2013. "Testing functional inequalities," Journal of Econometrics, Elsevier, vol. 172(1), pages 14-32.
    7. Gordon Anderson & Oliver Linton & Jasmin Thomas, 2017. "Similarity, dissimilarity and exceptionality: generalizing Gini’s transvariation to measure “differentness” in many distributions," METRON, Springer;Sapienza Università di Roma, vol. 75(2), pages 161-180, August.
    8. Maribel Jiménez & M�nica Jim�nez, 2019. "Intergenerational educational mobility in Latin America. An analysis from the equal opportunity approach," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, vol. 38(76), pages 289-330.
    9. Gordon Anderson & Alessio Farcomeni & Grazia Pittau & Roberto Zelli, 2014. "A new approach to measuring and studying the characteristics of class membership: The progress of poverty, inequality and polarization of income classes in urban China," Working Papers tecipa-521, University of Toronto, Department of Economics.
    10. Gordon Anderson & Teng Leo & Robert Muelhaupt, 2014. "Measuring Advances in Equality of Opportunity: The Changing Gender Gap in Educational Attainment in Canada in the Last Half Century," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 119(1), pages 73-99, October.
    11. Wang, Dan & Tian, Lili, 2017. "Parametric methods for confidence interval estimation of overlap coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 12-26.
    12. Gerard, François & Rothe, Christoph & Rokkanen, Miikka, 2016. "Bounds on Treatment Effects in Regression Discontinuity Designs under Manipulation of the Running Variable, with an Application," CEPR Discussion Papers 11668, C.E.P.R. Discussion Papers.
    13. Dahl, Christian M. & Huber, Martin & Mellace, Giovanni, 2017. "It's never too LATE: A new look at local average treatment effects with or without defiers," Discussion Papers on Economics 2/2017, University of Southern Denmark, Department of Economics.
    14. Gordon Anderson & Maria Pittau & Roberto Zelli, 2014. "Poverty status probability: a new approach to measuring poverty and the progress of the poor," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(4), pages 469-488, December.
    15. Anderson, Gordon & Farcomeni, Alessio & Pittau, Maria Grazia & Zelli, Roberto, 2016. "A new approach to measuring and studying the characteristics of class membership: Examining poverty, inequality and polarization in urban China," Journal of Econometrics, Elsevier, vol. 191(2), pages 348-359.
    16. Gordon Anderson & Maria Grazia Pittau & Roberto Zelli, 2020. "Measuring the progress of equality of educational opportunity in absence of cardinal comparability," METRON, Springer;Sapienza Università di Roma, vol. 78(2), pages 155-174, August.
    17. Anderson, Gordon & Fu, Rui & Leo, Teng Wah, 2022. "Health, loneliness and the ageing process in the absence of cardinal measure: Rendering intangibles tangible," The Journal of the Economics of Ageing, Elsevier, vol. 22(C).
    18. Seo, Juwon, 2018. "Tests of stochastic monotonicity with improved power," Journal of Econometrics, Elsevier, vol. 207(1), pages 53-70.
    19. Anderson, Gordon & Leo, Teng Wah, 2013. "An empirical examination of matching theories: The one child policy, partner choice and matching intensity in urban China," Journal of Comparative Economics, Elsevier, vol. 41(2), pages 468-489.
    20. Toru Kitagawa, 2013. "A bootstrap test for instrument validity in heterogeneous treatment effect models," CeMMAP working papers CWP53/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    21. Maria Grazia Pittau & Roberto Zelli, 2017. "At the roots of Gini’s transvariation: extracts from “Il concetto di transvariazione e le sue prime applicazioni”," METRON, Springer;Sapienza Università di Roma, vol. 75(2), pages 127-140, August.
    22. Chemeris, Anna & Liu, Yong & Ker, Alan P., 2022. "Insurance subsidies, climate change, and innovation: Implications for crop yield resiliency," Food Policy, Elsevier, vol. 108(C).
    23. Gordon Anderson, 2023. "Has Canada's 21st‐Century Grand Gender Convergence Stalled? Male and Female Income and Human Resource Stock Distributions Viewed Through an Equal Opportunity Lens," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(4), pages 907-930, December.
    24. François Gerard & Miikka Rokkanen & Christoph Rothe, 2020. "Bounds on treatment effects in regression discontinuity designs with a manipulated running variable," Quantitative Economics, Econometric Society, vol. 11(3), pages 839-870, July.
    25. Claudia Noack, 2021. "Sensitivity of LATE Estimates to Violations of the Monotonicity Assumption," Papers 2106.06421, arXiv.org.

  59. Srisuma, Sorawoot & Linton, Oliver, 2012. "Semiparametric estimation of Markov decision processes with continuous state space," Journal of Econometrics, Elsevier, vol. 166(2), pages 320-341.
    See citations under working paper version above.
  60. Koo, Bonsoo & Linton, Oliver, 2012. "Estimation of semiparametric locally stationary diffusion models," Journal of Econometrics, Elsevier, vol. 170(1), pages 210-233.

    Cited by:

    1. Chaohua Dong & Oliver Linton, 2017. "Additive nonparametric models with time variable and both stationary and nonstationary regressions," CeMMAP working papers 59/17, Institute for Fiscal Studies.
    2. Boonsoo Koo & Myung Hwan Seo, 2013. "Structural-break models under mis-specification: implications for forecasting," Monash Econometrics and Business Statistics Working Papers 11/13, Monash University, Department of Econometrics and Business Statistics.
    3. Jia Chen & Degui Li & Yuning Li & Oliver Linton, 2023. "Estimating Time-Varying Networks for High-Dimensional Time Series," Papers 2302.02476, arXiv.org.
    4. David T. Frazier & Bonsoo Koo, 2020. "Indirect Inference for Locally Stationary Models," Monash Econometrics and Business Statistics Working Papers 30/20, Monash University, Department of Econometrics and Business Statistics.
    5. Likai Chen & Ekaterina Smetanina & Wei Biao Wu, 2022. "Estimation of nonstationary nonparametric regression model with multiplicative structure [Income and wealth distribution in macroeconomics: A continuous-time approach]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 176-214.
    6. Koo, Bonsoo & Linton, Oliver, 2015. "Let’S Get Lade: Robust Estimation Of Semiparametric Multiplicative Volatility Models," Econometric Theory, Cambridge University Press, vol. 31(4), pages 671-702, August.
    7. Koo, B. & La Vecchia, D. & Linton, O., 2019. "Nonparametric Recovery of the Yield Curve Evolution from Cross-Section and Time Series Information," Cambridge Working Papers in Economics 1916, Faculty of Economics, University of Cambridge.
    8. Mohammadi, Neda & Santoro, Leonardo V. & Panaretos, Victor M., 2024. "Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective," Stochastic Processes and their Applications, Elsevier, vol. 167(C).
    9. Frazier, David T. & Koo, Bonsoo, 2021. "Indirect inference for locally stationary models," Journal of Econometrics, Elsevier, vol. 223(1), pages 1-27.
    10. Li, Haiqi & Zhou, Jin & Hong, Yongmiao, 2024. "Estimating and testing for smooth structural changes in moment condition models," Journal of Econometrics, Elsevier, vol. 246(1).
    11. Ruijun Bu & Jihyun Kim & Bin Wang, 2020. "Uniform and Lp Convergences of Nonparametric Estimation for Diffusion Models," Working Papers 202021, University of Liverpool, Department of Economics.
    12. Koo, Bonsoo & La Vecchia, Davide & Linton, Oliver, 2021. "Estimation of a nonparametric model for bond prices from cross-section and time series information," Journal of Econometrics, Elsevier, vol. 220(2), pages 562-588.
    13. Bu, Ruijun & Kim, Jihyun & Wang, Bin, 2023. "Uniform and Lp convergences for nonparametric continuous time regressions with semiparametric applications," Journal of Econometrics, Elsevier, vol. 235(2), pages 1934-1954.

  61. Gregory Connor & Matthias Hagmann & Oliver Linton, 2012. "Efficient Semiparametric Estimation of the Fama–French Model and Extensions," Econometrica, Econometric Society, vol. 80(2), pages 713-754, March.

    Cited by:

    1. Zhang, Lyuou & Zhou, Wen & Wang, Haonan, 2021. "A semiparametric latent factor model for large scale temporal data with heteroscedasticity," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    2. Alain-Philippe Fortin & Patrick Gagliardini & Olivier Scaillet, 2022. "Eigenvalue tests for the number of latent factors in short panels," Papers 2210.16042, arXiv.org.
    3. Kunpeng Li & Qi Li & Lina Lu, 2018. "Quasi Maximum Likelihood Analysis of High Dimensional Constrained Factor Models," Supervisory Research and Analysis Working Papers RPA 18-2, Federal Reserve Bank of Boston.
    4. Chaohua Dong & Jiti Gao & Oliver Linton, 2018. "High dimensional semiparametric moment restriction models," CeMMAP working papers CWP69/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Sainan Jin & Liangjun Su & Yonghui Zhang, 2015. "Nonparametric testing for anomaly effects in empirical asset pricing models," Empirical Economics, Springer, vol. 48(1), pages 9-36, February.
    6. Jaeheon Jung, 2019. "Estimating a Large Covariance Matrix in Time-varying Factor Models," Papers 1910.11965, arXiv.org.
    7. Jahn, Malte, 2020. "Artificial neural network regression models in a panel setting: Predicting economic growth," Economic Modelling, Elsevier, vol. 91(C), pages 148-154.
    8. Xiang, Jingjie & Li, Kunpeng & Cui, Guowei, 2018. "A note on the asymptotic properties of least squares estimation in high dimensional constrained factor models," Economics Letters, Elsevier, vol. 171(C), pages 144-148.
    9. Joachim Freyberger & Andreas Neuhierl & Michael Weber & Michael Weber, 2018. "Dissecting Characteristics Nonparametrically," CESifo Working Paper Series 7187, CESifo.
    10. Chaieb, Ines & Langlois, Hugues & Scaillet, Olivier, 2021. "Factors and risk premia in individual international stock returns," Journal of Financial Economics, Elsevier, vol. 141(2), pages 669-692.
    11. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019. "A diagnostic criterion for approximate factor structure," Journal of Econometrics, Elsevier, vol. 212(2), pages 503-521.
    12. Güler ARAS & İlhan ÇAM & Bilal ZAVALSIZ & Serkan KESKİN, 2018. "Fama-French Çok Faktör Varlık Fiyatlama Modellerinin Performanslarının Karşılaştırılması: Borsa İstanbul Üzerine Bir Uygulama," Istanbul Business Research, Istanbul University Business School, vol. 47(2), pages 183-207, November.
    13. Yuan Liao & Xiye Yang, 2017. "Uniform Inference for Conditional Factor Models with Instrumental and Idiosyncratic Betas," Departmental Working Papers 201711, Rutgers University, Department of Economics.
    14. Anshul Verma & Riccardo Junior Buonocore & Tiziana di Matteo, 2017. "A cluster driven log-volatility factor model: a deepening on the source of the volatility clustering," Papers 1712.02138, arXiv.org, revised May 2018.
    15. Fei Liu & Jiti Gao & Yanrong Yang, 2020. "Time-Varying Panel Data Models with an Additive Factor Structure," Monash Econometrics and Business Statistics Working Papers 42/20, Monash University, Department of Econometrics and Business Statistics.
    16. Liang Chen & Juan Jose Dolado & Jesus Gonzalo & Haozi Pan, 2023. "Estimation of Characteristics-based Quantile Factor Models," Papers 2304.13206, arXiv.org.
    17. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2020. "Estimation of large dimensional conditional factor models in finance," Handbook of Econometrics, in: Steven N. Durlauf & Lars Peter Hansen & James J. Heckman & Rosa L. Matzkin (ed.), Handbook of Econometrics, edition 1, volume 7, chapter 0, pages 219-282, Elsevier.
    18. Cai, Zongwu & Ren, Yu & Yang, Bingduo, 2015. "A semiparametric conditional capital asset pricing model," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 117-126.
    19. Jianqing Fan & Yuan Ke & Yuan Liao, 2016. "Augmented Factor Models with Applications to Validating Market Risk Factors and Forecasting Bond Risk Premia," Papers 1603.07041, arXiv.org, revised Sep 2018.
    20. Ilze Kalnina, 2023. "Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 538-549, April.
    21. Fan, Jianqing & Xue, Lingzhou & Yao, Jiawei, 2017. "Sufficient forecasting using factor models," Journal of Econometrics, Elsevier, vol. 201(2), pages 292-306.
    22. Dashan Huang & Fuwei Jiang & Kunpeng Li & Guoshi Tong & Guofu Zhou, 2022. "Scaled PCA: A New Approach to Dimension Reduction," Management Science, INFORMS, vol. 68(3), pages 1678-1695, March.
    23. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    24. Jungjun Choi & Hyukjun Kwon & Yuan Liao, 2023. "Inference for Low-rank Models without Estimating the Rank," Papers 2311.16440, arXiv.org, revised Oct 2024.
    25. Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
    26. Borak, Szymon & Härdle, Wolfgang Karl & Mammen, Enno & Park, Byeong U., 2007. "Time series modelling with semiparametric factor dynamics," SFB 649 Discussion Papers 2007-023, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    27. Lee, Jiyon, 2015. "A semiparametric single index model with heterogeneous impacts on an unobserved variable," Journal of Econometrics, Elsevier, vol. 184(1), pages 13-36.
    28. Sakemoto, Ryuta, 2019. "Currency carry trades and the conditional factor model," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 198-208.
    29. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    30. Fei Liu & Jiti Gao & Yanrong Yang, 2019. "Nonparametric Estimation in Panel Data Models with Heterogeneity and Time Varyingness," Monash Econometrics and Business Statistics Working Papers 24/19, Monash University, Department of Econometrics and Business Statistics.
    31. Stefano Giglio & Dacheng Xiu, 2017. "Inference on Risk Premia in the Presence of Omitted Factors," NBER Working Papers 23527, National Bureau of Economic Research, Inc.
    32. Ossola, Elisa & Gagilardini, Patrick & Scaillet, Olivier, 2015. "Time-varying risk premium in large cross-sectional equity datasets," Working Papers unige:76321, University of Geneva, Geneva School of Economics and Management.
    33. Yuan Liao & Xiye Yang, 2017. "Uniform Inference for Characteristic Effects of Large Continuous-Time Linear Models," Papers 1711.04392, arXiv.org, revised Dec 2018.
    34. Jiti Gao & Fei Liu & Bin Peng & Yayi Yan, 2020. "Binary Response Models for Heterogeneous Panel Data with Interactive Fixed Effects," Papers 2012.03182, arXiv.org, revised Nov 2021.
    35. French, Declan & Wu, Yuliang & Li, Youwei, 2016. "Identifying the relative importance of stock characteristics," Journal of Multinational Financial Management, Elsevier, vol. 34(C), pages 80-91.
    36. Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
    37. Ge, S. & Li, S. & Linton, O., 2020. "A Dynamic Network of Arbitrage Characteristics," Cambridge Working Papers in Economics 2060, Faculty of Economics, University of Cambridge.
    38. Yuan Liao & Xinjie Ma & Andreas Neuhierl & Linda Schilling, 2025. "The Uncertainty of Machine Learning Predictions in Asset Pricing," Papers 2503.00549, arXiv.org.
    39. Jung, Sungkyu, 2018. "Continuum directions for supervised dimension reduction," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 27-43.
    40. Connor, G. & Li, S. & Linton, O., 2020. "A Dynamic Semiparametric Characteristics-based Model for Optimal Portfolio Selection," Cambridge Working Papers in Economics 20103, Faculty of Economics, University of Cambridge.
    41. Georg Keilbar & Juan M. Rodriguez-Poo & Alexandra Soberon & Weining Wang, 2022. "A projection based approach for interactive fixed effects panel data models," Papers 2201.11482, arXiv.org, revised Feb 2025.
    42. Brownlees, Christian T., 2019. "Hierarchical GARCH," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 17-27.
    43. Chen, Likai & Wang, Weining & Wu, Wei Biao, 2017. "Dynamic semiparametric factor model with a common break," SFB 649 Discussion Papers 2017-026, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    44. Hongyi Liu, 2025. "Deep Learning for Conditional Asset Pricing Models," Papers 2509.04812, arXiv.org.
    45. Minshuo Chen & Renyuan Xu & Yumin Xu & Ruixun Zhang, 2025. "Diffusion Factor Models: Generating High-Dimensional Returns with Factor Structure," Papers 2504.06566, arXiv.org, revised Jul 2025.

