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Dennis Kristensen

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.

Working papers

  1. Mogens Fosgerau & Dennis Kristensen, 2020. "Identification of a class of index models: A topological approach," Papers 2004.07900, arXiv.org.

    Cited by:

    1. 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.
    2. Sørensen, Jesper R.-V. & Fosgerau, Mogens, 2022. "How McFadden met Rockafellar and learned to do more with less," Journal of Mathematical Economics, Elsevier, vol. 100(C).

  2. Dennis Kristensen & Young Jun Lee, 2019. "Local Polynomial Estimation of Time-Varying Parameters in Nonlinear Models," Papers 1904.05209, arXiv.org, revised Aug 2023.

    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.

  3. Dennis Kristensen & Patrick K. Mogensen & Jong Myun Moon & Bertel Schjerning, 2019. "Solving Dynamic Discrete Choice Models Using Smoothing and Sieve Methods," Papers 1904.05232, arXiv.org, revised Feb 2020.

    Cited by:

    1. Norets, Andriy & Shimizu, Kenichi, 2024. "Semiparametric Bayesian estimation of dynamic discrete choice models," Journal of Econometrics, Elsevier, vol. 238(2).
    2. Jackson Bunting, 2022. "Continuous permanent unobserved heterogeneity in dynamic discrete choice models," Papers 2202.03960, arXiv.org, revised Feb 2024.
    3. Yao Luo & Peijun Sang, 2022. "Penalized Sieve Estimation of Structural Models," Papers 2204.13488, arXiv.org.
    4. Thomas J. Sargent & John Stachurski, 2024. "Dynamic Programming: Finite States," Papers 2401.10473, arXiv.org.

  4. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers 60/17, Institute for Fiscal Studies.

    Cited by:

    1. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    2. Steven T. Berry & Philip A. Haile, 2021. "Foundations of Demand Estimation," NBER Working Papers 29305, National Bureau of Economic Research, Inc.
    3. Victor H. Aguiar & Nail Kashaev & Roy Allen, 2022. "Prices, Profits, Proxies, and Production," University of Western Ontario, Departmental Research Report Series 20226, University of Western Ontario, Department of Economics.
    4. Roy Allen, 2019. "Injectivity and the Law of Demand," Papers 1908.05714, arXiv.org.
    5. Christopher Dobronyi & Christian Gouri'eroux, 2020. "Consumer Theory with Non-Parametric Taste Uncertainty and Individual Heterogeneity," Papers 2010.13937, arXiv.org, revised Jan 2021.
    6. Hubner, Stefan, 2023. "Identification of unobserved distribution factors and preferences in the collective household model," Journal of Econometrics, Elsevier, vol. 234(1), pages 301-326.
    7. Haruki Kono, 2024. "Local Identification in Instrumental Variable Multivariate Quantile Regression Models," Papers 2401.11422, arXiv.org, revised Jun 2024.
    8. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.

  5. Michael Creel & Jiti Gao & Han Hong & Dennis Kristensen, 2016. "Bayesian Indirect Inference and the ABC of GMM," Monash Econometrics and Business Statistics Working Papers 1/16, Monash University, Department of Econometrics and Business Statistics.

    Cited by:

    1. Jean-Jacques Forneron & Serena Ng, 2015. "The ABC of Simulation Estimation with Auxiliary Statistics," Papers 1501.01265, arXiv.org, revised Oct 2017.
    2. Valerio Scalone, 2018. "Estimating Non-Linear DSGEs with the Approximate Bayesian Computation: an application to the Zero Lower Bound," Working papers 688, Banque de France.

  6. Arianna Agosto & Giuseppe Cavaliere & Dennis Kristensen & Anders Rahbek, 2015. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," CREATES Research Papers 2015-11, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Escribano, Ana & Maggi, Mario, 2019. "Intersectoral default contagion: A multivariate Poisson autoregression analysis," Economic Modelling, Elsevier, vol. 82(C), pages 376-400.
    2. Huaping Chen, 2023. "A New Soft-Clipping Discrete Beta GARCH Model and Its Application on Measles Infection," Stats, MDPI, vol. 6(1), pages 1-19, February.
    3. Huaping Chen & Qi Li & Fukang Zhu, 2023. "A covariate-driven beta-binomial integer-valued GARCH model for bounded counts with an application," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(7), pages 805-826, October.
    4. Arianna Agosto & Paolo Giudici, 2020. "A Poisson Autoregressive Model to Understand COVID-19 Contagion Dynamics," Risks, MDPI, vol. 8(3), pages 1-8, July.
    5. Giovanni Angelini & Luca De Angelis, 2017. "PARX model for football match predictions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(7), pages 795-807, November.
    6. Paolo Gorgi & Siem Jan Koopman, 2020. "Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects," Tinbergen Institute Discussion Papers 20-004/III, Tinbergen Institute.
    7. Stefano Cabras, 2021. "A Bayesian-Deep Learning Model for Estimating COVID-19 Evolution in Spain," Mathematics, MDPI, vol. 9(22), pages 1-18, November.
    8. Cavaliere, Giuseppe & Nielsen, Heino Bohn & Pedersen, Rasmus Søndergaard & Rahbek, Anders, 2022. "Bootstrap inference on the boundary of the parameter space, with application to conditional volatility models," Journal of Econometrics, Elsevier, vol. 227(1), pages 241-263.
    9. Rémy Garnier, 2022. "Concurrent neural network: a model of competition between times series," Annals of Operations Research, Springer, vol. 313(2), pages 945-964, June.
    10. Dennis Kristensen & Young Jun Lee, 2019. "Local Polynomial Estimation of Time-Varying Parameters in Nonlinear Models," Papers 1904.05209, arXiv.org, revised Aug 2023.
    11. Cavaliere, Giuseppe & Lu, Ye & Rahbek, Anders & Stærk-Østergaard, Jacob, 2023. "Bootstrap inference for Hawkes and general point processes," Journal of Econometrics, Elsevier, vol. 235(1), pages 133-165.
    12. Christis Katsouris, 2024. "Robust Estimation in Network Vector Autoregression with Nonstationary Regressors," Papers 2401.04050, arXiv.org.
    13. Lu, Ye & Suthaharan, Neyavan, 2023. "Electricity price spike clustering: A zero-inflated GARX approach," Energy Economics, Elsevier, vol. 124(C).
    14. Maia, Gisele de Oliveira & Barreto-Souza, Wagner & Bastos, Fernando de Souza & Ombao, Hernando, 2021. "Semiparametric time series models driven by latent factor," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1463-1479.
    15. Arianna Agosto & Paolo Giudici, 2020. "COVID-19 contagion and digital finance," Digital Finance, Springer, vol. 2(1), pages 159-167, September.
    16. Aknouche, Abdelhakim & Francq, Christian, 2018. "Count and duration time series with equal conditional stochastic and mean orders," MPRA Paper 90838, University Library of Munich, Germany.
    17. Geir D. Berentsen & Jan Bulla & Antonello Maruotti & Bård Støve, 2022. "Modelling clusters of corporate defaults: Regime‐switching models significantly reduce the contagion source," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 698-722, June.
    18. Giovanni Angelini & Giuseppe Cavaliere & Enzo D'Innocenzo & Luca De Angelis, 2022. "Time-Varying Poisson Autoregression," Papers 2207.11003, arXiv.org.
    19. Wang, Xiaoting & Hou, Siyuan & Shen, Jie, 2021. "Default clustering of the nonfinancial sector and systemic risk: Evidence from China," Economic Modelling, Elsevier, vol. 96(C), pages 196-208.
    20. Weiß, Christian H. & Zhu, Fukang, 2024. "Conditional-mean multiplicative operator models for count time series," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
    21. Yang, Kai & Yu, Xinyang & Zhang, Qingqing & Dong, Xiaogang, 2022. "On MCMC sampling in self-exciting integer-valued threshold time series models," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    22. Rasmus Soendergaard Pedersen & Anders Rahbek, 2017. "Testing Garch-X Type Models," Discussion Papers 17-15, University of Copenhagen. Department of Economics.
    23. Giuseppe Cavaliere & Indeewara Perera & Anders Rahbek, 2021. "Specification tests for GARCH processes," Discussion Papers 21-06, University of Copenhagen. Department of Economics.
    24. 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.
    25. Huaping Chen & Qi Li & Fukang Zhu, 2022. "A new class of integer-valued GARCH models for time series of bounded counts with extra-binomial variation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 243-270, June.
    26. Giada Adelfio & Arianna Agosto & Marcello Chiodi & Paolo Giudici, 2021. "Financial contagion through space-time point processes," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 665-688, June.
    27. Gagliardini, Patrick & Gouriéroux, Christian, 2019. "Identification by Laplace transforms in nonlinear time series and panel models with unobserved stochastic dynamic effects," Journal of Econometrics, Elsevier, vol. 208(2), pages 613-637.
    28. Mengya Liu & Qi Li & Fukang Zhu, 2020. "Self-excited hysteretic negative binomial autoregression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 385-415, September.
    29. Randal Douc & François Roueff & Tepmony Sim, 2021. "Necessary and sufficient conditions for the identifiability of observation‐driven models," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(2), pages 140-160, March.

  7. Michael Creel & Dennis Kristensen, 2015. "On Selection of Statistics for Approximate Bayesian Computing or the Method of Simulated Moments," UFAE and IAE Working Papers 950.15, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 27 Feb 2015.

    Cited by:

    1. Vincent Boucher, 2017. "The Estimation of Network Formation Games with Positive Spillovers," Cahiers de recherche 1710, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    2. Boucher, Vincent, 2020. "Equilibrium homophily in networks," European Economic Review, Elsevier, vol. 123(C).
    3. Valerio Scalone, 2018. "Estimating Non-Linear DSGEs with the Approximate Bayesian Computation: an application to the Zero Lower Bound," Working papers 688, Banque de France.
    4. Michael Creel & Jiti Gao & Han Hong & Dennis Kristensen, 2016. "Bayesian Indirect Inference and the ABC of GMM," Monash Econometrics and Business Statistics Working Papers 1/16, Monash University, Department of Econometrics and Business Statistics.
    5. Creel, Michael, 2017. "Neural nets for indirect inference," Econometrics and Statistics, Elsevier, vol. 2(C), pages 36-49.
    6. Michael Creel, 2016. "Neural Nets for Indirect Inference," UFAE and IAE Working Papers 960.16, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 18 Jul 2016.