  62. Li, Degui & Lu, Zudi & Linton, Oliver, 2012. "Local Linear Fitting Under Near Epoch Dependence: Uniform Consistency With Convergence Rates," Econometric Theory, Cambridge University Press, vol. 28(5), pages 935-958, October.
    See citations under working paper version above.
  63. Kim, Woocheol & Linton, Oliver, 2011. "Estimation Of A Semiparametric Igarch(1,1) Model," Econometric Theory, Cambridge University Press, vol. 27(3), pages 639-661, June.
    See citations under working paper version above.
  64. Buch-Kromann, Tine & Guillén, Montserrat & Linton, Oliver & Nielsen, Jens Perch, 2011. "Multivariate density estimation using dimension reducing information and tail flattening transformations," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 99-110, January.

    Cited by:

    1. Urbina, Jilber & Guillén, Montserrat, 2013. "An application of capital allocation principles to operational risk," MPRA Paper 75726, University Library of Munich, Germany, revised Dec 2013.
    2. María Luz Gámiz & Enno Mammen & María Dolores Martínez Miranda & Jens Perch Nielsen, 2016. "Double one-sided cross-validation of local linear hazards," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(4), pages 755-779, September.
    3. Del Brio, Esther B. & Perote, Javier, 2012. "Gram–Charlier densities: Maximum likelihood versus the method of moments," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 531-537.
    4. Ramon Alemany & Catalina Bolancé & Montserrat Guillén, 2012. "Nonparametric estimation of Value-at-Risk," Working Papers XREAP2012-19, Xarxa de Referència en Economia Aplicada (XREAP), revised Oct 2012.
    5. Gámiz Pérez, M. Luz & Martínez Miranda, María Dolores & Nielsen, Jens Perch, 2013. "Smoothing survival densities in practice," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 368-382.

  65. Issler, João Victor & Linton, Oliver & Timmermann, Allan, 2011. "Annals issue on forecasting--Guest editors' introduction," Journal of Econometrics, Elsevier, vol. 164(1), pages 1-3, September.

    Cited by:

    1. Mikkel Plagborg-Møller & Christian K. Wolf, 2020. "Local Projections and VARs Estimate the Same Impulse Responses," Working Papers 2020-16, Princeton University. Economics Department..

  66. Gaglianone, Wagner Piazza & Lima, Luiz Renato & Linton, Oliver & Smith, Daniel R., 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 150-160.
    See citations under working paper version above.
  67. Oliver B. Linton & Yang Yan, 2011. "Semi- and Nonparametric ARCH Processes," Journal of Probability and Statistics, Hindawi, vol. 2011, pages 1-17, August.

    Cited by:

    1. Joseph Ngatchou-Wandji & Marwa Ltaifa & Didier Alain Njamen Njomen & Jia Shen, 2022. "Nonparametric Estimation of the Density Function of the Distribution of the Noise in CHARN Models," Mathematics, MDPI, vol. 10(4), pages 1-20, February.
    2. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional Variance Forecasts for Long-Term Stock Returns," Risks, MDPI, vol. 7(4), pages 1-22, November.

  68. Atak, Alev & Linton, Oliver & Xiao, Zhijie, 2011. "A semiparametric panel model for unbalanced data with application to climate change in the United Kingdom," Journal of Econometrics, Elsevier, vol. 164(1), pages 92-115, September.
    See citations under working paper version above.
  69. Lewbel, Arthur & McFadden, Daniel & Linton, Oliver, 2011. "Estimating features of a distribution from binomial data," Journal of Econometrics, Elsevier, vol. 162(2), pages 170-188, June.
    See citations under working paper version above.
  70. Linton, Oliver & Song, Kyungchul & Whang, Yoon-Jae, 2010. "An improved bootstrap test of stochastic dominance," Journal of Econometrics, Elsevier, vol. 154(2), pages 186-202, February.
    See citations under working paper version above.
  71. Linton, Oliver & Pan, Jiazhu & Wang, Hui, 2010. "Estimation For A Nonstationary Semi-Strong Garch(1,1) Model With Heavy-Tailed Errors," Econometric Theory, Cambridge University Press, vol. 26(1), pages 1-28, February.

    Cited by:

    1. Chen, Min & Zhu, Ke, 2013. "Sign-based portmanteau test for ARCH-type models with heavy-tailed innovations," MPRA Paper 50487, University Library of Munich, Germany.
    2. Beutner, Eric & Heinemann, Alexander & Smeekes, Stephan, 2024. "A residual bootstrap for conditional Value-at-Risk," Journal of Econometrics, Elsevier, vol. 238(2).
    3. Aknouche, Abdelhakim & Al-Eid, Eid M. & Hmeid, Aboubakry M., 2011. "Offline and online weighted least squares estimation of nonstationary power ARCH processes," Statistics & Probability Letters, Elsevier, vol. 81(10), pages 1535-1540, October.
    4. Hill, Jonathan B. & Aguilar, Mike, 2013. "Moment condition tests for heavy tailed time series," Journal of Econometrics, Elsevier, vol. 172(2), pages 255-274.
    5. Eric Beutner & Julia Schaumburg & Barend Spanjers, 2024. "Bootstrapping GARCH Models Under Dependent Innovations," Tinbergen Institute Discussion Papers 24-008/III, Tinbergen Institute.
    6. Chen, Min & Zhu, Ke, 2014. "Sign-based specification tests for martingale difference with conditional heteroscedasity," MPRA Paper 56347, University Library of Munich, Germany.
    7. Koo, Bonsoo & Linton, Oliver, 2015. "Let’S Get Lade: Robust Estimation Of Semiparametric Multiplicative Volatility Models," Econometric Theory, Cambridge University Press, vol. 31(4), pages 671-702, August.
    8. Abdelhakim Aknouche, 2012. "Multistage weighted least squares estimation of ARCH processes in the stable and unstable cases," Statistical Inference for Stochastic Processes, Springer, vol. 15(3), pages 241-256, October.
    9. Ding, Y., 2021. "Conditional Heteroskedasticity in the Volatility of Asset Returns," Cambridge Working Papers in Economics 2179, Faculty of Economics, University of Cambridge.
    10. Zhu, Ke, 2015. "Hausman tests for the error distribution in conditionally heteroskedastic models," MPRA Paper 66991, University Library of Munich, Germany.
    11. Hill, Jonathan B. & Prokhorov, Artem, 2016. "GEL estimation for heavy-tailed GARCH models with robust empirical likelihood inference," Journal of Econometrics, Elsevier, vol. 190(1), pages 18-45.
    12. Wang, Hui & Pan, Jiazhu, 2014. "Normal mixture quasi maximum likelihood estimation for non-stationary TGARCH(1,1) models," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 117-123.
    13. Chen, Min & Zhu, Ke, 2015. "Sign-based portmanteau test for ARCH-type models with heavy-tailed innovations," Journal of Econometrics, Elsevier, vol. 189(2), pages 313-320.
    14. Ding, Y., 2021. "Conditional Heteroskedasticity in the Volatility of Asset Returns," Janeway Institute Working Papers 2111, Faculty of Economics, University of Cambridge.
    15. Herwartz, Helmut, 2017. "Stock return prediction under GARCH — An empirical assessment," International Journal of Forecasting, Elsevier, vol. 33(3), pages 569-580.
    16. Francq, Christian & Zakoian, Jean-Michel, 2010. "Strict stationarity testing and estimation of explosive ARCH models," MPRA Paper 22414, University Library of Munich, Germany.
    17. Aguilar, Mike & Hill, Jonathan B., 2015. "Robust score and portmanteau tests of volatility spillover," Journal of Econometrics, Elsevier, vol. 184(1), pages 37-61.
    18. Pedersen, Rasmus Søndergaard & Rahbek, Anders, 2016. "Nonstationary GARCH with t-distributed innovations," Economics Letters, Elsevier, vol. 138(C), pages 19-21.

  72. Hafner, Christian M. & Linton, Oliver, 2010. "Efficient estimation of a multivariate multiplicative volatility model," Journal of Econometrics, Elsevier, vol. 159(1), pages 55-73, November.
    See citations under working paper version above.
  73. Kong, Efang & Linton, Oliver & Xia, Yingcun, 2010. "Uniform Bahadur Representation For Local Polynomial Estimates Of M-Regression And Its Application To The Additive Model," Econometric Theory, Cambridge University Press, vol. 26(5), pages 1529-1564, October.
    See citations under working paper version above.
  74. Oliver Linton & David Jacho-Chávez, 2010. "On internally corrected and symmetrized kernel estimators for nonparametric regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(1), pages 166-186, May.

    Cited by:

    1. Qian, Junhui & Wang, Le, 2009. "Estimating Semiparametric Panel Data Models by Marginal Integration," MPRA Paper 18850, University Library of Munich, Germany.
    2. Yuliana Linke & Igor Borisov & Pavel Ruzankin & Vladimir Kutsenko & Elena Yarovaya & Svetlana Shalnova, 2024. "Multivariate Universal Local Linear Kernel Estimators in Nonparametric Regression: Uniform Consistency," Mathematics, MDPI, vol. 12(12), pages 1-23, June.
    3. Shen, Jia & Xie, Yuan, 2013. "Strong consistency of the internal estimator of nonparametric regression with dependent data," Statistics & Probability Letters, Elsevier, vol. 83(8), pages 1915-1925.
    4. Yuliana Linke & Igor Borisov & Pavel Ruzankin & Vladimir Kutsenko & Elena Yarovaya & Svetlana Shalnova, 2022. "Universal Local Linear Kernel Estimators in Nonparametric Regression," Mathematics, MDPI, vol. 10(15), pages 1-28, July.

  75. Jacho-Chávez, David & Lewbel, Arthur & Linton, Oliver, 2010. "Identification and nonparametric estimation of a transformed additively separable model," Journal of Econometrics, Elsevier, vol. 156(2), pages 392-407, June.
    See citations under working paper version above.
  76. Sokbae Lee & Oliver Linton & Yoon-Jae Whang, 2009. "Testing for Stochastic Monotonicity," Econometrica, Econometric Society, vol. 77(2), pages 585-602, March.
    See citations under working paper version above.
  77. Oliver Linton & Jens Perch Nielsen & Søren Feodor Nielsen, 2009. "Non-parametric regression with a latent time series," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 187-207, July.
    See citations under working paper version above.
  78. Linton, Oliver & Sancetta, Alessio, 2009. "Consistent estimation of a general nonparametric regression function in time series," Journal of Econometrics, Elsevier, vol. 152(1), pages 70-78, September.

    Cited by:

    1. Seok Young Hong & Oliver Linton, 2016. "Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in?finite order," CeMMAP working papers CWP53/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Hong, S-Y. & Linton, O., 2018. "Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff," Cambridge Working Papers in Economics 1877, Faculty of Economics, University of Cambridge.
    3. Degui Li & Oliver Linton & Zudi Lu, 2012. "A flexible semiparametric model for time series," CeMMAP working papers CWP28/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Degui Li & Oliver Linton & Zudi Lu, 2010. "Loch Linear Fitting under Near Epoch Dependence: Uniform Consistency with Convergence Rate," STICERD - Econometrics Paper Series 549, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    5. Battey, Heather & Sancetta, Alessio, 2013. "Conditional estimation for dependent functional data," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 1-17.
    6. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.
    7. Degui Li & Zudi Lu & Oliver Linton, 2011. "Local Linear Fitting Under Near Epoch Dependence: Uniform consistency with Convergence Rates," Monash Econometrics and Business Statistics Working Papers 16/11, Monash University, Department of Econometrics and Business Statistics.

  79. Linton, Oliver B. & Mammen, Enno, 2008. "Nonparametric transformation to white noise," Journal of Econometrics, Elsevier, vol. 142(1), pages 241-264, January.
    See citations under working paper version above.
  80. Kalnina, Ilze & Linton, Oliver, 2008. "Estimating quadratic variation consistently in the presence of endogenous and diurnal measurement error," Journal of Econometrics, Elsevier, vol. 147(1), pages 47-59, November.

    Cited by:

    1. Yuta Koike, 2013. "Limit Theorems for the Pre-averaged Hayashi-Yoshida Estimator with Random Sampling," Global COE Hi-Stat Discussion Paper Series gd12-276, Institute of Economic Research, Hitotsubashi University.
    2. Bibinger, Markus & Hautsch, Nikolaus & Malec, Peter & Reiss, Markus, 2014. "Estimating the spot covariation of asset prices: Statistical theory and empirical evidence," SFB 649 Discussion Papers 2014-055, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Chaker, Selma, 2019. "The signal and the noise volatilities," Research in International Business and Finance, Elsevier, vol. 50(C), pages 79-105.
    4. Rasmus Tangsgaard Varneskov, 2011. "Flat-Top Realized Kernel Estimation of Quadratic Covariation with Non-Synchronous and Noisy Asset Prices," CREATES Research Papers 2011-35, Department of Economics and Business Economics, Aarhus University.
    5. Richard Y. Chen & Per A. Mykland, 2015. "Model-Free Approaches to Discern Non-Stationary Microstructure Noise and Time-Varying Liquidity in High-Frequency Data," Papers 1512.06159, arXiv.org, revised Oct 2018.
    6. Christensen, Kim & Oomen, Roel & Renò, Roberto, 2022. "The drift burst hypothesis," Journal of Econometrics, Elsevier, vol. 227(2), pages 461-497.
    7. Wang, Fangfang, 2014. "Optimal design of Fourier estimator in the presence of microstructure noise," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 708-722.
    8. Ding, Yashuang (Dexter), 2023. "A simple joint model for returns, volatility and volatility of volatility," Journal of Econometrics, Elsevier, vol. 232(2), pages 521-543.
    9. Li, Yifan & Nolte, Ingmar & Vasios, Michalis & Voev, Valeri & Xu, Qi, 2022. "Weighted Least Squares Realized Covariation Estimation," Journal of Banking & Finance, Elsevier, vol. 137(C).
    10. Fangfang Wang, 2016. "An Unbiased Measure of Integrated Volatility in the Frequency Domain," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(2), pages 147-164, March.
    11. Bu, R. & Li, D. & Linton, O. & Wang, H., 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Janeway Institute Working Papers 2208, Faculty of Economics, University of Cambridge.
    12. Neil Shephard & Ole E. Barndorff-Nielsen & Asger Lunde, 2006. "Subsampling realised kernels," Economics Series Working Papers 278, University of Oxford, Department of Economics.
    13. Simon Clinet & Yoann Potiron, 2017. "Efficient asymptotic variance reduction when estimating volatility in high frequency data," Papers 1701.01185, arXiv.org, revised Jun 2018.
    14. Bollerslev, Tim & Li, Jia & Li, Qiyuan, 2024. "Optimal nonparametric range-based volatility estimation," Journal of Econometrics, Elsevier, vol. 238(1).
    15. Sílvia Gonçalves & Ulrich Hounyo & Nour Meddahi, 2013. "Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns," CREATES Research Papers 2013-07, Department of Economics and Business Economics, Aarhus University.
    16. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Multivariate realised kernels: consistent positive semi-definite estimators of the covariation of equity prices with noise and non-synchronous trading," Economics Papers 2008-W10, Economics Group, Nuffield College, University of Oxford.
    17. Li, M. Z. & Linton, O., 2021. "Robust Estimation of Integrated and Spot Volatility," Cambridge Working Papers in Economics 2115, Faculty of Economics, University of Cambridge.
    18. Chaker, Selma, 2017. "On high frequency estimation of the frictionless price: The use of observed liquidity variables," Journal of Econometrics, Elsevier, vol. 201(1), pages 127-143.
    19. Ding, Y., 2021. "Augmented Real-Time GARCH: A Joint Model for Returns, Volatility and Volatility of Volatility," Cambridge Working Papers in Economics 2112, Faculty of Economics, University of Cambridge.
    20. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2016. "Testing for heteroscedasticity in jumpy and noisy high-frequency data: A resampling approach," CREATES Research Papers 2016-27, Department of Economics and Business Economics, Aarhus University.
    21. Jacod, Jean & Li, Yingying & Zheng, Xinghua, 2019. "Estimating the integrated volatility with tick observations," Journal of Econometrics, Elsevier, vol. 208(1), pages 80-100.
    22. Kim Christensen & Ulrich Hounyo & Mark Podolskij, 2017. "Is the diurnal pattern sufficient to explain the intraday variation in volatility? A nonparametric assessment," CREATES Research Papers 2017-30, Department of Economics and Business Economics, Aarhus University.
    23. Norman R. Swanson & Valentina Corradi & Walter Distaso, 2011. "Predictive Inference for Integrated Volatility," Departmental Working Papers 201109, Rutgers University, Department of Economics.
    24. Andersen, Torben G. & Cebiroglu, Gökhan & Hautsch, Nikolaus, 2017. "Volatility, information feedback and market microstructure noise: A tale of two regimes," CFS Working Paper Series 569, Center for Financial Studies (CFS).
    25. Ilze Kalnina, 2023. "Inference for Nonparametric High-Frequency Estimators with an Application to Time Variation in Betas," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(2), pages 538-549, April.
    26. Shin S. Ikeda, 2013. "A Note on the Mixingale Limit Theorem by McLeish (1977)," GRIPS Discussion Papers 13-11, National Graduate Institute for Policy Studies.
    27. Rui Da & Dacheng Xiu, 2021. "When Moving‐Average Models Meet High‐Frequency Data: Uniform Inference on Volatility," Econometrica, Econometric Society, vol. 89(6), pages 2787-2825, November.
    28. Yacine Aït-Sahalia & Jean Jacod, 2010. "Analyzing the Spectrum of Asset Returns: Jump and Volatility Components in High Frequency Data," NBER Working Papers 15808, National Bureau of Economic Research, Inc.
    29. Selma Chaker, 2013. "Volatility and Liquidity Costs," Staff Working Papers 13-29, Bank of Canada.
    30. Charles S. Bos & Paweł Janus & Siem Jan Koopman, 2012. "Spot Variance Path Estimation and Its Application to High-Frequency Jump Testing," Journal of Financial Econometrics, Oxford University Press, vol. 10(2), pages 354-389, 2012 06.
    31. Mykland, Per A. & Zhang, Lan, 2021. "The Observed Asymptotic Variance: Hard edges, and a regression approach," Journal of Econometrics, Elsevier, vol. 222(1), pages 411-428.
    32. Xiu, Dacheng, 2010. "Quasi-maximum likelihood estimation of volatility with high frequency data," Journal of Econometrics, Elsevier, vol. 159(1), pages 235-250, November.
    33. Cui, Wenhao & Hu, Jie & Wang, Jiandong, 2024. "Nonparametric estimation for high-frequency data incorporating trading information," Journal of Econometrics, Elsevier, vol. 240(1).
    34. Dai, Chaoxing & Lu, Kun & Xiu, Dacheng, 2019. "Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data," Journal of Econometrics, Elsevier, vol. 208(1), pages 43-79.
    35. Kim, Donggyu & Wang, Yazhen & Zou, Jian, 2016. "Asymptotic theory for large volatility matrix estimation based on high-frequency financial data," Stochastic Processes and their Applications, Elsevier, vol. 126(11), pages 3527-3577.
    36. Yiqi Liu & Qiang Liu & Zhi Liu & Deng Ding, 2017. "Determining the integrated volatility via limit order books with multiple records," Quantitative Finance, Taylor & Francis Journals, vol. 17(11), pages 1697-1714, November.
    37. Bibinger, Markus, 2012. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," Stochastic Processes and their Applications, Elsevier, vol. 122(6), pages 2411-2453.
    38. Yacine Ait-Sahalia & Jianqing Fan & Yingying Li, 2011. "The Leverage Effect Puzzle: Disentangling Sources of Bias at High Frequency," NBER Working Papers 17592, National Bureau of Economic Research, Inc.
    39. Kalnina, Ilze, 2011. "Subsampling high frequency data," Journal of Econometrics, Elsevier, vol. 161(2), pages 262-283, April.
    40. Chen, Richard Y. & Mykland, Per A., 2017. "Model-free approaches to discern non-stationary microstructure noise and time-varying liquidity in high-frequency data," Journal of Econometrics, Elsevier, vol. 200(1), pages 79-103.
    41. Clinet, Simon & Potiron, Yoann, 2019. "Testing if the market microstructure noise is fully explained by the informational content of some variables from the limit order book," Journal of Econometrics, Elsevier, vol. 209(2), pages 289-337.
    42. Li, Yingying & Zhang, Zhiyuan & Zheng, Xinghua, 2013. "Volatility inference in the presence of both endogenous time and microstructure noise," Stochastic Processes and their Applications, Elsevier, vol. 123(7), pages 2696-2727.
    43. Giorgio Mirone, 2017. "Inference from the futures: ranking the noise cancelling accuracy of realized measures," CREATES Research Papers 2017-24, Department of Economics and Business Economics, Aarhus University.
    44. Ziyang Xiong & Zhao Chen & Christina Dan Wang, 2025. "An Efficient Multi-scale Leverage Effect Estimator under Dependent Microstructure Noise," Papers 2505.08654, arXiv.org, revised Sep 2025.
    45. Yoann Potiron & Per Mykland, 2016. "Local Parametric Estimation in High Frequency Data," Papers 1603.05700, arXiv.org, revised Aug 2018.
    46. Mykland, Per A. & Zhang, Lan & Chen, Dachuan, 2019. "The algebra of two scales estimation, and the S-TSRV: High frequency estimation that is robust to sampling times," Journal of Econometrics, Elsevier, vol. 208(1), pages 101-119.
    47. Zu, Yang & Peter Boswijk, H., 2014. "Estimating spot volatility with high-frequency financial data," Journal of Econometrics, Elsevier, vol. 181(2), pages 117-135.
    48. Park, Sujin & Hong, Seok Young & Linton, Oliver, 2016. "Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error," Journal of Econometrics, Elsevier, vol. 191(2), pages 325-347.
    49. Kim Christensen & Mark Podolskij & Nopporn Thamrongrat & Bezirgen Veliyev, 2015. "Inference from high-frequency data: A subsampling approach," CREATES Research Papers 2015-45, Department of Economics and Business Economics, Aarhus University.
    50. Andersen, Torben G. & Archakov, Ilya & Cebiroglu, Gökhan & Hautsch, Nikolaus, 2022. "Local mispricing and microstructural noise: A parametric perspective," Journal of Econometrics, Elsevier, vol. 230(2), pages 510-534.
    51. Hwang, Eunju & Shin, Dong Wan, 2018. "Two-stage stationary bootstrapping for bivariate average realized volatility matrix under market microstructure noise and asynchronicity," Journal of Econometrics, Elsevier, vol. 202(2), pages 178-195.
    52. Selma Chaker & Nour Meddahi, 2013. "Volatility Forecasting when the Noise Variance Is Time-Varying," Staff Working Papers 13-48, Bank of Canada.
    53. Bandi, Federico M. & Russell, Jeffrey R. & Yang, Chen, 2008. "Realized volatility forecasting and option pricing," Journal of Econometrics, Elsevier, vol. 147(1), pages 34-46, November.
    54. Kim Christensen & Roel Oomen & Roberto Renò, 2018. "The drift burst hypothesis," CREATES Research Papers 2018-21, Department of Economics and Business Economics, Aarhus University.
    55. Rasmus Tangsgaard Varneskov, 2011. "Generalized Flat-Top Realized Kernel Estimation of Ex-Post Variation of Asset Prices Contaminated by Noise," CREATES Research Papers 2011-31, Department of Economics and Business Economics, Aarhus University.
    56. Kim Christensen & Roel Oomen & Roberto Renò, 2016. "The Drift Burst Hypothesis," CREATES Research Papers 2016-28, Department of Economics and Business Economics, Aarhus University.
    57. Ikeda, Shin S., 2016. "A bias-corrected estimator of the covariation matrix of multiple security prices when both microstructure effects and sampling durations are persistent and endogenous," Journal of Econometrics, Elsevier, vol. 193(1), pages 203-214.
    58. Bibinger, Markus, 2011. "An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory," SFB 649 Discussion Papers 2011-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    59. Patton, Andrew J., 2011. "Data-based ranking of realised volatility estimators," Journal of Econometrics, Elsevier, vol. 161(2), pages 284-303, April.