  8. Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Kanaya, Shin & Kristensen, Dennis, 2016. "Estimation Of Stochastic Volatility Models By Nonparametric Filtering," Econometric Theory, Cambridge University Press, vol. 32(4), pages 861-916, August.
    2. David T. Frazier & Gael M. Martin & Ruben Loaiza-Maya, 2022. "Variational Bayes in State Space Models: Inferential and Predictive Accuracy," Monash Econometrics and Business Statistics Working Papers 1/22, Monash University, Department of Econometrics and Business Statistics.
    3. Gael M. Martin & Brendan P.M. McCabe & David T. Frazier & Worapree Maneesoonthorn & Christian P. Robert, 2016. "Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models," Monash Econometrics and Business Statistics Working Papers 09/16, Monash University, Department of Econometrics and Business Statistics.
    4. Hsiang-Hsi Liu & Yu-Cheng Lin, 2021. "Relationships among US S&P500 Stock Index, its Futures and NASDAQ Index Futures with Volatility Spillover and Jump Diffusion: Modeling and Hedging Performance," Bulletin of Applied Economics, Risk Market Journals, vol. 8(1), pages 121-148.
    5. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
    6. Chaya Weerasinghe & Ruben Loaiza-Maya & Gael M. Martin & David T. Frazier, 2023. "ABC-based Forecasting in State Space Models," Monash Econometrics and Business Statistics Working Papers 12/23, Monash University, Department of Econometrics and Business Statistics.
    7. Michael Creel & Dennis Kristensen, 2015. "On Selection of Statistics for Approximate Bayesian Computing or the Method of Simulated Moments," UFAE and IAE Working Papers 950.15, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 27 Feb 2015.
    8. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    9. Michael Creel, 2021. "Inference Using Simulated Neural Moments," Econometrics, MDPI, vol. 9(4), pages 1-15, September.
    10. David T. Frazier & Gael M. Martin & Christian P. Robert, 2015. "On Consistency of Approximate Bayesian Computation," Monash Econometrics and Business Statistics Working Papers 19/15, Monash University, Department of Econometrics and Business Statistics.
    11. David T. Frazier & Worapree Maneesoonthorn & Gael M. Martin & Brendan P.M. McCabe, 2018. "Approximate Bayesian forecasting," Monash Econometrics and Business Statistics Working Papers 2/18, Monash University, Department of Econometrics and Business Statistics.
    12. Jan Pospíšil & Tomáš Sobotka & Philipp Ziegler, 2019. "Robustness and sensitivity analyses for stochastic volatility models under uncertain data structure," Empirical Economics, Springer, vol. 57(6), pages 1935-1958, December.
    13. Gael M. Martin & Brendan P.M. McCabe & Worapree Maneesoonthorn & Christian P. Robert, 2014. "Approximate Bayesian Computation in State Space Models," Monash Econometrics and Business Statistics Working Papers 20/14, Monash University, Department of Econometrics and Business Statistics.
    14. D T Frazier & G M Martin & C P Robert & J Rousseau, 2018. "Asymptotic properties of approximate Bayesian computation," Biometrika, Biometrika Trust, vol. 105(3), pages 593-607.
    15. Creel, Michael, 2017. "Neural nets for indirect inference," Econometrics and Statistics, Elsevier, vol. 2(C), pages 36-49.
    16. Jan Posp'iv{s}il & Tom'av{s} Sobotka & Philipp Ziegler, 2019. "Robustness and sensitivity analyses for stochastic volatility models under uncertain data structure," Papers 1912.06709, arXiv.org.
    17. Michael Creel, 2016. "A Note on Julia and MPI, with Code Examples," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 535-546, October.

  9. Michael Creel & Dennis Kristensen, 2013. "Indirect Likelihood Inference (revised)," UFAE and IAE Working Papers 931.13, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).

    Cited by:

    1. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    2. Jean-Jacques Forneron & Serena Ng, 2015. "The ABC of Simulation Estimation with Auxiliary Statistics," Papers 1501.01265, arXiv.org, revised Oct 2017.
    3. Michael Creel & Dennis Kristensen, 2015. "On Selection of Statistics for Approximate Bayesian Computing or the Method of Simulated Moments," UFAE and IAE Working Papers 950.15, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 27 Feb 2015.
    4. Bertl Johanna & Ewing Gregory & Kosiol Carolin & Futschik Andreas, 2017. "Approximate maximum likelihood estimation for population genetic inference," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(5-6), pages 291-312, December.
    5. Valerio Scalone, 2015. "Estimating Non-Linear DSGEs with the Approximate Bayesian Computation: an application to the Zero Lower Bound," Working Papers 6/15, Sapienza University of Rome, DISS.
    6. Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.
    7. Martin M. Andreasen & Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez, 2013. "The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications," CREATES Research Papers 2013-12, Department of Economics and Business Economics, Aarhus University.
    8. Blasques, Francisco & Duplinskiy, Artem, 2018. "Penalized indirect inference," Journal of Econometrics, Elsevier, vol. 205(1), pages 34-54.
    9. Michael Creel, 2016. "A Note on Julia and MPI, with Code Examples," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 535-546, October.

  10. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers 45/13, Institute for Fiscal Studies.

    Cited by:

    1. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and Time Effects in Nonlinear Panel Models with Large N, T," Papers 1311.7065, arXiv.org, revised Dec 2018.
    2. Freyberger, Joachim, 2015. "Asymptotic theory for differentiated products demand models with many markets," Journal of Econometrics, Elsevier, vol. 185(1), pages 162-181.
    3. 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.
    4. Dennis Kristensen & Patrick K. Mogensen & Jong Myun Moon & Bertel Schjerning, 2019. "Solving Dynamic Discrete Choice Models Using Smoothing and Sieve Methods," Papers 1904.05232, arXiv.org, revised Feb 2020.
    5. Sanghyeok Lee & Tue Gørgens, 2022. "Using maximum simulated likelihood methods to overcome left censoring: Dynamic event history models of heart attack risk in New Zealand," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 348-376, January.
    6. Jack Britton & Ben Waltmann, 2021. "Revisiting the solution of dynamic discrete choice models: time to bring back Keane and Wolpin (1994)?," IFS Working Papers W21/13, Institute for Fiscal Studies.
    7. Abhimanyu Gupta, 2020. "Efficient closed-form estimation of large spatial autoregressions," Papers 2008.12395, arXiv.org, revised May 2021.
    8. Isaiah Andrews & Matthew Gentzkow & Jesse M. Shapiro, 2014. "Measuring the Sensitivity of Parameter Estimates to Estimation Moments," NBER Working Papers 20673, National Bureau of Economic Research, Inc.
    9. Han Hong & Huiyu Li & Jessie Li, 2019. "BLP Estimation Using Laplace Transformation and Overlapping Simulation Draws," Working Paper Series 2019-24, Federal Reserve Bank of San Francisco.
    10. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    11. Lee, Donghoon & Song, Kyungchul, 2015. "Simulated maximum likelihood estimation for discrete choices using transformed simulated frequencies," Journal of Econometrics, Elsevier, vol. 187(1), pages 131-153.
    12. Laurent Delsol & Ingrid Van Keilegom, 2020. "Semiparametric M-estimation with non-smooth criterion functions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(2), pages 577-605, April.

  11. Heejoon Han & Dennis Kristensen, 2012. "Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates," CREATES Research Papers 2012-25, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Heejoon Han & Myung D. Park & Shen Zhang, 2015. "A Multiplicative Error Model with Heterogeneous Components for Forecasting Realized Volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(3), pages 209-219, April.
    2. Ekaterina Smetanina & Wei Biao Wu, 2021. "Asymptotic theory for QMLE for the real‐time GARCH(1,1) model," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 752-776, September.
    3. 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.
    4. Clements, A.E. & Hurn, A.S. & Volkov, V.V., 2015. "Volatility transmission in global financial markets," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 3-18.
    5. Giovanni Angelini & Luca De Angelis, 2017. "PARX model for football match predictions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(7), pages 795-807, November.
    6. Lorenzo Carbonari & Alessio Farcomeni & Cosimo Petracchi & Giovanni Trovato, 2024. "Macroprudential Policies and Credit Volatility," Working Paper series 24-16, Rimini Centre for Economic Analysis.
    7. Ulm, M. & Hambuckers, J., 2022. "Do interest rate differentials drive the volatility of exchange rates? Evidence from an extended stochastic volatility model," Journal of Empirical Finance, Elsevier, vol. 65(C), pages 125-148.
    8. Dennis Kristensen & Young Jun Lee, 2019. "Local Polynomial Estimation of Time-Varying Parameters in Nonlinear Models," Papers 1904.05209, arXiv.org, revised Aug 2023.
    9. Abdul-Nasir T. Yola, 2019. "On the Reaction of Stock Market to Monetary Policy Innovations: New Evidence from Nigeria," Academic Journal of Economic Studies, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 5(2), pages 94-98, June.
    10. Julien Chevallier & Bilel Sanhaji, 2023. "Jump-Robust Realized-GARCH-MIDAS-X Estimators for Bitcoin and Ethereum Volatility Indices," Post-Print halshs-04344131, HAL.
    11. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
    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. Francq, Christian & Sucarrat, Genaro, 2013. "An Exponential Chi-Squared QMLE for Log-GARCH Models Via the ARMA Representation," MPRA Paper 51783, University Library of Munich, Germany.
    14. Becker, Janis & Leschinski, Christian, 2018. "The Bias of Realized Volatility," Hannover Economic Papers (HEP) dp-642, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    15. Arianna Agosto & Giuseppe Cavaliere & Dennis Kristensen & Anders Rahbek, 2015. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," CREATES Research Papers 2015-11, Department of Economics and Business Economics, Aarhus University.
    16. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2021. "Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model," Econometrics and Statistics, Elsevier, vol. 20(C), pages 12-28.
    17. Amendola, A. & Candila, V. & Cipollini, F. & Gallo, G.M., 2024. "Doubly multiplicative error models with long- and short-run components," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    18. 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.
    19. Huang, Zhuo & Liu, Hao & Wang, Tianyi, 2016. "Modeling long memory volatility using realized measures of volatility: A realized HAR GARCH model," Economic Modelling, Elsevier, vol. 52(PB), pages 812-821.
    20. Heejoon Han, 2016. "Quantile Dependence between Stock Markets and its Application in Volatility Forecasting," Papers 1608.07193, arXiv.org.
    21. Francq, Christian & Sucarrat, Genaro, 2015. "Equation-by-Equation Estimation of a Multivariate Log-GARCH-X Model of Financial Returns," MPRA Paper 67140, University Library of Munich, Germany.
    22. Heino Bohn Nielsen & Anders Rahbek, 2023. "Penalized Quasi-likelihood Estimation and Model Selection in Time Series Models with Parameters on the Boundary," Papers 2302.02867, arXiv.org.
    23. Asai, Manabu, 2023. "Feasible Panel GARCH Models: Variance-Targeting Estimation and Empirical Application," Econometrics and Statistics, Elsevier, vol. 25(C), pages 23-38.
    24. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    25. Thieu, Le Quyen, 2016. "Variance targeting estimation of the BEKK-X model," MPRA Paper 75572, University Library of Munich, Germany.
    26. Rasmus Soendergaard Pedersen & Anders Rahbek, 2017. "Testing Garch-X Type Models," Discussion Papers 17-15, University of Copenhagen. Department of Economics.
    27. James, Robert & Leung, Henry & Leung, Jessica Wai Yin & Prokhorov, Artem, 2023. "Forecasting tail risk measures for financial time series: An extreme value approach with covariates," Journal of Empirical Finance, Elsevier, vol. 71(C), pages 29-50.
    28. Caiya Zhang & Kaihong Xu & Lianfen Qian, 2020. "Asymptotic properties of the QMLE in a log-linear RealGARCH model with Gaussian errors," Statistical Papers, Springer, vol. 61(6), pages 2313-2330, December.
    29. Sucarrat, Genaro & Grønneberg, Steffen, 2016. "Models of Financial Return With Time-Varying Zero Probability," MPRA Paper 68931, University Library of Munich, Germany.
    30. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2021. "Autoregressive conditional proportion: A multiplicative-error model for (0,1)-valued time series," MPRA Paper 110954, University Library of Munich, Germany, revised 06 Dec 2021.
    31. Holger Fink & Andreas Fuest & Henry Port, 2018. "The Impact of Sovereign Yield Curve Differentials on Value-at-Risk Forecasts for Foreign Exchange Rates," Risks, MDPI, vol. 6(3), pages 1-19, August.
    32. Huaping Chen & Qi Li & Fukang Zhu, 2022. "A new class of integer-valued GARCH models for time series of bounded counts with extra-binomial variation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 243-270, June.
    33. Thieu, Le Quyen, 2016. "Equation by equation estimation of the semi-diagonal BEKK model with covariates," MPRA Paper 75582, University Library of Munich, Germany.
    34. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.
    35. M. Karanasos & S. Yfanti & J. Hunter, 2022. "Emerging stock market volatility and economic fundamentals: the importance of US uncertainty spillovers, financial and health crises," Annals of Operations Research, Springer, vol. 313(2), pages 1077-1116, June.
    36. Ming Chen & Qiongxia Song, 2016. "Semi-parametric estimation and forecasting for exogenous log-GARCH models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 93-112, March.
    37. Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    38. Hoga, Yannick, 2021. "The uncertainty in extreme risk forecasts from covariate-augmented volatility models," International Journal of Forecasting, Elsevier, vol. 37(2), pages 675-686.
    39. Francq, Christian & Thieu, Le Quyen, 2015. "Qml inference for volatility models with covariates," MPRA Paper 63198, University Library of Munich, Germany.
    40. Aleksander Schiffers & Marcin Chlebus, 2021. "The effectiveness of Value-at-Risk models in various volatility regimes," Working Papers 2021-28, Faculty of Economic Sciences, University of Warsaw.
    41. Stavroula Yfanti & Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2022. "A three‐dimensional asymmetric power HEAVY model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2737-2761, July.
    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.
    44. Mengya Liu & Qi Li & Fukang Zhu, 2020. "Self-excited hysteretic negative binomial autoregression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 385-415, September.
    45. Han, Heejoon & Park, Joon Y., 2014. "GARCH with omitted persistent covariate," Economics Letters, Elsevier, vol. 124(2), pages 248-254.
    46. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," Working Papers 0597, University of Heidelberg, Department of Economics.

  12. Michael Creel & Dennis Kristensen, 2011. "Indirect likelihood inference," UFAE and IAE Working Papers 874.11, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).

    Cited by:

    1. Jiti Gao & Han Hong, 2014. "A Computational Implementation of GMM," Monash Econometrics and Business Statistics Working Papers 24/14, Monash University, Department of Econometrics and Business Statistics.
    2. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    3. Aldrich, EM, 2014. "GPU Computing in Economics," Santa Cruz Department of Economics, Working Paper Series qt8p12748g, Department of Economics, UC Santa Cruz.
    4. Jean-Jacques Forneron & Serena Ng, 2015. "The ABC of Simulation Estimation with Auxiliary Statistics," Papers 1501.01265, arXiv.org, revised Oct 2017.
    5. Michael Creel & Dennis Kristensen, 2015. "On Selection of Statistics for Approximate Bayesian Computing or the Method of Simulated Moments," UFAE and IAE Working Papers 950.15, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 27 Feb 2015.
    6. Bertl Johanna & Ewing Gregory & Kosiol Carolin & Futschik Andreas, 2017. "Approximate maximum likelihood estimation for population genetic inference," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(5-6), pages 291-312, December.
    7. Valerio Scalone, 2015. "Estimating Non-Linear DSGEs with the Approximate Bayesian Computation: an application to the Zero Lower Bound," Working Papers 6/15, Sapienza University of Rome, DISS.
    8. Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.
    9. Valerio Scalone, 2018. "Estimating Non-Linear DSGEs with the Approximate Bayesian Computation: an application to the Zero Lower Bound," Working papers 688, Banque de France.
    10. Michael Creel & Jiti Gao & Han Hong & Dennis Kristensen, 2016. "Bayesian Indirect Inference and the ABC of GMM," Monash Econometrics and Business Statistics Working Papers 1/16, Monash University, Department of Econometrics and Business Statistics.
    11. Creel, Michael, 2017. "Neural nets for indirect inference," Econometrics and Statistics, Elsevier, vol. 2(C), pages 36-49.
    12. Michael Creel, 2016. "Neural Nets for Indirect Inference," UFAE and IAE Working Papers 960.16, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 18 Jul 2016.
    13. Michael Creel & Dennis Kristensen, 2013. "Indirect Likelihood Inference (revised)," UFAE and IAE Working Papers 931.13, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    14. Michael Creel, 2016. "A Note on Julia and MPI, with Code Examples," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 535-546, October.

  13. Pierre-Andre Chiappori & Ivana Komunjer & Dennis Kristensen, 2011. "Nonparametric Identification and Estimation of Transformation Models," CAM Working Papers 2011-01, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.

    Cited by:

    1. Senay Sokullu, 2012. "Nonparametric Estimation of Semiparametric Transformation Models," Bristol Economics Discussion Papers 12/625, School of Economics, University of Bristol, UK.
    2. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    3. 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.
    4. Liyu Dou & Jakub Kastl & John Lazarev, 2020. "Quantifying Delay Externalities in Airline Networks," Working Papers 2020-65, Princeton University. Economics Department..
    5. Aureo de Paula & Imran Rasul & Pedro Souza, 2019. "Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition," Papers 1910.07452, arXiv.org, revised Oct 2023.
    6. Andrew Chesher & Adam Rosen & Konrad Smolinski, 2011. "An instrumental variable model of multiple discrete choice," CeMMAP working papers CWP39/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Bonev, Petyo, 2020. "Nonparametric identification in nonseparable duration models with unobserved heterogeneity," Economics Working Paper Series 2005, University of St. Gallen, School of Economics and Political Science.
    8. Stefan Hoderlein & Liangjun Su & Halbert White & Thomas Tao Yang, 2015. "Testing for Monotonicity in Unobservables under Unconfoundedness," Boston College Working Papers in Economics 899, Boston College Department of Economics.
    9. Centorrino, Samuele & Parmeter, Christopher F., 2024. "Nonparametric estimation of stochastic frontier models with weak separability," Journal of Econometrics, Elsevier, vol. 238(2).
    10. Christoph Breunig, 2019. "Specification Testing in Nonparametric Instrumental Quantile Regression," Papers 1909.10129, arXiv.org.
    11. Aureo de Paula & Imran Rasul & Pedro CL Souza, 2018. "Recovering social networks from panel data: Identification, simulations and an application," Documentos de Trabajo 16173, The Latin American and Caribbean Economic Association (LACEA).
    12. Lin, Yingqian & Tu, Yundong & Yao, Qiwei, 2020. "Estimation for double-nonlinear cointegration," Journal of Econometrics, Elsevier, vol. 216(1), pages 175-191.
    13. Krief, Jerome M., 2017. "Direct instrumental nonparametric estimation of inverse regression functions," Journal of Econometrics, Elsevier, vol. 201(1), pages 95-107.
    14. Gouriéroux, Christian & Monfort, Alain & Zakoian, Jean-Michel, 2017. "Pseudo-Maximum Likelihood and Lie Groups of Linear Transformations," MPRA Paper 79623, University Library of Munich, Germany.
    15. Irene Botosaru & Chris Muris, 2017. "Binarization for panel models with fixed effects," CeMMAP working papers CWP31/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. 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.
    17. Christoph Breunig & Stephan Martin, 2020. "Nonclassical Measurement Error in the Outcome Variable," Papers 2009.12665, arXiv.org, revised May 2021.
    18. 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.
    19. 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.
    20. Senay Sokullu & Irene Botosaru & Chris Muris, 2022. "Time-Varying Linear Transformation Models with Fixed Effects and Endogeneity for Short Panels," Bristol Economics Discussion Papers 22/756, School of Economics, University of Bristol, UK.
    21. Nick Kloodt & Natalie Neumeyer & Ingrid Keilegom, 2021. "Specification testing in semi-parametric transformation models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(4), pages 980-1003, December.
    22. Irene Botosaru & Chris Muris & Krishna Pendakur, 2020. "Intertemporal Collective Household Models: Identification in Short Panels with Unobserved Heterogeneity in Resource Shares," CeMMAP working papers CWP26/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. Hubner, Stefan, 2023. "Identification of unobserved distribution factors and preferences in the collective household model," Journal of Econometrics, Elsevier, vol. 234(1), pages 301-326.
    24. Kloodt, Nick, 2021. "Identification in a fully nonparametric transformation model with heteroscedasticity," Statistics & Probability Letters, Elsevier, vol. 170(C).
    25. Timo Kuosmanen & Sheng Dai, 2023. "Modeling economies of scope in joint production: Convex regression of input distance function," Papers 2311.11637, arXiv.org.
    26. Lin, Yingqian & Tu, Yundong, 2024. "Functional coefficient cointegration models with Box–Cox transformation," Economics Letters, Elsevier, vol. 234(C).
    27. Chalak, Karim, 2024. "Nonparametric Gini-Frisch bounds," Journal of Econometrics, Elsevier, vol. 238(1).
    28. Joachim Freyberger, 2021. "Normalizations and misspecification in skill formation models," Papers 2104.00473, arXiv.org, revised Jul 2022.
    29. Shosei Sakaguchi, 2024. "Partial identification and inference in duration models with endogenous censoring," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(2), pages 308-326, March.
    30. Breunig, Christoph, 2016. "Specification testing in nonparametric instrumental quantile regression," SFB 649 Discussion Papers 2016-032, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.