  81. Lu, Zudi & Linton, Oliver, 2007. "Local Linear Fitting Under Near Epoch Dependence," Econometric Theory, Cambridge University Press, vol. 23(1), pages 37-70, February.

    Cited by:

    1. Jenish, Nazgul, 2012. "Nonparametric spatial regression under near-epoch dependence," Journal of Econometrics, Elsevier, vol. 167(1), pages 224-239.
    2. Chen, Xiaohong & Liao, Zhipeng & Sun, Yixiao, 2014. "Sieve inference on possibly misspecified semi-nonparametric time series models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 639-658.
    3. Degui Li & Oliver Linton & Zudi Lu, 2012. "A flexible semiparametric model for time series," CeMMAP working papers CWP28/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Nikolay Gospodinov & Masayuki Hirukawa, 2008. "Time Series Nonparametric Regression Using Asymmetric Kernels with an Application to Estimation of Scalar Diffusion Processes," CIRJE F-Series CIRJE-F-573, CIRJE, Faculty of Economics, University of Tokyo.
    5. Degui Li & Oliver Linton & Zudi Lu, 2010. "Loch Linear Fitting under Near Epoch Dependence: Uniform Consistency with Convergence Rate," STICERD - Econometrics Paper Series 549, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    6. Yang, Lixiong & Lee, Chingnun & Shie, Fu Shuen, 2014. "How close a relationship does a capital market have with other markets? A reexamination based on the equal variance test," Pacific-Basin Finance Journal, Elsevier, vol. 26(C), pages 198-226.
    7. Christian M. Hafner & Oliver B. Linton & Linqi Wang, 2024. "Dynamic Autoregressive Liquidity (DArLiQ)," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(2), pages 774-785, April.
    8. Hafner, C. M., 2022. "Dynamic Autoregressive Liquidity (DArLiQ)," Cambridge Working Papers in Economics 2214, Faculty of Economics, University of Cambridge.
    9. Xiaohong Chen & . . & Yixiao Sun, 2012. "Sieve inference on semi-nonparametric time series models," CeMMAP working papers CWP06/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Jia Chen & Degui Li & Oliver Linton & Zudi Lu, 2015. "Semiparametric model averaging of ultra-high dimensional time series," CeMMAP working papers 62/15, Institute for Fiscal Studies.
    11. Inoue, Atsushi & Jin, Lu & Rossi, Barbara, 2017. "Rolling window selection for out-of-sample forecasting with time-varying parameters," Journal of Econometrics, Elsevier, vol. 196(1), pages 55-67.
    12. Lee, Jiyon, 2015. "A semiparametric single index model with heterogeneous impacts on an unobserved variable," Journal of Econometrics, Elsevier, vol. 184(1), pages 13-36.
    13. Jenish, Nazgul & Prucha, Ingmar R., 2012. "On spatial processes and asymptotic inference under near-epoch dependence," Journal of Econometrics, Elsevier, vol. 170(1), pages 178-190.
    14. Li, Degui & Linton, Oliver & Lu, Zudi, 2015. "A flexible semiparametric forecasting model for time series," Journal of Econometrics, Elsevier, vol. 187(1), pages 345-357.
    15. Degui Li & Zudi Lu & Oliver Linton, 2011. "Local Linear Fitting Under Near Epoch Dependence: Uniform consistency with Convergence Rates," Monash Econometrics and Business Statistics Working Papers 16/11, Monash University, Department of Econometrics and Business Statistics.
    16. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    17. Linton, Oliver & Sancetta, Alessio, 2009. "Consistent estimation of a general nonparametric regression function in time series," Journal of Econometrics, Elsevier, vol. 152(1), pages 70-78, September.
    18. Kurisu, Daisuke, 2019. "On nonparametric inference for spatial regression models under domain expanding and infill asymptotics," Statistics & Probability Letters, Elsevier, vol. 154(C), pages 1-1.
    19. Rossi, Barbara & Inoue, Atsushi & Jin, Lu, 2014. "Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters," CEPR Discussion Papers 10168, C.E.P.R. Discussion Papers.
    20. Xiaohong Chen & . . & Yixiao Sun, 2012. "Sieve inference on semi-nonparametric time series models," CeMMAP working papers 06/12, Institute for Fiscal Studies.

  82. Connor, Gregory & Linton, Oliver, 2007. "Semiparametric estimation of a characteristic-based factor model of common stock returns," Journal of Empirical Finance, Elsevier, vol. 14(5), pages 694-717, December.
    See citations under working paper version above.
  83. Seo, Myung Hwan & Linton, Oliver, 2007. "A smoothed least squares estimator for threshold regression models," Journal of Econometrics, Elsevier, vol. 141(2), pages 704-735, December.
    See citations under working paper version above.
  84. Linton, Oliver & Xiao, Zhijie, 2007. "A Nonparametric Regression Estimator That Adapts To Error Distribution Of Unknown Form," Econometric Theory, Cambridge University Press, vol. 23(3), pages 371-413, June.
    See citations under working paper version above.
  85. Linton, O. & Whang, Yoon-Jae, 2007. "The quantilogram: With an application to evaluating directional predictability," Journal of Econometrics, Elsevier, vol. 141(1), pages 250-282, November.

    Cited by:

    1. Stanislav Anatolyev, 2021. "Directional news impact curve," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 94-107, January.
    2. Thilo A. Schmitt & Rudi Schafer & Holger Dette & Thomas Guhr, 2015. "Quantile Correlations: Uncovering temporal dependencies in financial time series," Papers 1507.04990, arXiv.org.
    3. Park, Joon Y. & Whang, Yoon-Jae, 2012. "Random walk or chaos: A formal test on the Lyapunov exponent," Journal of Econometrics, Elsevier, vol. 169(1), pages 61-74.
    4. Jozef Barun'ik & Tobias Kley, 2015. "Quantile Coherency: A General Measure for Dependence between Cyclical Economic Variables," Papers 1510.06946, arXiv.org, revised Dec 2018.
    5. Ayedi Ahmed & Marjène Gana & Stéphane Goutte & Khaled Guesmi, 2023. "Managing Portfolio Risk During the BREXIT Crisis: A Cross-Quantilogram Analysis of Stock Markets and Commodities Across European Countries, the US, and BRICS," Working Papers halshs-04068651, HAL.
    6. Baumöhl, Eduard & Lyócsa, Štefan, 2017. "Directional predictability from stock market sector indices to gold: A cross-quantilogram analysis," Finance Research Letters, Elsevier, vol. 23(C), pages 152-164.
    7. Arif, Muhammad & Naeem, Muhammad Abubakr & Farid, Saqib & Nepal, Rabindra & Jamasb, Tooraj, 2022. "Diversifier or more? Hedge and safe haven properties of green bonds during COVID-19," Energy Policy, Elsevier, vol. 168(C).
    8. Valdivia Coria, Joab Dan, 2022. "Apalancamiento, ciclo financiero y económico [Leverage, financial and business cycles]," MPRA Paper 116849, University Library of Munich, Germany.
    9. Ngo Thai Hung & Vo Xuan Vinh, 2023. "Asymmetric impact of the COVID-19 pandemic on foreign exchange markets: Evidence from an extreme quantile approach," Economics and Business Letters, Oviedo University Press, vol. 12(1), pages 20-32.
    10. Juan Carlos Escanciano & Carlos Velasco, 2006. "Testing the Martingale Difference Hypothesis Using Integrated Regression Functions," Faculty Working Papers 06/06, School of Economics and Business Administration, University of Navarra.
    11. John Galbraith & Simon van Norden, 2008. "The Calibration Of Probabilistic Economic Forecasts," Departmental Working Papers 2008-05, McGill University, Department of Economics.
    12. Ashby, M. & Linton, O. B., 2022. "Do Consumption-based Asset Pricing Models Explain Own-history Predictability in Stock Market Returns?," Cambridge Working Papers in Economics 2259, Faculty of Economics, University of Cambridge.
    13. Balsalobre-Lorente, Daniel & Sinha, Avik & Murshed, Muntasir, 2023. "Russia-Ukraine conflict sentiments and energy market returns in G7 countries: Discovering the unexplored dynamics," Energy Economics, Elsevier, vol. 125(C).
    14. Syed Jawad Hussain Shahzad & Naveed Raza & David Roubaud & Jose Arreola Hernandez & Stelios Bekiros, 2019. "Gold as Safe Haven for G-7 Stocks and Bonds: A Revisit," Post-Print hal-02352004, HAL.
    15. Corbet, Shaen & Katsiampa, Paraskevi & Lau, Chi Keung Marco, 2020. "Measuring quantile dependence and testing directional predictability between Bitcoin, altcoins and traditional financial assets," International Review of Financial Analysis, Elsevier, vol. 71(C).
    16. Zhang, Dongna & Chen, Xihui Haviour & Lau, Chi Keung Marco & Xu, Bing, 2023. "Implications of cryptocurrency energy usage on climate change," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    17. Anatolyev Stanislav, 2009. "Multi-Market Direction-of-Change Modeling Using Dependence Ratios," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-24, March.
    18. Christian Urom & Gideon Ndubuisi & Hela Mzoughi & Khaled Guesmi, 2024. "Exploring the coherency and predictability between the stocks of artificial intelligence and energy corporations," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-31, December.
    19. Stelios Bekiros & Syed Jawad Hussain Shahzad & Jose Arreola-Hernandez & Mobeen Ur Rehman, 2018. "Directional predictability and time-varying spillovers between stock markets and economic cycles," Post-Print hal-01996787, HAL.
    20. Satish Kumar & Rabeh Khalfaoui & Aviral Kumar Tiwari, 2021. "Does geopolitical risk improve the directional predictability from oil to stock returns? Evidence from oil-exporting and oil-importing countries," Post-Print hal-03797578, HAL.
    21. Davis, Richard & Drees, Holger & Segers, Johan & Warchol, Michal, 2018. "Inference on the tail process with application to financial time series modelling," LIDAM Discussion Papers ISBA 2018002, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    22. Shahzad, Syed Jawad Hussain & Naifar, Nader & Hammoudeh, Shawkat & Roubaud, David, 2017. "Directional predictability from oil market uncertainty to sovereign credit spreads of oil-exporting countries: Evidence from rolling windows and crossquantilogram analysis," Energy Economics, Elsevier, vol. 68(C), pages 327-339.
    23. Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel R. Smith, 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 150-160, January.
    24. Roch, Oriol, 2013. "Histogram-based prediction of directional price relatives," Finance Research Letters, Elsevier, vol. 10(3), pages 110-115.
    25. Alin Marius Andries & Steven Ongena & Nicu Sprincean & Radu Tunaru, 2020. "Risk Spillovers and Interconnectedness between Systemically Important Institutions," Swiss Finance Institute Research Paper Series 20-40, Swiss Finance Institute.
    26. Rahman, Md Lutfur & Hedström, Axel & Uddin, Gazi Salah & Kang, Sang Hoon, 2021. "Quantile relationship between Islamic and non-Islamic equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    27. António Afonso & José Alves & Wojciech Grabowski & Sofia Monteiro, 2025. "Stock and Sovereign Returns Linkages: Time-Varying Causality and Extreme-Quantile Determinants," CESifo Working Paper Series 11667, CESifo.
    28. Stefan Birr & Stanislav Volgushev & Tobias Kley & Holger Dette & Marc Hallin, 2017. "Quantile spectral analysis for locally stationary time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(5), pages 1619-1643, November.
    29. Lee, JiHyung, 2015. "Predictive quantile regression with persistent covariates: IVX-QR approach," MPRA Paper 65150, University Library of Munich, Germany.
    30. Stanislav Anatolyev & Nikolay Gospodinov, 2007. "Modeling Financial Return Dynamics by Decomposition," Working Papers w0095, Center for Economic and Financial Research (CEFIR).
    31. Uwe Hassler & Marc-Oliver Pohle & Tanja Zahn, 2025. "Simultaneous Inference Bands for Autocorrelations," Papers 2503.18560, arXiv.org, revised Aug 2025.
    32. Engin Bekar, 2022. "The Relationship Between Geopolitical Risks and Housing Returns in Türkiye: Evidence from the Cross – Quantilogram," International Econometric Review (IER), Econometric Research Association, vol. 14(2), pages 59-71, June.
    33. Ćmiel, Bogdan & Ledwina, Teresa, 2020. "Validation of association," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 55-67.
    34. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.
    35. Busettti, F. & Harvey, A., 2007. "Tests of time-invariance," Cambridge Working Papers in Economics 0701, Faculty of Economics, University of Cambridge.
    36. Alex Maynard & Katsumi Shimotsu & Nina Kuriyama, 2023. "Inference in Predictive Quantile Regressions," Papers 2306.00296, arXiv.org, revised May 2024.
    37. Bouri, Elie & Shahzad, Syed Jawad Hussain & Raza, Naveed & Roubaud, David, 2018. "Oil volatility and sovereign risk of BRICS," Energy Economics, Elsevier, vol. 70(C), pages 258-269.
    38. Bruno Spilak & Wolfgang Karl Hardle, 2020. "Tail-risk protection: Machine Learning meets modern Econometrics," Papers 2010.03315, arXiv.org, revised Aug 2021.
    39. Yuichi Goto & Tobias Kley & Ria Van Hecke & Stanislav Volgushev & Holger Dette & Marc Hallin, 2021. "The Integrated Copula Spectrum," Working Papers ECARES 2021-29, ULB -- Universite Libre de Bruxelles.
    40. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.
    41. Sinha, Avik & Sharif, Arshian & Adhikari, Arnab & Sharma, Ankit, 2021. "Dependence Structure between Indian Financial Market and Energy Commodities: A Cross-quantilogram based Evidence," MPRA Paper 111181, University Library of Munich, Germany, revised 2021.
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    Cited by:

    1. Feiyu Jiang & Dong Li & Ke Zhu, 2019. "Non-standard inference for augmented double autoregressive models with null volatility coefficients," Papers 1905.01798, arXiv.org.
    2. Jiang, Feiyu & Li, Dong & Zhu, Ke, 2020. "Non-standard inference for augmented double autoregressive models with null volatility coefficients," Journal of Econometrics, Elsevier, vol. 215(1), pages 165-183.
    3. Rivera-Alonso, David & Iglesias, Emma M., 2024. "Is the Chinese crude oil spot price a good hedging tool for other crude oil prices, and in special for the main Russian oil benchmarks and during international sanctions?," Resources Policy, Elsevier, vol. 90(C).
    4. Demos Antonis & Kyriakopoulou Dimitra, 2019. "Finite-Sample Theory and Bias Correction of Maximum Likelihood Estimators in the EGARCH Model," Journal of Time Series Econometrics, De Gruyter, vol. 11(1), pages 1-20, January.
    5. Kyriakopoulou, Dimitra & Demos, Antonis, 2010. "Edgeworth and Moment Approximations: The Case of MM and QML Estimators for the MA (1) Models," MPRA Paper 122393, University Library of Munich, Germany.
    6. Antonis Demos & Dimitra Kyriakopoulou, 2011. "Bias Correction of ML and QML Estimators in the EGARCH(1,1) Model," DEOS Working Papers 1108, Athens University of Economics and Business.
    7. Christian Francq & Jean-Michel Zakoïan, 2008. "Estimating ARCH Models when the Coefficients are Allowed to be Equal to Zero," Working Papers 2008-07, Center for Research in Economics and Statistics.
    8. Stelios Arvanitis & Antonis Demos, "undated". "A Class of Indirect Inference Estimators: Higher Order Asymptotics and Approximate Bias Correction (Revised)," DEOS Working Papers 1411, Athens University of Economics and Business, revised 23 Sep 2014.
    9. Antonis Demos & Stelios Arvanitis, 2010. "A New Class of Indirect Estimators and Bias Correction," DEOS Working Papers 1023, Athens University of Economics and Business.
    10. Fan, Yanqin & Park, Sang Soo, 2014. "Nonparametric inference for counterfactual means: Bias-correction, confidence sets, and weak IV," Journal of Econometrics, Elsevier, vol. 178(P1), pages 45-56.
    11. Arvanitis Stelios & Demos Antonis, 2014. "Valid Locally Uniform Edgeworth Expansions for a Class of Weakly Dependent Processes or Sequences of Smooth Transformations," Journal of Time Series Econometrics, De Gruyter, vol. 6(2), pages 183-235, July.

  87. Fernandes, Marcelo & Linton, Oliver & Scaillet, Olivier, 2007. "Semiparametric methods in econometrics," Journal of Econometrics, Elsevier, vol. 141(1), pages 1-4, November.

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    1. Hallin, Marc & La Vecchia, Davide, 2017. "R-estimation in semiparametric dynamic location-scale models," Journal of Econometrics, Elsevier, vol. 196(2), pages 233-247.

  88. Cho, Young-Hyun & Linton, Oliver & Whang, Yoon-Jae, 2007. "Are there Monday effects in stock returns: A stochastic dominance approach," Journal of Empirical Finance, Elsevier, vol. 14(5), pages 736-755, December.
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  89. Arthur Lewbel & Oliver Linton, 2007. "Nonparametric Matching and Efficient Estimators of Homothetically Separable Functions," Econometrica, Econometric Society, vol. 75(4), pages 1209-1227, July.
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  90. Connor, Gregory & Korajczyk, Robert A. & Linton, Oliver, 2006. "The common and specific components of dynamic volatility," Journal of Econometrics, Elsevier, vol. 132(1), pages 231-255, May.

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    1. Gilles Dufrénot & Valérie Mignon & Anne Péguin-Feissolle, 2010. "The Effects of the Subprime Crisis on the Latin American Financial Markets: an Empirical Assessment," Working Papers 2010-11, CEPII research center.
    2. Najam Iqbal & Muhammad Saqib Manzoor & Muhammad Ishaq Bhatti, 2021. "Asymmetry and Leverage with News Impact Curve Perspective in Australian Stock Returns’ Volatility during COVID-19," JRFM, MDPI, vol. 14(7), pages 1-15, July.
    3. Jianqing Fan & Donggyu Kim & Minseok Shin & Yazhen Wang, 2024. "Factor and Idiosyncratic VAR-Ito Volatility Models for Heavy-Tailed High-Frequency Financial Data," Working Papers 202415, University of California at Riverside, Department of Economics.
    4. Kwangmin Jung & Donggyu Kim & Seunghyeon Yu, 2022. "Next generation models for portfolio risk management: An approach using financial big data," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 89(3), pages 765-787, September.
    5. Matteo Barigozzi & Marc Hallin, 2023. "Dynamic Factor Models: a Genealogy," Working Papers ECARES 2023-15, ULB -- Universite Libre de Bruxelles.
    6. Barigozzi, Matteo & Hallin, Mark, 2015. "Generalized dynamic factor models and volatilities: recovering the market volatility shocks," LSE Research Online Documents on Economics 60980, London School of Economics and Political Science, LSE Library.
    7. M. Hashem Pesaran & Paolo Zaffaroni, 2009. "Optimality and Diversifiability of Mean Variance and Arbitrage Pricing Portfolios," CESifo Working Paper Series 2857, CESifo.
    8. Pesaran, M.H. & Zaffaroni, P., 2008. "Optimal Asset Allocation with Factor Models for Large Portfolios," Cambridge Working Papers in Economics 0813, Faculty of Economics, University of Cambridge.
    9. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities estimation and forecasting," LSE Research Online Documents on Economics 67455, London School of Economics and Political Science, LSE Library.
    10. Matteo Barigozzi & Marc Hallin, 2018. "Generalized Dynamic Factor Models and Volatilities: Consistency, rates, and prediction intervals," Papers 1811.10045, arXiv.org, revised Jul 2019.
    11. Kim, Donggyu & Fan, Jianqing, 2019. "Factor GARCH-Itô models for high-frequency data with application to large volatility matrix prediction," Journal of Econometrics, Elsevier, vol. 208(2), pages 395-417.
    12. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2006. "Dynamic Factor GARCH: Multivariate Volatility Forecast for a Large Number of Series," LEM Papers Series 2006/25, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    13. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Papers 1510.05118, arXiv.org, revised Jul 2016.
    14. Soosung Hwang & Steve Satchell, 2005. "GARCH model with cross-sectional volatility: GARCHX models," Applied Financial Economics, Taylor & Francis Journals, vol. 15(3), pages 203-216.
    15. Eric Renault & Thijs Van Der & Bas J M Werker, 2023. "Arbitrage Pricing Theory for Idiosyncratic Variance Factors," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1403-1442.
    16. L. Vanessa Smith & Takashi Yamagata, 2008. "Firm Level Volatility-Return Analysis using Dynamic Panels," Discussion Papers 08/09, Department of Economics, University of York.
    17. Byun, Sung Je, 2016. "The usefulness of cross-sectional dispersion for forecasting aggregate stock price volatility," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 162-180.
    18. Ghysels, Eric, 2014. "Factor Analysis with Large Panels of Volatility Proxies," CEPR Discussion Papers 10034, C.E.P.R. Discussion Papers.
    19. García-Martos, Carolina & Rodríguez, Julio & Sánchez, María Jesús, 2011. "Forecasting electricity prices and their volatilities using Unobserved Components," Energy Economics, Elsevier, vol. 33(6), pages 1227-1239.
    20. Lübbers, Johannes & Posch, Peter N., 2016. "Commodities' common factor: An empirical assessment of the markets' drivers," Journal of Commodity Markets, Elsevier, vol. 4(1), pages 28-40.
    21. Matteo Barigozzi, 2023. "Asymptotic equivalence of Principal Components and Quasi Maximum Likelihood estimators in Large Approximate Factor Models," Papers 2307.09864, arXiv.org, revised Jun 2024.
    22. Andreou, Elena & Ghysels, Eric, 2021. "Predicting the VIX and the volatility risk premium: The role of short-run funding spreads Volatility Factors," Journal of Econometrics, Elsevier, vol. 220(2), pages 366-398.
    23. Engle, Robert F. & Campos-Martins, Susana, 2023. "What are the events that shake our world? Measuring and hedging global COVOL," Journal of Financial Economics, Elsevier, vol. 147(1), pages 221-242.
    24. Brownlees, Christian T., 2019. "Hierarchical GARCH," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 17-27.
    25. Gregory Connor & Lisa R. Goldberg & Robert A. Korajczyk, 2010. "Portfolio Risk Analysis," Economics Books, Princeton University Press, edition 1, number 9224.
    26. Umberto Triacca & Fulvia Focker, 2014. "Estimating overnight volatility of asset returns by using the generalized dynamic factor model approach," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(2), pages 235-254, October.
    27. Xinyu Song, 2019. "Large Volatility Matrix Prediction with High-Frequency Data," Papers 1907.01196, arXiv.org, revised Sep 2019.

  91. Andrew Jeffrey & Oliver Linton & Thong Nguyen, 2006. "Flexible Term Structure Estimation: Which Method is Preferred?," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 63(1), pages 99-122, February.
    See citations under working paper version above.
  92. Kristensen, Dennis & Linton, Oliver, 2006. "A Closed-Form Estimator For The Garch(1,1) Model," Econometric Theory, Cambridge University Press, vol. 22(2), pages 323-337, April.

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    1. Donald W. K. Andrews & Patrik Guggenberger, 2014. "A Conditional-Heteroskedasticity-Robust Confidence Interval for the Autoregressive Parameter," The Review of Economics and Statistics, MIT Press, vol. 96(2), pages 376-381, May.
    2. Hafner, C. & Preminger, A., 2010. "Deciding between GARCH and Stochastic Volatility via Strong Decision Rules," LIDAM Reprints ISBA 2010032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Linton, O. & Xiao, Z., 2019. "Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity," Cambridge Working Papers in Economics 1907, Faculty of Economics, University of Cambridge.
    4. Leucht, Anne & Neumann, Michael H. & Kreiss, Jens-Peter, 2013. "A model specification test for GARCH(1,1) processes," Working Papers 13-11, University of Mannheim, Department of Economics.
    5. Abhimanyu Gupta, 2020. "Efficient closed-form estimation of large spatial autoregressions," Papers 2008.12395, arXiv.org, revised May 2021.
    6. Hafner, Christian M. & Linton, Oliver, 2017. "An Almost Closed Form Estimator For The Egarch Model," Econometric Theory, Cambridge University Press, vol. 33(4), pages 1013-1038, August.
    7. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, November.
    8. Amendola, Alessandra & Storti, Giuseppe, 2009. "Combination of multivariate volatility forecasts," SFB 649 Discussion Papers 2009-007, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Christian M. Dahl & Emma M. Iglesias, 2008. "The limiting properties of the QMLE in a general class of asymmetric volatility models," CREATES Research Papers 2008-38, Department of Economics and Business Economics, Aarhus University.
    10. Shi, Yanlin, 2022. "A closed-form estimator for the Markov switching in mean model," Finance Research Letters, Elsevier, vol. 44(C).
    11. Todd Prono, 2017. "Regular Variation of Popular GARCH Processes Allowing for Distributional Asymmetry," Finance and Economics Discussion Series 2017-095, Board of Governors of the Federal Reserve System (U.S.).
    12. Ahsan, Md. Nazmul & Dufour, Jean-Marie, 2021. "Simple estimators and inference for higher-order stochastic volatility models," Journal of Econometrics, Elsevier, vol. 224(1), pages 181-197.
    13. Arvanitis Stelios & Demos Antonis, 2018. "On the Validity of Edgeworth Expansions and Moment Approximations for Three Indirect Inference Estimators," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-38, January.
    14. Todd, Prono, 2009. "Simple, Skewness-Based GMM Estimation of the Semi-Strong GARCH(1,1) Model," MPRA Paper 30994, University Library of Munich, Germany, revised 30 Jul 2011.
    15. PREMINGER, Arie & STORTI, Giuseppe, 2006. "A GARCH (1,1) estimator with (almost) no moment conditions on the error term," LIDAM Discussion Papers CORE 2006068, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Prono, Todd, 2011. "When A Factor Is Measured with Error: The Role of Conditional Heteroskedasticity in Identifying and Estimating Linear Factor Models," MPRA Paper 33593, University Library of Munich, Germany.
    17. HAFNER, Christian & PREMINGER, Arie, 2006. "Asymptotic theory for a factor GARCH model," LIDAM Discussion Papers CORE 2006071, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Amendola, Alessandra & Storti, Giuseppe, 2008. "A GMM procedure for combining volatility forecasts," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3047-3060, February.
    19. Todd Prono, 2016. "Closed-Form Estimation of Finite-Order ARCH Models: Asymptotic Theory and Finite-Sample Performance," Finance and Economics Discussion Series 2016-083, Board of Governors of the Federal Reserve System (U.S.).
    20. Hafner C. & Linton, O., 2013. "An Almost Closed Form Estimator for the EGARCH," LIDAM Discussion Papers ISBA 2013010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    21. Li, Qi & Lian, Heng & Zhu, Fukang, 2016. "Robust closed-form estimators for the integer-valued GARCH (1,1) model," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 209-225.
    22. Sbrana, Giacomo & Poloni, Federico, 2013. "A closed-form estimator for the multivariate GARCH(1,1) model," Journal of Multivariate Analysis, Elsevier, vol. 120(C), pages 152-162.
    23. Xuejie Feng & Chiping Zhang, 2020. "A Perturbation Method to Optimize the Parameters of Autoregressive Conditional Heteroscedasticity Model," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 1021-1044, March.
    24. Poloni, Federico & Sbrana, Giacomo, 2014. "Feasible generalized least squares estimation of multivariate GARCH(1, 1) models," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 151-159.

  93. O. Linton & E. Mammen, 2005. "Estimating Semiparametric ARCH(∞) Models by Kernel Smoothing Methods," Econometrica, Econometric Society, vol. 73(3), pages 771-836, May.
    See citations under working paper version above.
  94. Linton, Oliver, 2005. "Nonparametric Inference For Unbalanced Time Series Data," Econometric Theory, Cambridge University Press, vol. 21(1), pages 143-157, February.
    See citations under working paper version above.
  95. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2005. "Consistent Testing for Stochastic Dominance under General Sampling Schemes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 735-765.
    See citations under working paper version above.
  96. Kim, Woocheol & Linton, Oliver, 2004. "The Live Method For Generalized Additive Volatility Models," Econometric Theory, Cambridge University Press, vol. 20(6), pages 1094-1139, December.
    See citations under working paper version above.
  97. Steve Berry & Oliver B. Linton & Ariel Pakes, 2004. "Limit Theorems for Estimating the Parameters of Differentiated Product Demand Systems," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 71(3), pages 613-654.
    See citations under working paper version above.
  98. Wang Q. & Linton O. & Hardle W., 2004. "Semiparametric Regression Analysis With Missing Response at Random," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 334-345, January.
    See citations under working paper version above.
  99. Hodgson, Douglas J. & Linton, Oliver & Vorkink, Keith, 2004. "Testing forward exchange rate unbiasedness efficiently: A semiparametric approach," Journal of Applied Economics, Universidad del CEMA, vol. 7(2), pages 1-29, November.

    Cited by:

    1. Dhekra Azouzi & Rohit Vishal Kumar & Chaker Aloui, 2011. "Forward Rate Unbiasedness Hypothesis in the Tunisian Exchange Rate Market," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 1(2), pages 17-44, July.
    2. Amengual, Dante & Sentana, Enrique, 2010. "A comparison of mean-variance efficiency tests," Journal of Econometrics, Elsevier, vol. 154(1), pages 16-34, January.
    3. Derek E. H. Olmstead, 2018. "Ontario's Auction Market for Financial Transmission Rights: An Analysis of its Efficiency," The Energy Journal, , vol. 39(1), pages 235-252, January.
    4. Ioannis N. Kallianiotis, 2021. "Exchange Rate Determination: The Portfolio-Balance Approach," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 11(1), pages 1-2.
    5. Fu, Hsuan & Luger, Richard, 2022. "Multiple testing of the forward rate unbiasedness hypothesis across currencies," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 232-245.

  100. Kristensen, Dennis & Linton, Oliver, 2004. "03.5.2. Consistent Standard Errors for Target Variance Approach to GARCH Estimation—Solution," Econometric Theory, Cambridge University Press, vol. 20(5), pages 990-993, October.

    Cited by:

    1. Rasmus Søndergaard Pedersen, 2014. "Targeting estimation of CCC-Garch models with infinite fourth moments," Discussion Papers 14-04, University of Copenhagen. Department of Economics.
    2. Francq, Christian & Horvath, Lajos & Zakoian, Jean-Michel, 2009. "Merits and drawbacks of variance targeting in GARCH models," MPRA Paper 15143, University Library of Munich, Germany.
    3. Christian Francq & Lajos Horváth & Jean-Michel Zakoïan, 2016. "Variance Targeting Estimation of Multivariate GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 353-382.
    4. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2016. "Copula--based Specification of vector MEMs," Econometrics Working Papers Archive 2016_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    5. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    6. Stanislav Anatolyev & Stanislav Khrapov, 2015. "Right on Target, or Is it? The Role of Distributional Shape in Variance Targeting," Econometrics, MDPI, vol. 3(3), pages 1-23, August.
    7. Van Dijk, Dick & Munandar, Haris & Hafner, Christian, 2011. "The Euro-introduction and non-Euro currencies," LIDAM Reprints ISBA 2011052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Fabrizio Cipollini & Robert F. Engle & Giampiero M. Gallo, 2017. "Copula-based vMEM Specifications versus Alternatives: The Case of Trading Activity," Econometrics Working Papers Archive 2017_02, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    9. Asai, Manabu, 2023. "Feasible Panel GARCH Models: Variance-Targeting Estimation and Empirical Application," Econometrics and Statistics, Elsevier, vol. 25(C), pages 23-38.
    10. Qi Li & Fukang Zhu, 2020. "Mean targeting estimator for the integer-valued GARCH(1, 1) model," Statistical Papers, Springer, vol. 61(2), pages 659-679, April.
    11. Christian T. Brownlees & Fabrizio Cipollini & Giampiero M. Gallo, 2011. "Multiplicative Error Models," Econometrics Working Papers Archive 2011_03, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti", revised Apr 2011.
    12. Francq, C. & Jiménez-Gamero, M.D. & Meintanis, S.G., 2017. "Tests for conditional ellipticity in multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 196(2), pages 305-319.

  101. Shintani, Mototsugu & Linton, Oliver, 2004. "Nonparametric neural network estimation of Lyapunov exponents and a direct test for chaos," Journal of Econometrics, Elsevier, vol. 120(1), pages 1-33, May.
    See citations under working paper version above.
  102. Xiao Z. & Linton O.B. & Carroll R.J. & Mammen E., 2003. "More Efficient Local Polynomial Estimation in Nonparametric Regression With Autocorrelated Errors," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 980-992, January.

    Cited by:

    1. David Jacho-Chavez & Arthur Lewbel & Oliver Linton, 2006. "Identification and Nonparametric Estimation of a Transformed Additively Separable Model," Boston College Working Papers in Economics 652, Boston College Department of Economics, revised 26 Nov 2008.
    2. Dabo-Niang, S. & Guillas, S. & Ternynck, C., 2016. "Efficiency in multivariate functional nonparametric models with autoregressive errors," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 168-182.
    3. Stefano Magrini & Margherita Gerolimetto, 2015. "Spatial Distribution Dynamics," ERSA conference papers ersa15p1172, European Regional Science Association.
    4. Su, Liangjun & Lu, Xun, 2013. "Nonparametric dynamic panel data models: Kernel estimation and specification testing," Journal of Econometrics, Elsevier, vol. 176(2), pages 112-133.
    5. Aneiros-Perez, G. & Vilar-Fernandez, J.M., 2008. "Local polynomial estimation in partial linear regression models under dependence," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2757-2777, January.
    6. Juliane Geller & Michael H. Neumann, 2018. "Improved local polynomial estimation in time series regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 1-27, January.
    7. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Short-Term Exuberance and Long-Term Stability: A Simultaneous Optimization of Stock Return Predictions for Short and Long Horizons," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    8. Alan T. K. Wan & Jinhong You & Riquan Zhang, 2016. "A Seemingly Unrelated Nonparametric Additive Model with Autoregressive Errors," Econometric Reviews, Taylor & Francis Journals, vol. 35(5), pages 894-928, May.
    9. Ozabaci, Deniz & Henderson, Daniel J., 2014. "Additive Kernel Estimates of Returns to Schooling," IZA Discussion Papers 8736, Institute of Labor Economics (IZA).
    10. Martins-Filho, Carlos & Yao, Feng, 2009. "Nonparametric regression estimation with general parametric error covariance," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 309-333, March.
    11. Linton, O. & Xiao, Z., 2019. "Efficient Estimation of Nonparametric Regression in The Presence of Dynamic Heteroskedasticity," Cambridge Working Papers in Economics 1907, Faculty of Economics, University of Cambridge.
    12. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    13. Liu, Jun M. & Chen, Rong & Yao, Qiwei, 2010. "Nonparametric transfer function models," Journal of Econometrics, Elsevier, vol. 157(1), pages 151-164, July.
    14. Su, Liangjun & Ullah, Aman, 2008. "Local polynomial estimation of nonparametric simultaneous equations models," Journal of Econometrics, Elsevier, vol. 144(1), pages 193-218, May.
    15. Qiu, Jia & Li, Degao & You, Jinhong, 2015. "SCAD-penalized regression for varying-coefficient models with autoregressive errors," Journal of Multivariate Analysis, Elsevier, vol. 137(C), pages 100-118.
    16. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Short-Term Exuberance and long-term stability: A simultaneous optimization of stock return predictions for short and long horizons," Graz Economics Papers 2020-20, University of Graz, Department of Economics.
    17. Liangjun Su & Aman Ullah & Yun Wang, 2013. "Nonparametric regression estimation with general parametric error covariance: a more efficient two-step estimator," Empirical Economics, Springer, vol. 45(2), pages 1009-1024, October.
    18. Su, Liangjun, 2012. "Semiparametric GMM estimation of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 167(2), pages 543-560.
    19. Stanley lat‐Meng Ko & Chia Chun Lo & Liang Peng, 2025. "Can Storage Momentum and Its Difference of a Nonferrous Metal Predict Price Return?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(7), pages 831-843, July.
    20. Linton, Oliver B. & Mammen, Enno, 2008. "Nonparametric transformation to white noise," Journal of Econometrics, Elsevier, vol. 142(1), pages 241-264, January.
    21. Qiong Pang & Xijian Hu, 2024. "INLA Estimation of Semi-Variable Coefficient Spatial Lag Model—Analysis of PM2.5 Influencing Factors in the Context of Urbanization in China," Mathematics, MDPI, vol. 12(7), pages 1-24, March.
    22. Bingduo Yang & Xiaohui Liu & Liang Peng & Zongwu Cai, 2018. "Unified Tests for a Dynamic Predictive Regression," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 201808, University of Kansas, Department of Economics, revised Sep 2018.
    23. You, Jinhong & Zhou, Xian, 2006. "Statistical inference in a panel data semiparametric regression model with serially correlated errors," Journal of Multivariate Analysis, Elsevier, vol. 97(4), pages 844-873, April.
    24. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional Variance Forecasts for Long-Term Stock Returns," Risks, MDPI, vol. 7(4), pages 1-22, November.
    25. Degao Li & Guodong Li & Jinhong You, 2014. "Significant Variable Selection And Autoregressive Order Determination For Time-Series Partially Linear Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(5), pages 478-490, August.
    26. Xuemei Hu & Xiaohui Liu, 2013. "Empirical likelihood confidence regions for semi-varying coefficient models with linear process errors," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(1), pages 161-180, March.
    27. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    28. Cai, Zongwu, 2007. "Trending time-varying coefficient time series models with serially correlated errors," Journal of Econometrics, Elsevier, vol. 136(1), pages 163-188, January.
    29. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Longer-Term Forecasting of Excess Stock Returns—The Five-Year Case," Mathematics, MDPI, vol. 8(6), pages 1-20, June.
    30. Margherita Gerolimetto & Stefano Magrini, 2016. "Distribution Dynamics in the US. A Spatial Perspective," Working Papers 2016:02, Department of Economics, University of Venice "Ca' Foscari".

  103. Linton, Oliver & Perron, Benoit, 2003. "The Shape of the Risk Premium: Evidence from a Semiparametric Generalized Autoregressive Conditional Heteroscedasticity Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(3), pages 354-367, July.

    Cited by:

    1. Seok Young Hong & Oliver Linton, 2016. "Asymptotic properties of a Nadaraya-Watson type estimator for regression functions of in?finite order," CeMMAP working papers CWP53/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Conrad, Christian & Mammen , Enno, 2015. "Asymptotics for parametric GARCH-in-Mean Models," Working Papers 0579, University of Heidelberg, Department of Economics.
    3. Bent Jesper Christensen & Jie Zhu & Morten Ø. Nielsen, 2009. "Long Memory In Stock Market Volatility And The Volatility-in-mean Effect: The Fiegarch-m Model," Working Paper 1207, Economics Department, Queen's University.
    4. Hong, S-Y. & Linton, O., 2018. "Nonparametric estimation of infinite order regression and its application to the risk-return tradeoff," Cambridge Working Papers in Economics 1877, Faculty of Economics, University of Cambridge.
    5. Likai Chen & Ekaterina Smetanina & Wei Biao Wu, 2022. "Estimation of nonstationary nonparametric regression model with multiplicative structure [Income and wealth distribution in macroeconomics: A continuous-time approach]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 176-214.
    6. Jie Zhu, 2008. "FIEGARCH-M and and International Crises: A Cross-Country Analysis," CREATES Research Papers 2008-16, Department of Economics and Business Economics, Aarhus University.
    7. Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.
    8. Hafner, Christian & Kyriakopoulou, Dimitra, 2020. "Exponential-Type GARCH Models With Linear-in-Variance Risk Premium," LIDAM Reprints ISBA 2020029, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    9. Song, Zefang & Song, Xinyuan & Li, Yuan, 2023. "Bayesian Analysis of ARCH-M model with a dynamic latent variable," Econometrics and Statistics, Elsevier, vol. 28(C), pages 47-62.
    10. Jing Li, 2021. "On Estimating Risk Premium With Flexible Fourier Form," Economics Bulletin, AccessEcon, vol. 41(3), pages 1026-1035.
    11. Dias, Gustavo Fruet, 2017. "The time-varying GARCH-in-mean model," Economics Letters, Elsevier, vol. 157(C), pages 129-132.
    12. Enno Mammen & Jens Perch Nielsen & Michael Scholz & Stefan Sperlich, 2019. "Conditional Variance Forecasts for Long-Term Stock Returns," Risks, MDPI, vol. 7(4), pages 1-22, November.
    13. Linton, Oliver & Sancetta, Alessio, 2009. "Consistent estimation of a general nonparametric regression function in time series," Journal of Econometrics, Elsevier, vol. 152(1), pages 70-78, September.
    14. Peixin Zhao & Qian Jiang, 2025. "Orthogonal Weighted Empirical Likelihood Test for ARCH-M Models with Double Functional Coefficients," Methodology and Computing in Applied Probability, Springer, vol. 27(1), pages 1-12, March.