  14. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2011. "Bounding quantile demand functions using revealed preference inequalities," CeMMAP working papers CWP21/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Emmanuel Hache & Déborah Leboullenger & Valérie Mignon, 2016. "Beyond average energy consumption in the French residential housing market: A household classification approach," Working Papers hal-02475511, HAL.
    2. Sam Cosaert & Thomas Demuynck, 2018. "Nonparametric welfare and demand analysis with unobserved individual heterogeneity," ULB Institutional Repository 2013/251988, ULB -- Universite Libre de Bruxelles.
    3. Stoye, Jörg & Kitamura, Yuichi, 2013. "Nonparametric Analysis of Random Utility Models: Testing," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79753, Verein für Socialpolitik / German Economic Association.
    4. 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.
    5. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    6. Stefan Hoderlein & Hajo Holzmann & Alexander Meister, 2015. "The triangular model with random coefficients," CeMMAP working papers 33/15, Institute for Fiscal Studies.
    7. Kate Ho & Adam Rosen, 2015. "Partial identification in applied research: benefits and challenges," CeMMAP working papers 64/15, Institute for Fiscal Studies.
    8. Laurens Cherchye & Bram De Rock & Frederic Vermeulen, 2023. "Nonparametric Models in Consumer Behaviour," Working Papers ECARES 2023-04, ULB -- Universite Libre de Bruxelles.
    9. Jerry A. Hausman & Whitney K. Newey, 2016. "Individual Heterogeneity and Average Welfare," Econometrica, Econometric Society, vol. 84, pages 1225-1248, May.
    10. Richard Blundell & Martin Browning & Laurens Cherchye & Ian Crawford & Bram De Rock & Frederic Vermeulen, 2015. "Sharp for SARP: Nonparametric bounds on counterfactual demands," ULB Institutional Repository 2013/237105, ULB -- Universite Libre de Bruxelles.
    11. Stefan Hoderlein & Liangjun Su & Halbert White & Thomas Tao Yang, 2015. "Testing for Monotonicity in Unobservables under Unconfoundedness," Boston College Working Papers in Economics 899, Boston College Department of Economics.
    12. Nikolay Klemashev & Alexander Shananin, 2015. "Positively-homogeneous Konus-Divisia indices and their applications to demand analysis and forecasting," Papers 1501.05771, arXiv.org.
    13. Hubner, Stefan, 2016. "Topics in nonparametric identification and estimation," Other publications TiSEM 08fce56b-3193-46e0-871b-0, Tilburg University, School of Economics and Management.
    14. Laurens Cherchye & Thomas Demuynck & Per Hjertstrand & Bram De Rock, 2015. "Revealed preference tests for weak separability: An integer programming approach," ULB Institutional Repository 2013/251996, ULB -- Universite Libre de Bruxelles.
    15. Abi Adams & Richard Blundell & Martin Browning & Ian Crawford, 2015. "Prices versus preferences: taste change and revealed preference," IFS Working Papers W15/11, Institute for Fiscal Studies.
    16. Laurens Cherchye & Thomas Demuynck & Bram De Rock & Frederic Vermeulen, 2017. "Household Consumption When the Marriage Is Stable," American Economic Review, American Economic Association, vol. 107(6), pages 1507-1534, June.
    17. Cherchye, L.J.H. & de Rock, B. & Lewbel, A. & Vermeulen, F.M.P., 2012. "Sharing Rule Identification for General Collective Consumption Models," Discussion Paper 2012-041, Tilburg University, Center for Economic Research.
    18. Francesca Molinari, 2020. "Microeconometrics with Partial Identification," Papers 2004.11751, arXiv.org.
    19. Victor Chernozhukov & Jerry A. Hausman & Whitney K. Newey, 2019. "Demand Analysis with Many Prices," NBER Working Papers 26424, National Bureau of Economic Research, Inc.
    20. Thomas Demuynck, 2018. "Testing the homogeneous marginal utility of income assumption," ULB Institutional Repository 2013/251991, ULB -- Universite Libre de Bruxelles.
    21. Laurens CHERCHYE & Thomas DEMUYNCK & Bram DE ROCK, 2011. "Nash bargained consumption decisions: a revealed preference analysis," Working Papers of Department of Economics, Leuven ces11.07, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    22. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    23. Cherchye, Laurens & Demuynck, Thomas & Rock, Bram De, 2019. "Bounding counterfactual demand with unobserved heterogeneity and endogenous expenditures," Journal of Econometrics, Elsevier, vol. 211(2), pages 483-506.
    24. Ian Crawford, 2019. "Nonparametric Analysis of Labour Supply Using Random Fields," Economics Papers 2019-W06, Economics Group, Nuffield College, University of Oxford.
    25. Ian Crawford & Matthew Polisson, 2015. "Demand analysis with partially observed prices," IFS Working Papers W15/16, Institute for Fiscal Studies.
    26. Matias D. Cattaneo & Xinwei Ma & Yusufcan Masatlioglu & Elchin Suleymanov, 2017. "A Random Attention Model," Papers 1712.03448, arXiv.org, revised Aug 2019.
    27. Bart Capéau & Liebrecht De Sadeleer & Sebastiaan Maes & André M.J. Decoster, 2021. "Nonparametric Welfare Analysis for Discrete Choice: Levels and Differences of Individual and Social Welfare," CESifo Working Paper Series 9071, CESifo.
    28. Sam COSAERT & Thomas DEMUYNCK, 2013. "Revealed preference theory for finite choice sets," Working Papers of Department of Economics, Leuven ces13.08, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    29. Laurens Cherchye & Sam Cosaert & Bram De Rock & Pieter Jan Kerstens & Frederic Vermeulen, 2017. "Individual Welfare Analysis for Collective Households," Working Papers ECARES ECARES 2017-44, ULB -- Universite Libre de Bruxelles.
    30. McCalman, Phillip, 2023. "Robust trade policy to offset foreign market power," European Economic Review, Elsevier, vol. 154(C).
    31. Jerry Hausman & Whitney K. Newey, 2014. "Individual Heterogeneity and Average Welfare," CeMMAP working papers 42/14, Institute for Fiscal Studies.
    32. Apostolos Serletis & Maksim Isakin, 2017. "Stochastic volatility demand systems," Econometric Reviews, Taylor & Francis Journals, vol. 36(10), pages 1111-1122, November.
    33. Demuynck, T., 2015. "The homogeneous marginal utility of income assumption," Research Memorandum 013, Maastricht University, Graduate School of Business and Economics (GSBE).
    34. Richard Blundell, 2017. "What Have We Learned from Structural Models?," American Economic Review, American Economic Association, vol. 107(5), pages 287-292, May.
    35. Aguiar, Victor H. & Serrano, Roberto, 2017. "Slutsky matrix norms: The size, classification, and comparative statics of bounded rationality," Journal of Economic Theory, Elsevier, vol. 172(C), pages 163-201.
    36. Richard Blundell & Joel L. Horowitz & Matthias Parey, 2013. "Nonparametric estimation of a heterogeneous demand function under the Slutsky inequality restriction," CeMMAP working papers 54/13, Institute for Fiscal Studies.
    37. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers 60/17, Institute for Fiscal Studies.
    38. Adams-Prassl, Abigail, 2019. "Mutually Consistent Revealed Preference Demand Predictions," CEPR Discussion Papers 13580, C.E.P.R. Discussion Papers.
    39. Laura Blow & Richard Blundell, 2018. "A Nonparametric Revealed Preference Approach to Measuring the Value of Environmental Quality," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(3), pages 503-527, March.
    40. Blundell, Richard & Kristensen, Dennis & Matzkin, Rosa, 2014. "Bounding quantile demand functions using revealed preference inequalities," Journal of Econometrics, Elsevier, vol. 179(2), pages 112-127.
    41. Kaido, Hiroaki, 2016. "A dual approach to inference for partially identified econometric models," Journal of Econometrics, Elsevier, vol. 192(1), pages 269-290.
    42. Victor H. Aguiar & Nail Kashaev, 2018. "Stochastic Revealed Preferences with Measurement Error," Papers 1810.05287, arXiv.org, revised Sep 2020.
    43. Timothy Christensen & Hyungsik Roger Moon & Frank Schorfheide, 2022. "Optimal Decision Rules when Payoffs are Partially Identified," Papers 2204.11748, arXiv.org, revised May 2023.
    44. Christian Bontemps & Thierry Magnac, 2017. "Set Identification, Moment Restrictions, and Inference," Annual Review of Economics, Annual Reviews, vol. 9(1), pages 103-129, September.
    45. Sarantis Tsiaplias, 2017. "The Welfare Implications of Unobserved Heterogeneity," Melbourne Institute Working Paper Series wp2017n21, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    46. Stefan Hoderlein & Jörg Stoye, 2015. "Testing stochastic rationality and predicting stochastic demand: the case of two goods," Economic Theory Bulletin, Springer;Society for the Advancement of Economic Theory (SAET), vol. 3(2), pages 313-328, October.
    47. Arman Bidarbakht Nia, 2017. "A generalization to QUAIDS," Empirical Economics, Springer, vol. 52(1), pages 393-410, February.
    48. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    49. Jerry Hausman & Whitney K. Newey, 2013. "Individual heterogeneity and average welfare," CeMMAP working papers 34/13, Institute for Fiscal Studies.

  15. Dennis Kristensen, 2011. "Nonparametric Detection and Estimation of Structural Change," CREATES Research Papers 2011-13, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Liudas Giraitis & George Kapetanios & Tony Yates, 2015. "Inference on Multivariate Heteroscedastic Time Varying Random Coefficient Models," Working Papers 767, Queen Mary University of London, School of Economics and Finance.
    2. Byrne, Joseph P. & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2022. "The time-varying risk price of currency portfolios," Journal of International Money and Finance, Elsevier, vol. 124(C).
    3. Tobias Adrian & Richard K. Crump & Emanuel Moench, 2011. "Regression-based estimation of dynamic asset pricing models," Staff Reports 493, Federal Reserve Bank of New York.
    4. Andrew Ang & Dennis Kristensen, 2011. "Testing Conditional Factor Models," NBER Working Papers 17561, National Bureau of Economic Research, Inc.
    5. Tao, Yubo & Phillips, Peter C.B. & Yu, Jun, 2019. "Random coefficient continuous systems: Testing for extreme sample path behavior," Journal of Econometrics, Elsevier, vol. 209(2), pages 208-237.
    6. Pouliot, William, 2016. "Robust tests for change in intercept and slope in linear regression models with application to manager performance in the mutual fund industry," Economic Modelling, Elsevier, vol. 58(C), pages 523-534.
    7. Isabel Casas & Jiti Gao & Shangyu Xie, 2018. "Modelling Time-Varying Income Elasticities of Health Care Expenditure for the OECD," CREATES Research Papers 2018-29, Department of Economics and Business Economics, Aarhus University.
    8. Wu, Jilin, 2016. "Detecting structural changes under nonstationary volatility," Economics Letters, Elsevier, vol. 146(C), pages 151-154.
    9. Dennis Kristensen & Young Jun Lee, 2019. "Local Polynomial Estimation of Time-Varying Parameters in Nonlinear Models," Papers 1904.05209, arXiv.org, revised Aug 2023.
    10. Burcu Kapar & William Pouliot, 2013. "Multiple Change-Point Detection in Linear Regression Models via U-Statistic Type Processes," Discussion Papers 13-13, Department of Economics, University of Birmingham.
    11. 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.
    12. Chen, Bin, 2015. "Modeling and testing smooth structural changes with endogenous regressors," Journal of Econometrics, Elsevier, vol. 185(1), pages 196-215.
    13. Fu, Zhonghao & Hong, Yongmiao, 2019. "A model-free consistent test for structural change in regression possibly with endogeneity," Journal of Econometrics, Elsevier, vol. 211(1), pages 206-242.
    14. Ping Yu & Peter C.B. Phillips, 2014. "Threshold Regression with Endogeneity," Cowles Foundation Discussion Papers 1966, Cowles Foundation for Research in Economics, Yale University.
    15. Chen, Bin & Maung, Kenwin, 2023. "Time-varying forecast combination for high-dimensional data," Journal of Econometrics, Elsevier, vol. 237(2).
    16. 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.
    17. Sakemoto, Ryuta, 2019. "Currency carry trades and the conditional factor model," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 198-208.
    18. Byrne, Joseph P & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2017. "The Time-Varying Risk Price of Currency Carry Trades," MPRA Paper 80788, University Library of Munich, Germany.
    19. Casas Villalba, Maria Isabel, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.
    20. Byrne, Joseph P. & Sakemoto, Ryuta, 2021. "The conditional volatility premium on currency portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    21. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).
    22. Isabel Casas & Xiuping Mao & Helena Veiga, 2018. "Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium," CREATES Research Papers 2018-10, Department of Economics and Business Economics, Aarhus University.
    23. Bin Chen & Kenwin Maung, 2020. "Time-varying Forecast Combination for High-Dimensional Data," Papers 2010.10435, arXiv.org.
    24. Maria Mohr & Leonie Selk, 2020. "Estimating change points in nonparametric time series regression models," Statistical Papers, Springer, vol. 61(4), pages 1437-1463, August.
    25. 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.

  16. 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.

    Cited by:

    1. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    2. 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).
    3. Michael Creel & Dennis Kristensen, "undated". "Indirect Likelihood Inference," Working Papers 558, Barcelona School of Economics.
    4. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers CWP45/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Stelios Arvanitis & Antonis Demos, 2015. "A class of indirect inference estimators: higher‐order asymptotics and approximate bias correction," Econometrics Journal, Royal Economic Society, vol. 18(2), pages 200-241, June.
    6. Joachim Freyberger, 2012. "Asymptotic theory for differentiated products demand models with many markets," CeMMAP working papers CWP19/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Joachim Freyberger, 2012. "Asymptotic theory for differentiated products demand models with many markets," CeMMAP working papers 19/12, Institute for Fiscal Studies.
    8. Michael Creel & Dennis Kristensen, 2013. "Indirect Likelihood Inference (revised)," UFAE and IAE Working Papers 931.13, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).

  17. Dennis Kristensen, 2010. "Semi-Nonparametric Estimation and Misspecification Testing of Diffusion Models," CREATES Research Papers 2010-43, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Zhang, Shulin & Song, Peter X.-K. & Shi, Daimin & Zhou, Qian M., 2012. "Information ratio test for model misspecification on parametric structures in stochastic diffusion models," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3975-3987.
    2. Bu, Ruijun & Hadri, Kaddour & Kristensen, Dennis, 2021. "Diffusion copulas: Identification and estimation," Journal of Econometrics, Elsevier, vol. 221(2), pages 616-643.
    3. 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.
    4. Zu, Yang & Boswijk, H. Peter, 2017. "Consistent nonparametric specification tests for stochastic volatility models based on the return distribution," Journal of Empirical Finance, Elsevier, vol. 41(C), pages 53-75.
    5. Zu, Y., 2015. "Consistent nonparametric specification tests for stochastic volatility models based on the return distribution," Working Papers 15/02, Department of Economics, City University London.
    6. 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.
    7. Chen, Qiang & Zheng, Xu & Pan, Zhiyuan, 2015. "Asymptotically distribution-free tests for the volatility function of a diffusion," Journal of Econometrics, Elsevier, vol. 184(1), pages 124-144.
    8. 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.
    9. 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.