  104. Kristensen, Dennis & Linton, Oliver, 2003. "03.5.2. Consistent Standard Errors for Target Variance Approach to GARCH Estimation," Econometric Theory, Cambridge University Press, vol. 19(5), pages 879-880, October.

    Cited by:

    1. Van Dijk, Dick & Munandar, Haris & Hafner, Christian, 2011. "The Euro-introduction and non-Euro currencies," LIDAM Reprints ISBA 2011052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

  105. Xiaohong Chen & Oliver Linton & Ingrid Van Keilegom, 2003. "Estimation of Semiparametric Models when the Criterion Function Is Not Smooth," Econometrica, Econometric Society, vol. 71(5), pages 1591-1608, September.
    See citations under working paper version above.
  106. Mototsugu Shintani & Oliver Linton, 2003. "Is There Chaos in the World Economy? A Nonparametric Test Using Consistent Standard Errors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(1), pages 331-357, February.
    See citations under working paper version above.
  107. Keith Vorkink & Douglas J. Hodgson & Oliver Linton, 2002. "Testing the capital asset pricing model efficiently under elliptical symmetry: a semiparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 617-639.
    See citations under working paper version above.
  108. Linton, Oliver, 2002. "Edgeworth approximations for semiparametric instrumental variable estimators and test statistics," Journal of Econometrics, Elsevier, vol. 106(2), pages 325-368, February.
    See citations under working paper version above.
  109. Zhijie Xiao & Oliver Linton, 2002. "A Nonparametric Prewhitened Covariance Estimator," Journal of Time Series Analysis, Wiley Blackwell, vol. 23(2), pages 215-250, March.

    Cited by:

    1. Hirukawa, Masayuki, 2010. "Nonparametric multiplicative bias correction for kernel-type density estimation on the unit interval," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 473-495, February.
    2. Iglesias, Emma M. & Linton, Oliver, 2009. "Estimation of tail thickness parameters from GJR-GARCH models," UC3M Working papers. Economics we094726, Universidad Carlos III de Madrid. Departamento de Economía.
    3. Alessandro Casini & Pierre Perron, 2021. "Prewhitened Long-Run Variance Estimation Robust to Nonstationarity," Papers 2103.02235, arXiv.org, revised Aug 2024.
    4. Bu, R. & Li, D. & Linton, O. & Wang, H., 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Janeway Institute Working Papers 2208, Faculty of Economics, University of Cambridge.
    5. Christopher Withers & Saralees Nadarajah, 2014. "Non-parametric confidence intervals for covariance and correlation," METRON, Springer;Sapienza Università di Roma, vol. 72(3), pages 283-306, October.
    6. Linton, Oliver, 2004. "Nonparametric inference for unbalanced time series data," LSE Research Online Documents on Economics 2116, London School of Economics and Political Science, LSE Library.
    7. Hirukawa, Masayuki, 2023. "Robust Covariance Matrix Estimation in Time Series: A Review," Econometrics and Statistics, Elsevier, vol. 27(C), pages 36-61.
    8. Park, Sujin & Hong, Seok Young & Linton, Oliver, 2016. "Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error," Journal of Econometrics, Elsevier, vol. 191(2), pages 325-347.
    9. Hirukawa Masayuki, 2004. "A Two-Stage Plug-In Bandwidth Selection and Its Implementation in Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Working Papers 04005, Concordia University, Department of Economics.
    10. Qunyong Wang & Na Wu, 2012. "Long-run covariance and its applications in cointegration regression," Stata Journal, StataCorp LLC, vol. 12(3), pages 525-542, September.

  110. Arthur Lewbel & Oliver Linton, 2002. "Nonparametric Censored and Truncated Regression," Econometrica, Econometric Society, vol. 70(2), pages 765-779, March.
    See citations under working paper version above.
  111. Linton, Oliver & Whang, Yoon-Jae, 2002. "Nonparametric Estimation With Aggregated Data," Econometric Theory, Cambridge University Press, vol. 18(2), pages 420-468, April.
    See citations under working paper version above.
  112. Juan Rodríguez-Poo & Oliver Linton, 2001. "Nonparametric factor analysis of residual time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 10(1), pages 161-182, June.

    Cited by:

    1. Barigozzi, Matteo & Hallin, Marc & Soccorsi, Stefano & von Sachs, Rainer, 2021. "Time-varying general dynamic factor models and the measurement of financial connectedness," Journal of Econometrics, Elsevier, vol. 222(1), pages 324-343.
    2. Cristina Amado & Annastiina Silvennoinen & Timo Ter¨asvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," NIPE Working Papers 07/2018, NIPE - Universidade do Minho.
    3. Koo, Bonsoo & Linton, Oliver, 2015. "Let’S Get Lade: Robust Estimation Of Semiparametric Multiplicative Volatility Models," Econometric Theory, Cambridge University Press, vol. 31(4), pages 671-702, August.
    4. Dhaene, Geert & Wu, Jianbin, 2020. "Incorporating overnight and intraday returns into multivariate GARCH volatility models," Journal of Econometrics, Elsevier, vol. 217(2), pages 471-495.
    5. Aslanidis, Nektarios & Casas, Isabel, 2013. "Nonparametric correlation models for portfolio allocation," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2268-2283.
    6. Su, Liangjun & Wang, Xia, 2017. "On time-varying factor models: Estimation and testing," Journal of Econometrics, Elsevier, vol. 198(1), pages 84-101.
    7. Hafner, Christian M. & Linton, Oliver, 2010. "Efficient estimation of a multivariate multiplicative volatility model," Journal of Econometrics, Elsevier, vol. 159(1), pages 55-73, November.
    8. Hafner, C.M. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 2005. "Semi-Parametric Modelling of Correlation Dynamics," Econometric Institute Research Papers EI 2005-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

  113. Linton, Oliver, 2001. "ESTIMATING ADDITIVE NONPARAMETRIC MODELS BY PARTIAL Lq NORM: THE CURSE OF FRACTIONALITY," Econometric Theory, Cambridge University Press, vol. 17(6), pages 1037-1050, December.
    See citations under working paper version above.
  114. Linton, Oliver & Mammen, Enno & Nielsen, Jans Perch & Tanggaard, Carsten, 2001. "Yield curve estimation by kernel smoothing methods," Journal of Econometrics, Elsevier, vol. 105(1), pages 185-223, November.
    See citations under working paper version above.
  115. Linton, Oliver & Xiao, Zhijie, 2001. "Second-Order Approximation For Adaptive Regression Estimators," Econometric Theory, Cambridge University Press, vol. 17(5), pages 984-1024, October.
    See citations under working paper version above.
  116. Gozalo, Pedro L. & Linton, Oliver B., 2001. "Testing additivity in generalized nonparametric regression models with estimated parameters," Journal of Econometrics, Elsevier, vol. 104(1), pages 1-48, August.

    Cited by:

    1. M.L. Nores & M.P. Díaz, 2016. "Bootstrap hypothesis testing in generalized additive models for comparing curves of treatments in longitudinal studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 810-826, April.
    2. Tadao Hoshino, 2014. "Quantile regression estimation of partially linear additive models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(3), pages 509-536, September.
    3. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers CWP20/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. David Jacho-Chavez & Arthur Lewbel & Oliver Linton, 2006. "Identification and Nonparametric Estimation of a Transformed Additively Separable Model," Boston College Working Papers in Economics 652, Boston College Department of Economics, revised 26 Nov 2008.
    5. Lawrence Dacuycuy, 2005. "On distribution approximation: a simple comparative study on procedural variations of the Zheng test," Economics Bulletin, AccessEcon, vol. 3(11), pages 1-10.
    6. Wenceslao González-Manteiga & Rosa Crujeiras, 2013. "An updated review of Goodness-of-Fit tests for regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(3), pages 361-411, September.
    7. Joel L. Horowitz & Sokbae (Simon) Lee, 2004. "Nonparametric estimation of an additive quantile regression model," CeMMAP working papers CWP07/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Bontemps, Christophe & Simioni, Michel & Surry, Yves R., 2005. "Hedonic Housing Prices and Agricultural Pollution: An Empirical Investigation on Semiparametric Models," 2005 International Congress, August 23-27, 2005, Copenhagen, Denmark 24709, European Association of Agricultural Economists.
    9. Christophe Bontemps & Michel Simioni & Yves Surry, 2008. "Semiparametric hedonic price models: assessing the effects of agricultural nonpoint source pollution," Post-Print hal-02661292, HAL.
    10. Centorrino, Samuele & Parmeter, Christopher F., 2024. "Nonparametric estimation of stochastic frontier models with weak separability," Journal of Econometrics, Elsevier, vol. 238(2).
    11. Zhang, Chunming & Dette, Holger, 2004. "A power comparison between nonparametric regression tests," Statistics & Probability Letters, Elsevier, vol. 66(3), pages 289-301, February.
    12. Lawrence Dacuycuy, 2006. "Explaining male wage inequality in the Philippines: non-parametric and semiparametric approaches," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2497-2511.
    13. Arthur Lewbel & Xun Lu & Liangjun Su, 2012. "Specification Testing for Transformation Models with an Application to Generalized Accelerated Failure-time Models," Boston College Working Papers in Economics 817, Boston College Department of Economics, revised 01 May 2013.
    14. Joel L. Horowitz, 2012. "Nonparametric additive models," CeMMAP working papers 20/12, Institute for Fiscal Studies.
    15. Gao, Jiti & King, Maxwell, 2003. "Estimation and model specification testing in nonparametric and semiparametric econometric models," MPRA Paper 11989, University Library of Munich, Germany, revised Feb 2006.
    16. Debbarh, Mohammed & Viallon, Vivian, 2008. "Testing additivity in nonparametric regression under random censorship," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2584-2591, November.
    17. Connor, Gregory & Hagmann, Matthias & Linton, Oliver, 2007. "Efficient estimation of a semiparametric characteristic-based factor model of security returns," LSE Research Online Documents on Economics 24504, London School of Economics and Political Science, LSE Library.
    18. Lu, Xun & White, Halbert, 2014. "Testing for separability in structural equations," Journal of Econometrics, Elsevier, vol. 182(1), pages 14-26.
    19. Jorge Barrientos Marin, 2006. "Estimation And Testing An Additive Partially Linear Model In A System Of Engel Curves," Working Papers. Serie AD 2006-23, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    20. Hall, Peter & Yatchew, Adonis, 2005. "Unified approach to testing functional hypotheses in semiparametric contexts," Journal of Econometrics, Elsevier, vol. 127(2), pages 225-252, August.
    21. Wang, Taining & Zhang, Xiaoqi & Tian, Jinjing, 2025. "A Consistent Estimator for Model Structure and Variable Selection," Econometrics and Statistics, Elsevier, vol. 34(C), pages 44-68.
    22. Germán Aneiros-Pérez & Philippe Vieu, 2013. "Testing linearity in semi-parametric functional data analysis," Computational Statistics, Springer, vol. 28(2), pages 413-434, April.
    23. Zhang, Chunming & Dette, Holger, 2003. "A power comparison between nonparametric regression tests," Technical Reports 2003,22, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    24. Li, Qi & Hsiao, Cheng & Zinn, Joel, 2003. "Consistent specification tests for semiparametric/nonparametric models based on series estimation methods," Journal of Econometrics, Elsevier, vol. 112(2), pages 295-325, February.
    25. Neumeyer, Natalie & Van Keilegom, Ingrid, 2010. "Estimating the error distribution in nonparametric multiple regression with applications to model testing," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1067-1078, May.
    26. Holger Dette & Matthias Guhlich & Natalie Neumeyer, 2015. "Testing for additivity in nonparametric quantile regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(3), pages 437-477, June.
    27. Nitschka Thomas & Markov Nikolay, 2016. "Semi-Parametric Estimates of Taylor Rules for a Small, Open Economy – Evidence from Switzerland," German Economic Review, De Gruyter, vol. 17(4), pages 478-490, December.
    28. Pascal Lavergne & Valentin Patilea, 2006. "Breaking the Curse of Dimensionality in Nonparametric Testing," Working Papers 2006-24, Center for Research in Economics and Statistics.
    29. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    30. Jorge Barrientos Marín, 2005. "A note on the Bandwidth choice when the null hypothesis is semiparametric," Revista de Economía del Rosario, Universidad del Rosario.
    31. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.
    32. Felix Abramovich & Italia Feis & Theofanis Sapatinas, 2009. "Optimal testing for additivity in multiple nonparametric regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(3), pages 691-714, September.
    33. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    34. Daniel J. Henderson & Christopher F. Parmeter & Liangjun Su, 2017. "M-Estimation of a Nonparametric Threshold Regression Model," Working Papers 2017-15, University of Miami, Department of Economics.

  117. Linton, Oliver B., 2000. "Efficient Estimation Of Generalized Additive Nonparametric Regression Models," Econometric Theory, Cambridge University Press, vol. 16(4), pages 502-523, August.
    See citations under working paper version above.
  118. Oliver Linton & Douglas Steigerwald, 2000. "Adaptive testing in arch models," Econometric Reviews, Taylor & Francis Journals, vol. 19(2), pages 145-174.
    See citations under working paper version above.
  119. Gozalo, Pedro & Linton, Oliver, 2000. "Local nonlinear least squares: Using parametric information in nonparametric regression," Journal of Econometrics, Elsevier, vol. 99(1), pages 63-106, November.

    Cited by:

    1. Hagmann, M. & Scaillet, O., 2007. "Local multiplicative bias correction for asymmetric kernel density estimators," Journal of Econometrics, Elsevier, vol. 141(1), pages 213-249, November.
    2. Bourdon, Jean & Michaelowa, Katharina & Frölich, Markus, 2007. "Teacher shortages, teacher contracts and their impact on education in Africa," HWWI Research Papers 2-10, Hamburg Institute of International Economics (HWWI).
    3. Kumbhakar, Subal & Tsionas, Efthymios, 2003. "Recent Developments in Stochastic Frontier Modeling," Efficiency Series Papers 2003/06, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    4. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    5. Dette, Holger & Wieczorek, Gabriele, 2007. "Testing for a constant coefficient of variation in nonparametric regression," Technical Reports 2007,36, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    6. Frölich, Markus & Michaelowa, Katharina, 2005. "Peer Effects and Textbooks in Primary Education: Evidence from Francophone Sub-Saharan Africa," IZA Discussion Papers 1519, Institute of Labor Economics (IZA).
    7. Eduardo Fé-Rodríguez & Richard Hofler, 2009. "Count Data Stochastic Frontier Models, with an application to the patents-R&D Relationship," Economics Discussion Paper Series 0916, Economics, The University of Manchester.
    8. Theofanis P. Mamuneas & Andreas Savvides & Thanasis Stengos, 2006. "Economic development and the return to human capital: a smooth coefficient semiparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 111-132, January.
    9. Lewbel, Arthur & McFadden, Daniel & Linton, Oliver, 2011. "Estimating features of a distribution from binomial data," Journal of Econometrics, Elsevier, vol. 162(2), pages 170-188, June.
    10. Peter C.B. Phillips & Ke-Li Xu, 2007. "Tilted Nonparametric Estimation of Volatility Functions," Cowles Foundation Discussion Papers 1612, Cowles Foundation for Research in Economics, Yale University, revised Jul 2010.
    11. Valentin Zelenyuk & Leopold Simar, 2011. "To Smooth or Not to Smooth? The Case of Discrete Variables in Nonparametric Regressions," CEPA Working Papers Series WP102011, School of Economics, University of Queensland, Australia.
    12. Li, S. & Linton, O., 2020. "When will the Covid-19 pandemic peak?," Cambridge Working Papers in Economics 2025, Faculty of Economics, University of Cambridge.
    13. Kien Tran & Efthymios Tsionas, 2010. "Local GMM Estimation of Semiparametric Panel Data with Smooth Coefficient Models," Econometric Reviews, Taylor & Francis Journals, vol. 29(1), pages 39-61.
    14. Li, Degui & Simar, Leopold & Zelenyuk, Valentin, 2016. "Generalized nonparametric smoothing with mixed discrete and continuous data," LIDAM Reprints ISBA 2016020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    15. Talamakrouni, Majda & El Ghouch, Anouar & Van Keilegom, Ingrid, 2012. "Guided censored regression," LIDAM Discussion Papers ISBA 2012023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    16. D. F. Benoit & D. Van Den Poel, 2010. "Binary quantile regression: A Bayesian approach based on the asymmetric Laplace density," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 10/662, Ghent University, Faculty of Economics and Business Administration.
    17. Centorrino, Samuele & Florens, Jean-Pierre, 2021. "Nonparametric Instrumental Variable Estimation of Binary Response Models with Continuous Endogenous Regressors," Econometrics and Statistics, Elsevier, vol. 17(C), pages 35-63.
    18. Lewbel, Arthur, 2007. "A local generalized method of moments estimator," Economics Letters, Elsevier, vol. 94(1), pages 124-128, January.
    19. Wrenn, Douglas H. & Sam, Abdoul G., 2014. "Geographically and temporally weighted likelihood regression: Exploring the spatiotemporal determinants of land use change," Regional Science and Urban Economics, Elsevier, vol. 44(C), pages 60-74.
    20. Florios, Kostas & Skouras, Spyros, 2008. "Exact computation of max weighted score estimators," Journal of Econometrics, Elsevier, vol. 146(1), pages 86-91, September.
    21. Xiangdong Long & Liangjun Su & Aman Ullah, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 109-125, January.
    22. Temel, T. & Lucas, A., 2005. "Deepening the Measuring of Technical Inefficiency in Private Farming in Georgia: Locally Parametric Regression," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 2(1), pages 115-138.
    23. Caraveli, H. & Tsionas, E.G., 2009. "Where in the U-shaped Curve Is Europe Found? An Empirical Analysis of Centre-Periphery in the E.U," The Journal of Economic Asymmetries, Elsevier, vol. 6(1), pages 75-88.
    24. Tsionas, Euthimios G. & Mamatzakis, Emmanuel C., 2017. "Adjustment costs in the technical efficiency: An application to global banking," European Journal of Operational Research, Elsevier, vol. 256(2), pages 640-649.
    25. Rothe, Christoph & Firpo, Sergio, 2013. "Semiparametric Estimation and Inference Using Doubly Robust Moment Conditions," IZA Discussion Papers 7564, Institute of Labor Economics (IZA).
    26. Xu, Ke-Li & Phillips, Peter C. B., 2011. "Tilted Nonparametric Estimation of Volatility Functions With Empirical Applications," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(4), pages 518-528.
    27. Puhani, Patrick & Fröhlich, Markus, 2002. "Immigration and Heterogeneous Labour in Western Germany: A Labour Market Classification Based on Nonparametric Estimation," CEPR Discussion Papers 3158, C.E.P.R. Discussion Papers.
    28. Artem Prokhorov & Kien C. Tran & Mike G. Tsionas, 2021. "Estimation of semi- and nonparametric stochastic frontier models with endogenous regressors," Empirical Economics, Springer, vol. 60(6), pages 3043-3068, June.
    29. Majda Talamakrouni & Anouar El Ghouch & Ingrid Van Keilegom, 2015. "Guided Censored Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 214-233, March.
    30. Dong, Yingying & Lewbel, Arthur, 2011. "Nonparametric identification of a binary random factor in cross section data," Journal of Econometrics, Elsevier, vol. 163(2), pages 163-171, August.
    31. McCloud, Nadine & Parmeter, Christopher F., 2020. "Determining the Number of Effective Parameters in Kernel Density Estimation," Computational Statistics & Data Analysis, Elsevier, vol. 143(C).
    32. Sancetta, Alessio, 2013. "Weak conditions for shrinking multivariate nonparametric density estimators," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 285-300.
    33. Yixiao Sun & Peter C.B. Phillips, 2002. "Nonlinear Log-Periodogram Regression for Perturbed Fractional Processes," Cowles Foundation Discussion Papers 1366, Cowles Foundation for Research in Economics, Yale University.
    34. El Ghouch, Anouar & Genton, Marc G., 2009. "Local Polynomial Quantile Regression With Parametric Features," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1416-1429.

  120. Stefan Sperlich & Oliver Linton & Wolfgang Härdle, 1999. "Integration and backfitting methods in additive models-finite sample properties and comparison," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 8(2), pages 419-458, December.
    See citations under working paper version above.
  121. Whang, Yoon-Jae & Linton, Oliver, 1999. "The asymptotic distribution of nonparametric estimates of the Lyapunov exponent for stochastic time series," Journal of Econometrics, Elsevier, vol. 91(1), pages 1-42, July.
    See citations under working paper version above.
  122. J. P. Nielsen & O. B. Linton, 1998. "An optimization interpretation of integration and back‐fitting estimators for separable nonparametric models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(1), pages 217-222.
    See citations under working paper version above.
  123. Linton, Oliver, 1997. "An Asymptotic Expansion in the GARCH(l, 1) Model," Econometric Theory, Cambridge University Press, vol. 13(4), pages 558-581, February.
    See citations under working paper version above.
  124. Linton, Oliver, 1996. "Edgeworth Approximation for MINPIN Estimators in Semiparametric Regression Models," Econometric Theory, Cambridge University Press, vol. 12(1), pages 30-60, March.
    See citations under working paper version above.
  125. Linton, Oliver, 1995. "Second Order Approximation in the Partially Linear Regression Model," Econometrica, Econometric Society, vol. 63(5), pages 1079-1112, September.
    See citations under working paper version above.
  126. Linton, Oliver & Nielsen, Jens Perch, 1994. "A multiplicative bias reduction method for nonparametric regression," Statistics & Probability Letters, Elsevier, vol. 19(3), pages 181-187, February.

    Cited by:

    1. Scholz, Michael & Nielsen, Jens Perch & Sperlich, Stefan, 2015. "Nonparametric prediction of stock returns based on yearly data: The long-term view," Insurance: Mathematics and Economics, Elsevier, vol. 65(C), pages 143-155.
    2. Hirukawa, Masayuki, 2010. "Nonparametric multiplicative bias correction for kernel-type density estimation on the unit interval," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 473-495, February.
    3. Wenzhuan Zhang & Yingcun Xia, 2012. "Twicing local linear kernel regression smoothers," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(2), pages 399-417.
    4. Yao, Weixin, 2012. "A bias corrected nonparametric regression estimator," Statistics & Probability Letters, Elsevier, vol. 82(2), pages 274-282.
    5. Jens Perch Nielsen & Carsten Tanggaard & M.C. Jones, 2007. "Local Linear Density Estimation for Filtered Survival Data, with Bias Correction," CREATES Research Papers 2007-13, Department of Economics and Business Economics, Aarhus University.
    6. Funke, Benedikt & Hirukawa, Masayuki, 2021. "Bias correction for local linear regression estimation using asymmetric kernels via the skewing method," Econometrics and Statistics, Elsevier, vol. 20(C), pages 109-130.
    7. Bischofberger, Stephan M. & Hiabu, Munir & Mammen, Enno & Nielsen, Jens Perch, 2019. "A comparison of in-sample forecasting methods," Computational Statistics & Data Analysis, Elsevier, vol. 137(C), pages 133-154.
    8. Xu, Ke-Li, 2010. "Reweighted Functional Estimation Of Diffusion Models," Econometric Theory, Cambridge University Press, vol. 26(2), pages 541-563, April.
    9. Naito, Kanta & Yoshizaki, Masahiro, 2009. "Bandwidth selection for a data sharpening estimator in nonparametric regression," Journal of Multivariate Analysis, Elsevier, vol. 100(7), pages 1465-1486, August.
    10. Nielsen, Jens Perch & Tanggaard, Carsten & Jones, M. C., 2003. "Local Linear Density Estimation for Filtered Survival Data, with Bias Correction," Finance Working Papers 03-9, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    11. Perch Nielsen, Jens & Tanggaard, Carsten, 2000. "Boundary and Bias Correction in Kernel Hazard Estimation," Finance Working Papers 00-7, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    12. Oliver Linton, 1997. "Second Order Approximation in a Linear Regression with Heteroskedasticity for Unknown Form," Cowles Foundation Discussion Papers 1151, Cowles Foundation for Research in Economics, Yale University.

  127. Linton, Oliver, 1993. "Adaptive Estimation in ARCH Models," Econometric Theory, Cambridge University Press, vol. 9(4), pages 539-569, August.
    See citations under working paper version above.

Chapters

  1. Hardle, Wolfgang & Linton, Oliver, 1986. "Applied nonparametric methods," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 38, pages 2295-2339, Elsevier.
    See citations under working paper version above.Sorry, no citations of chapters recorded.

Books

  1. Linton,Oliver, 2019. "Financial Econometrics," Cambridge Books, Cambridge University Press, number 9781107177154, November.

    Cited by:

    1. Lajos Horváth & Hemei Li & Zhenya Liu, 2021. "How to identify the different phases of stock market bubbles statistically?," Post-Print hal-03511435, HAL.
    2. Kristina Bluwstein & Alba Patozi, 2024. "The effects of macroprudential policy announcements on systemic risk," Bank of England working papers 1080, Bank of England.
    3. Ge, S. & Li, S. & Linton, O. B. & Liu, W. & Su, W., 2024. "Should We Augment Large Covariance Matrix Estimation with Auxiliary Network Information?," Cambridge Working Papers in Economics 2427, Faculty of Economics, University of Cambridge.
    4. Cui, Wenhao & Hu, Jie & Wang, Jiandong, 2024. "Nonparametric estimation for high-frequency data incorporating trading information," Journal of Econometrics, Elsevier, vol. 240(1).
    5. Steven Campbell & Qien Song & Ting-Kam Leonard Wong, 2024. "Macroscopic properties of equity markets: stylized facts and portfolio performance," Papers 2409.10859, arXiv.org, revised Apr 2025.
    6. Daniel S. Hamermesh & Gerard A. Pfann, 2022. "The Variability and Volatility of Sleep: An ARCHetypal Behavior," NBER Working Papers 29658, National Bureau of Economic Research, Inc.

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