  18. Shin Kanaya & Dennis Kristensen, 2010. "Estimation of Stochastic Volatility Models by Nonparametric Filtering," CREATES Research Papers 2010-67, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. 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.
    2. Kanaya, Shin, 2016. "Convergence rates of sums of α-mixing triangular arrays : with an application to non-parametric drift function estimation of continuous-time processes," Discussion Paper Series 646, Institute of Economic Research, Hitotsubashi University.
    3. Andrew Ang & Dennis Kristensen, 2011. "Testing Conditional Factor Models," NBER Working Papers 17561, National Bureau of Economic Research, Inc.
    4. 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.
    5. Matthieu Garcin & Clément Goulet, 2017. "Non-parametric news impact curve: a variational approach," Post-Print halshs-01244292, HAL.
    6. 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.
    7. Bandi, Federico & Corradi, Valentina & Moloche, Guillermo, 2009. "Bandwidth selection for continuous-time Markov processes," MPRA Paper 43682, University Library of Munich, Germany.
    8. Bu, Ruijun & Hadri, Kaddour & Kristensen, Dennis, 2021. "Diffusion copulas: Identification and estimation," Journal of Econometrics, Elsevier, vol. 221(2), pages 616-643.
    9. Federico M. Bandi & Roberto Reno, 2009. "Nonparametric Stochastic Volatility," Global COE Hi-Stat Discussion Paper Series gd08-035, Institute of Economic Research, Hitotsubashi University.
    10. Shang, Yuhuang & Zheng, Tingguo, 2021. "Mixed-frequency SV model for stock volatility and macroeconomics," Economic Modelling, Elsevier, vol. 95(C), pages 462-472.
    11. Ghosh, Anisha & Linton, Oliver, 2023. "Estimation with mixed data frequencies: A bias-correction approach," Journal of Empirical Finance, Elsevier, vol. 74(C).
    12. Mustafayeva, Konul & Wang, Weining, 2020. "Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data," IRTG 1792 Discussion Papers 2020-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    13. Giacomo Toscano & Maria Cristina Recchioni, 2022. "Bias-optimal vol-of-vol estimation: the role of window overlapping," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 45(1), pages 137-185, June.
    14. Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.
    15. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    16. Arthur T. Rego & Thiago R. dos Santos, 2018. "Non-Gaussian Stochastic Volatility Model with Jumps via Gibbs Sampler," Papers 1809.01501, arXiv.org, revised Oct 2018.
    17. Liu, Qiang & Liu, Yiqi & Liu, Zhi & Wang, Li, 2018. "Estimation of spot volatility with superposed noisy data," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 62-79.
    18. Chao Yu & Yue Fang & Zeng Li & Bo Zhang & Xujie Zhao, 2014. "Non-Parametric Estimation Of High-Frequency Spot Volatility For Brownian Semimartingale With Jumps," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 572-591, November.
    19. Ruijun Bu & Degui Li & Oliver Linton & Hanchao Wang, 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Working Papers 202212, University of Liverpool, Department of Economics.
    20. Park, Joon Y. & Wang, Bin, 2021. "Nonparametric estimation of jump diffusion models," Journal of Econometrics, Elsevier, vol. 222(1), pages 688-715.
    21. Zu, Yang & Peter Boswijk, H., 2014. "Estimating spot volatility with high-frequency financial data," Journal of Econometrics, Elsevier, vol. 181(2), pages 117-135.
    22. Matthieu Garcin & Clément Goulet, 2015. "A fully non-parametric heteroskedastic model," Documents de travail du Centre d'Economie de la Sorbonne 15086, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    23. Yu, Chao & Fang, Yue & Zhao, Xujie & Zhang, Bo, 2013. "Kernel filtering of spot volatility in presence of Lévy jumps and market microstructure noise," MPRA Paper 63293, University Library of Munich, Germany, revised 10 Mar 2014.
    24. Aït-Sahalia, Yacine & Li, Chenxu & Li, Chen Xu, 2024. "Maximum likelihood estimation of latent Markov models using closed-form approximations," Journal of Econometrics, Elsevier, vol. 240(2).
    25. Matthieu Garcin & Clément Goulet, 2017. "Non-parametric news impact curve: a variational approach," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01244292, HAL.
    26. Li, Jia & Patton, Andrew J., 2018. "Asymptotic inference about predictive accuracy using high frequency data," Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
    27. Kim, Jihyun & Park, Joon & Wang, Bin, 2020. "Estimation of Volatility Functions in Jump Diffusions Using Truncated Bipower Increments," TSE Working Papers 20-1096, Toulouse School of Economics (TSE).
    28. Curato, Imma Valentina & Mancino, Maria Elvira & Recchioni, Maria Cristina, 2018. "Spot volatility estimation using the Laplace transform," Econometrics and Statistics, Elsevier, vol. 6(C), pages 22-43.
    29. 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.
    30. Zu, Yang, 2015. "Nonparametric specification tests for stochastic volatility models based on volatility density," Journal of Econometrics, Elsevier, vol. 187(1), pages 323-344.

  19. Dennis Kristensen & Anders Rahbek, 2010. "Testing and Inference in Nonlinear Cointegrating Vector Error Correction Models," CREATES Research Papers 2010-68, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    2. Georg Keilbar & Yanfen Zhang, 2021. "On cointegration and cryptocurrency dynamics," Digital Finance, Springer, vol. 3(1), pages 1-23, March.
    3. Boswijk, H. Peter & Cavaliere, Giuseppe & Rahbek, Anders & Taylor, A.M. Robert, 2016. "Inference on co-integration parameters in heteroskedastic vector autoregressions," Journal of Econometrics, Elsevier, vol. 192(1), pages 64-85.
    4. Line Elvstrøm Ekner & Emil Nejstgaard, 2013. "Parameter Identification in the Logistic STAR Model," Discussion Papers 13-07, University of Copenhagen. Department of Economics.
    5. Michal Ksawery Popiel, 2016. "Interest Rate Pass-through: A Nonlinear Vector Error-correction Approach," Working Paper 1352, Economics Department, Queen's University.
    6. Giuseppe Cavaliere & Anders Rahbek, 2019. "A Primer On Bootstrap Testing Of Hypotheses In Time Series Models: With An Application To Double Autoregressive Models," Discussion Papers 19-03, University of Copenhagen. Department of Economics.
    7. Kristensen, Dennis & Rahbek, Anders, 2010. "Likelihood-based inference for cointegration with nonlinear error-correction," Journal of Econometrics, Elsevier, vol. 158(1), pages 78-94, September.
    8. Andreas Hetland, 2018. "The Stochastic Stationary Root Model," Econometrics, MDPI, vol. 6(3), pages 1-33, August.
    9. 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.
    10. Skrobotov, Anton, 2021. "Structural breaks in cointegration models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 117-141.
    11. She, Rui & Ling, Shiqing, 2020. "Inference in heavy-tailed vector error correction models," Journal of Econometrics, Elsevier, vol. 214(2), pages 433-450.
    12. Marçal, Emerson & Simões, Oscar Rodrigues, 2024. "Current account and real effective exchange rate dynamics: the role of non-linear dynamics in Brazil," Textos para discussão 571, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).

  20. Dennis Kristensen & Andrew Ang, 2009. "Testing Conditional Factor Models," CREATES Research Papers 2009-09, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Byrne, Joseph P. & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2022. "The time-varying risk price of currency portfolios," Journal of International Money and Finance, Elsevier, vol. 124(C).
    2. Kang, Hankil & Kang, Jangkoo & Lee, Changjun, 2013. "Do the production-based factors capture the time-varying patterns in stock returns?," Emerging Markets Review, Elsevier, vol. 15(C), pages 122-135.
    3. Aït-Sahalia, Yacine & Kalnina, Ilze & Xiu, Dacheng, 2020. "High-frequency factor models and regressions," Journal of Econometrics, Elsevier, vol. 216(1), pages 86-105.
    4. Dennis Kristensen, 2009. "Semiparametric modelling and estimation (in Russian)," Quantile, Quantile, issue 7, pages 53-83, September.
    5. Stefan Nagel, 2012. "Empirical Cross-Sectional Asset Pricing," NBER Working Papers 18554, National Bureau of Economic Research, Inc.
    6. Tobias Adrian & Richard K. Crump & Emanuel Moench, 2011. "Regression-based estimation of dynamic asset pricing models," Staff Reports 493, Federal Reserve Bank of New York.
    7. Anna Kovner & Peter Van Tassel, 2022. "Evaluating Regulatory Reform: Banks' Cost of Capital and Lending," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(5), pages 1313-1367, August.
    8. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    9. Andrew Ang & Dennis Kristensen, 2011. "Testing Conditional Factor Models," NBER Working Papers 17561, National Bureau of Economic Research, Inc.
    10. Lieven Baele & Geert Bekaert & Koen Inghelbrecht & Min Wei, 2020. "Flights to Safety," The Review of Financial Studies, Society for Financial Studies, vol. 33(2), pages 689-746.
    11. Kinnunen, Jyri, 2014. "Risk-return trade-off and serial correlation: Do volume and volatility matter?," Journal of Financial Markets, Elsevier, vol. 20(C), pages 1-19.
    12. 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.
    13. Andrew Ang & Marie Brière & Ombretta Signori, 2012. "Inflation and Individual Equities," NBER Working Papers 17798, National Bureau of Economic Research, Inc.
    14. Richard T. Baillie & Fabio Calonaci & George Kapetanios, 2019. "Hierarchical Time Varying Estimation of a Multi Factor Asset Pricing Model," Working Papers 879, Queen Mary University of London, School of Economics and Finance.
    15. Deshui Yu & Yayi Yan, 2023. "Joint dynamics of stock returns and cash flows: A time‐varying present‐value framework," Financial Management, Financial Management Association International, vol. 52(3), pages 513-541, September.
    16. Guglielmo Maria Caporale & Luis A. Gil-Alana & Miguel Martin-Valmayor, 2020. "Persistence in the Realized Betas: Some Evidence for the Spanish Stock Market," CESifo Working Paper Series 8171, CESifo.
    17. Siddhartha Chib & Simon C. Smith, 2024. "Factor Selection and Structural Breaks," Finance and Economics Discussion Series 2024-037, Board of Governors of the Federal Reserve System (U.S.).
    18. 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.
    19. Carbajal-De-Nova, Carolina & Venegas-Martínez, Francisco, 2019. "On the paradigm shift of asset pricing models, before and after the global financial crisis: a literature review," Panorama Económico, Escuela Superior de Economía, Instituto Politécnico Nacional, vol. 15(29), pages 7-38, Primer se.
    20. 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.
    21. Joseph, Byrne & Sakemoto, Ryuta, 2020. "The Conditional Risk and Return Trade-Off on Currency Portfolios," MPRA Paper 99497, University Library of Munich, Germany.
    22. Reiß, Markus & Todorov, Viktor & Tauchen, George, 2014. "Nonparametric test for a constant beta over a fixed time interval," SFB 649 Discussion Papers 2014-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    23. Yu, Deshui & Huang, Difang & Chen, Li, 2023. "Stock return predictability and cyclical movements in valuation ratios," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 36-53.
    24. 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.
    25. Takahiro Komatsu & Naoki Makimoto, 2015. "Dynamic Investment Strategy with Factor Models Under Regime Switches," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 22(2), pages 209-237, May.
    26. Lars Hornuf & Gül Yüksel, 2022. "The Performance of Socially Responsible Investments: A Meta-Analysis," CESifo Working Paper Series 9724, CESifo.
    27. Oh, Dong Hwan & Patton, Andrew J., 2024. "Better the devil you know: Improved forecasts from imperfect models," Journal of Econometrics, Elsevier, vol. 242(1).
    28. François-Éric Racicot & William F Rentz & David Tessier & Raymond Théoret, 2019. "The conditional Fama-French model and endogenous illiquidity: A robust instrumental variables test," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-26, September.
    29. Boons, Martijn & Duarte, Fernando & de Roon, Frans & Szymanowska, Marta, 2020. "Time-varying inflation risk and stock returns," Journal of Financial Economics, Elsevier, vol. 136(2), pages 444-470.
    30. 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.
    31. Zongwu Cai & Ying Fang & Qiuhua Xu, 2020. "Testing Capital Asset Pricing Models using Functional-Coefficient Panel Data Models with Cross-Sectional Dependence," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202009, University of Kansas, Department of Economics, revised Jul 2020.
    32. Chen, Bin, 2015. "Modeling and testing smooth structural changes with endogenous regressors," Journal of Econometrics, Elsevier, vol. 185(1), pages 196-215.
    33. Yan Li & Liangjun Su & Yuewu Xu, 2015. "A Combined Approach to the Inference of Conditional Factor Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(2), pages 203-220, April.
    34. Baele, Lieven & Londono, Juan M., 2013. "Understanding industry betas," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 30-51.
    35. Ryuta Sakemoto, 2022. "Multi‐scale inter‐temporal capital asset pricing model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4298-4317, October.
    36. Chen, Bin & Maung, Kenwin, 2023. "Time-varying forecast combination for high-dimensional data," Journal of Econometrics, Elsevier, vol. 237(2).
    37. Cai, Zongwu & Fang, Ying & Xu, Qiuhua, 2022. "Testing capital asset pricing models using functional-coefficient panel data models with cross-sectional dependence," Journal of Econometrics, Elsevier, vol. 227(1), pages 114-133.
    38. Jianqing Fan & Kunpeng Li & Yuan Liao, 2020. "Recent Developments on Factor Models and its Applications in Econometric Learning," Papers 2009.10103, arXiv.org.
    39. Carmine Trecroci, 2014. "How Do Alphas and Betas Move? Uncertainty, Learning and Time Variation in Risk Loadings," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(2), pages 257-278, April.
    40. Matias D. Cattaneo & Richard K. Crump & Weining Wang, 2023. "Beta-Sorted Portfolios," Staff Reports 1068, Federal Reserve Bank of New York.
    41. Roussanov, Nikolai, 2014. "Composition of wealth, conditioning information, and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 111(2), pages 352-380.
    42. Reiß, Markus & Todorov, Viktor & Tauchen, George, 2015. "Nonparametric test for a constant beta between Itô semi-martingales based on high-frequency data," Stochastic Processes and their Applications, Elsevier, vol. 125(8), pages 2955-2988.
    43. Insana, Alessandra, 2022. "Does systematic risk change when markets close? An analysis using stocks’ beta," Economic Modelling, Elsevier, vol. 109(C).
    44. Nikolay Gospodinov, 2017. "Asset Co-movements: Features and Challenges," FRB Atlanta Working Paper 2017-11, Federal Reserve Bank of Atlanta.
    45. Isabel Casas & Eva Ferreira & Susan Orbe, 2021. "Time-Varying Coefficient Estimation in SURE Models. Application to Portfolio Management," Journal of Financial Econometrics, Oxford University Press, vol. 19(4), pages 707-745.
    46. Smith, Simon C. & Timmermann, Allan, 2022. "Have risk premia vanished?," Journal of Financial Economics, Elsevier, vol. 145(2), pages 553-576.
    47. Dennis Kristensen, 2009. "Semiparametric Modelling and Estimation: A Selective Overview," CREATES Research Papers 2009-44, Department of Economics and Business Economics, Aarhus University.
    48. Schrimpf, Paul & Kearns, Jonathan & Ferrari, Massimo, 2017. "Monetary policy's rising FX impact in the era of ultra-low rates," CEPR Discussion Papers 11918, C.E.P.R. Discussion Papers.
    49. Umlandt, Dennis, 2023. "Score-driven asset pricing: Predicting time-varying risk premia based on cross-sectional model performance," Journal of Econometrics, Elsevier, vol. 237(2).
    50. Sakemoto, Ryuta, 2019. "Currency carry trades and the conditional factor model," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 198-208.
    51. Byrne, Joseph P & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2017. "The Time-Varying Risk Price of Currency Carry Trades," MPRA Paper 80788, University Library of Munich, Germany.
    52. Cai, Biqing & Cheng, Tingting & Yan, Cheng, 2018. "Time-varying skills (versus luck) in U.S. active mutual funds and hedge funds," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 81-106.
    53. Gagliardini, Patrick & Ossola, Elisa & Scaillet, Olivier, 2019. "Estimation of large dimensional conditional factor models in finance," Working Papers unige:125031, University of Geneva, Geneva School of Economics and Management.
    54. Yu, Deshui & Chen, Li, 2024. "Local predictability of stock returns and cash flows," Journal of Empirical Finance, Elsevier, vol. 77(C).
    55. Arnold, Marc & Wagner, Alexander F. & Westermann, Ramona, 2013. "Growth options, macroeconomic conditions, and the cross section of credit risk," Journal of Financial Economics, Elsevier, vol. 107(2), pages 350-385.
    56. Yuan Liao & Xiye Yang, 2017. "Uniform Inference for Characteristic Effects of Large Continuous-Time Linear Models," Papers 1711.04392, arXiv.org, revised Dec 2018.
    57. Russell Davidson & Niels S. Grønborg, 2018. "Time-varying parameters: New test tailored to applications in finance and macroeconomics," CREATES Research Papers 2018-22, Department of Economics and Business Economics, Aarhus University.
    58. Gianluca De Nard & Olivier Ledoit & Michael Wolf, 2018. "Factor models for portfolio selection in large dimensions: the good, the better and the ugly," ECON - Working Papers 290, Department of Economics - University of Zurich, revised Dec 2018.
    59. Kim, Soohun & Skoulakis, Georgios, 2018. "Ex-post risk premia estimation and asset pricing tests using large cross sections: The regression-calibration approach," Journal of Econometrics, Elsevier, vol. 204(2), pages 159-188.
    60. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2019. "Estimating beta: Forecast adjustments and the impact of stock characteristics for a broad cross-section," Journal of Financial Markets, Elsevier, vol. 44(C), pages 91-118.
    61. Torben G. Andersen & Martin Thyrsgaard & Viktor Todorov, 2021. "Recalcitrant betas: Intraday variation in the cross‐sectional dispersion of systematic risk," Quantitative Economics, Econometric Society, vol. 12(2), pages 647-682, May.
    62. Асатуров К.Г., 2015. "Динамические Модели Систематического Риска: Сравнение На Примере Индийского Фондового Рынка," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 51(4), pages 59-75, октябрь.
    63. Desai, Chintal Ajitbhai, 2017. "The cross-section of consumer lending risk," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 256-282.
    64. Mikihito Nishi, 2024. "Estimating Time-Varying Parameters of Various Smoothness in Linear Models via Kernel Regression," Papers 2406.14046, arXiv.org, revised Oct 2024.
    65. Paul SCHNEIDER, 2014. "Generalized Risk Premia," Swiss Finance Institute Research Paper Series 14-29, Swiss Finance Institute.
    66. Byrne, Joseph P. & Sakemoto, Ryuta, 2021. "The conditional volatility premium on currency portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    67. Ok, Hyunmin & Kim, Jinyong & Kim, Yongsik, 2023. "Is the Kimchi premium a speculative bubble?," Finance Research Letters, Elsevier, vol. 57(C).
    68. Lu, Xun & Su, Liangjun, 2015. "Jackknife model averaging for quantile regressions," Journal of Econometrics, Elsevier, vol. 188(1), pages 40-58.
    69. Borup, Daniel, 2019. "Asset pricing model uncertainty," Journal of Empirical Finance, Elsevier, vol. 54(C), pages 166-189.
    70. Robert Jacobson & Natalie Mizik, 2009. "—Customer Satisfaction-Based Mispricing: Issues and Misconceptions," Marketing Science, INFORMS, vol. 28(5), pages 836-845, 09-10.
    71. Mehmet Balcilar & Riza Demirer & Festus V. Bekun, 2021. "Flexible Time-Varying Betas in a Novel Mixture Innovation Factor Model with Latent Threshold," Mathematics, MDPI, vol. 9(8), pages 1-20, April.
    72. 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.
    73. Riccardo Borghi & Eric Hillebrand & Jakob Mikkelsen & Giovanni Urga, 2018. "The dynamics of factor loadings in the cross-section of returns," CREATES Research Papers 2018-38, Department of Economics and Business Economics, Aarhus University.
    74. Chen, Dachuan & Mykland, Per A. & Zhang, Lan, 2024. "Realized regression with asynchronous and noisy high frequency and high dimensional data," Journal of Econometrics, Elsevier, vol. 239(2).
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    77. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun & Wang, Weining, 2021. "Long- and short-run components of factor betas: Implications for stock pricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    78. Cheng, Tingting & Yan, Cheng & Yan, Yayi, 2021. "Improved inference for fund alphas using high-dimensional cross-sectional tests," Journal of Empirical Finance, Elsevier, vol. 61(C), pages 57-81.
    79. Dong Hwan Oh & Andrew J. Patton, 2021. "Better the Devil You Know: Improved Forecasts from Imperfect Models," Finance and Economics Discussion Series 2021-071, Board of Governors of the Federal Reserve System (U.S.).
    80. Lioui, Abraham & Tarelli, Andrea, 2020. "Factor Investing for the Long Run," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    81. 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).
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    83. Cosemans, M. & Frehen, R.G.P. & Schotman, P.C. & Bauer, R.M.M.J., 2009. "Efficient Estimation of Firm-Specific Betas and its Benefits for Asset Pricing Tests and Portfolio Choice," MPRA Paper 23557, University Library of Munich, Germany.
    84. Andrew Ang & Morten Sorensen, 2012. "Risks, Returns, and Optimal Holdings of Private Equity: A Survey of Existing Approaches," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 1-27.
    85. Victor Chernozhukov & Christian Hansen & Yuan Liao & Yinchu Zhu, 2021. "Inference for Low-Rank Models," Papers 2107.02602, arXiv.org, revised Jan 2023.
    86. Johan Knif & James W. Kolari & Gregory Koutmos & Seppo Pynonen, 2023. "Modeling the Time Variation in Factor Exposures," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 12(2), pages 1-2.
    87. Nieto Domenech, Belén & Orbe Mandaluniz, Susan & Zárraga Alonso, Ainhoa, 2011. "Time-Varying Beta Estimators in the Mexican Emerging Market," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    88. Arbab Khalid Cheema & Wenjie Ding & Qingwei Wang, 2023. "The cross-section of January effect," Journal of Asset Management, Palgrave Macmillan, vol. 24(6), pages 513-530, October.

  21. Dennis Kristensen & Antonio Mele, 2009. "Adding and Subtracting Black-Scholes: A New Approach to Approximating Derivative Prices in Continuous Time Models," CREATES Research Papers 2009-14, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Arismendi, Juan & Genaro, Alan De, 2016. "A Monte Carlo multi-asset option pricing approximation for general stochastic processes," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 75-99.
    2. Liexin Cheng & Xue Cheng, 2024. "Short-Term Asymptotics of Volatility Skew and Curvature Based on Cumulants," Papers 2401.03776, arXiv.org, revised Nov 2024.
    3. Yang, Nian & Chen, Nan & Wan, Xiangwei, 2019. "A new delta expansion for multivariate diffusions via the Itô-Taylor expansion," Journal of Econometrics, Elsevier, vol. 209(2), pages 256-288.
    4. Kailin Ding & Zhenyu Cui & Xiaoguang Yang, 2023. "Pricing arithmetic Asian and Amerasian options: A diffusion operator integral expansion approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(2), pages 217-241, February.
    5. Michael Kurz, 2018. "Closed-form approximations in derivatives pricing: The Kristensen-Mele approach," Papers 1804.08904, arXiv.org.
    6. Aït-Sahalia, Yacine & Li, Chenxu & Li, Chen Xu, 2021. "Closed-form implied volatility surfaces for stochastic volatility models with jumps," Journal of Econometrics, Elsevier, vol. 222(1), pages 364-392.
    7. Wan, Xiangwei & Yang, Nian, 2021. "Hermite expansion of transition densities and European option prices for multivariate diffusions with jumps," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    8. Antonio Cosma & Stefano Galluccio & Paola Pederzoli & Olivier Scaillet, 2015. "Valuing American options using fast recursive projections," DEM Discussion Paper Series 15-20, Department of Economics at the University of Luxembourg.
    9. Pagliarani, Stefano & Pascucci, Andrea, 2011. "Analytical approximation of the transition density in a local volatility model," MPRA Paper 31107, University Library of Munich, Germany.
    10. Juan Arismendi, 2014. "A Multi-Asset Option Approximation for General Stochastic Processes," ICMA Centre Discussion Papers in Finance icma-dp2014-03, Henley Business School, University of Reading.
    11. Oh, Dong Hwan & Patton, Andrew J., 2024. "Better the devil you know: Improved forecasts from imperfect models," Journal of Econometrics, Elsevier, vol. 242(1).
    12. Azusa Takeyama & Nick Constantinou & Dmitri Vinogradov, 2012. "A Framework for Extracting the Probability of Default from Stock Option Prices," IMES Discussion Paper Series 12-E-14, Institute for Monetary and Economic Studies, Bank of Japan.
    13. Damir FILIPOVIC & Eberhard BERHARD & Paul SCHNEIDER, 2011. "Density Approximations For Multivariate Affine Jump-Diffusion Processes," Swiss Finance Institute Research Paper Series 11-20, Swiss Finance Institute.
    14. Antonio Cosma & Stefano Galluccio & Paola Pederzoli & O. Scaillet, 2016. "Early Exercise Decision in American Options with Dividends, Stochastic Volatility and Jumps," Swiss Finance Institute Research Paper Series 16-73, Swiss Finance Institute.
    15. Dennis Kristensen & Young Jun Lee & Antonio Mele, 2023. "Closed-form approximations of moments and densities of continuous-time Markov models," Papers 2308.09009, arXiv.org.
    16. Xiu, Dacheng, 2014. "Hermite polynomial based expansion of European option prices," Journal of Econometrics, Elsevier, vol. 179(2), pages 158-177.
    17. Choi, Seungmoon, 2015. "Explicit form of approximate transition probability density functions of diffusion processes," Journal of Econometrics, Elsevier, vol. 187(1), pages 57-73.
    18. Jarno Talponen, 2018. "Matching distributions: Recovery of implied physical densities from option prices," Papers 1803.03996, arXiv.org.
    19. Recchioni, Maria Cristina & Iori, Giulia & Tedeschi, Gabriele & Ouellette, Michelle S., 2021. "The complete Gaussian kernel in the multi-factor Heston model: Option pricing and implied volatility applications," European Journal of Operational Research, Elsevier, vol. 293(1), pages 336-360.
    20. João Pedro Vidal Nunes & Pedro Miguel Silva Prazeres, 2014. "Pricing Swaptions Under Multifactor Gaussian Hjm Models," Mathematical Finance, Wiley Blackwell, vol. 24(4), pages 762-789, October.
    21. Dong Hwan Oh & Andrew J. Patton, 2021. "Better the Devil You Know: Improved Forecasts from Imperfect Models," Finance and Economics Discussion Series 2021-071, Board of Governors of the Federal Reserve System (U.S.).

  22. Michael Creel & Dennis Kristensen, 2009. "Estimation of Dynamic Latent Variable Models Using Simulated Nonparametric Moments," UFAE and IAE Working Papers 792.09, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).

    Cited by:

    1. Tierney, Heather L.R., 2009. "Evaluating Exclusion-from-Core Measures of Inflation using Real-Time Data," MPRA Paper 17856, University Library of Munich, Germany.
    2. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    3. Michael Creel & Dennis Kristensen, "undated". "Indirect Likelihood Inference," Working Papers 558, Barcelona School of Economics.
    4. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers CWP45/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Tierney, Heather L.R., 2009. "Examining the Ability of Core Inflation to Capture the Overall Trend of Total Inflation," MPRA Paper 22409, University Library of Munich, Germany, revised Feb 2010.
    6. Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.
    7. Kukacka, Jiri & Sacht, Stephen, 2023. "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    8. Mike G. Tsionas & Subal C. Kumbhakar, 2023. "Efficiency Measurement in Norwegian Electricity Distribution: A Generalized Four-Way-Error-Component Stochastic Frontier Model," The Energy Journal, , vol. 44(2), pages 181-204, March.
    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. Tierney, Heather L.R., 2009. "A Local Examination for Persistence in Exclusions-from-Core Measures of Inflation Using Real-Time Data," MPRA Paper 13383, University Library of Munich, Germany, revised 03 Feb 2009.
    11. 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.
    12. Kukacka, Jiri & Barunik, Jozef, 2016. "Estimation of financial agent-based models with simulated maximum likelihood," FinMaP-Working Papers 63, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    13. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    14. Agnieszka Leszczynska, 2014. "Willingness to Pay for Green Products vs Ecological Value System," International Journal of Synergy and Research, ToKnowPress, vol. 3(1), pages 67-77.
    15. Michael Creel & Dennis Kristensen, 2013. "Indirect Likelihood Inference (revised)," UFAE and IAE Working Papers 931.13, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    16. Michael Creel, 2016. "A Note on Julia and MPI, with Code Examples," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 535-546, October.

  23. 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.

    Cited by:

    1. Kanaya, Shin & Kristensen, Dennis, 2016. "Estimation Of Stochastic Volatility Models By Nonparametric Filtering," Econometric Theory, Cambridge University Press, vol. 32(4), pages 861-916, August.
    2. Zhang, Shulin & Song, Peter X.-K. & Shi, Daimin & Zhou, Qian M., 2012. "Information ratio test for model misspecification on parametric structures in stochastic diffusion models," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3975-3987.
    3. 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.
    4. 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.
    5. Ruijun Bu & Jie Cheng & Kaddour Hadri, 2014. "Reducible Diffusions with Time-Varying Transformations with Application to Short-Term Interest Rates," Economics Working Papers 14-01, Queen's Management School, Queen's University Belfast.
    6. Bu, Ruijun & Hadri, Kaddour & Kristensen, Dennis, 2021. "Diffusion copulas: Identification and estimation," Journal of Econometrics, Elsevier, vol. 221(2), pages 616-643.
    7. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    8. Kristensen, Dennis, 2011. "Semi-nonparametric estimation and misspecification testing of diffusion models," Journal of Econometrics, Elsevier, vol. 164(2), pages 382-403, October.
    9. Dennis Kristensen, 2009. "Semiparametric Modelling and Estimation: A Selective Overview," CREATES Research Papers 2009-44, Department of Economics and Business Economics, Aarhus University.
    10. Chen, Qiang & Zheng, Xu & Pan, Zhiyuan, 2015. "Asymptotically distribution-free tests for the volatility function of a diffusion," Journal of Econometrics, Elsevier, vol. 184(1), pages 124-144.
    11. Koo, Bonsoo & Linton, Oliver, 2012. "Estimation of semiparametric locally stationary diffusion models," Journal of Econometrics, Elsevier, vol. 170(1), pages 210-233.
    12. Seungmoon Choi, 2015. "Maximum Likelihood Estimation of Continuous-Time Diffusion Models for Korean Short-Term Interest Rates," Economic Analysis (Quarterly), Economic Research Institute, Bank of Korea, vol. 21(4), pages 28-58, December.
    13. Buchholz, Nicholas & Shum, Matthew & Xu, Haiqing, 2021. "Semiparametric estimation of dynamic discrete choice models," Journal of Econometrics, Elsevier, vol. 223(2), pages 312-327.
    14. 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.
    15. 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.

  24. Dennis Kristensen, 2009. "Semiparametric Modelling and Estimation: A Selective Overview," CREATES Research Papers 2009-44, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Botosaru, Irene, 2020. "Nonparametric analysis of a duration model with stochastic unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 217(1), pages 112-139.

  25. Dennis Kristensen, 2008. "Uniform Convergence Rates of Kernel Estimators with Heterogenous, Dependent Data," CREATES Research Papers 2008-37, Department of Economics and Business Economics, Aarhus University.

    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. Byrne, Joseph P. & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2022. "The time-varying risk price of currency portfolios," Journal of International Money and Finance, Elsevier, vol. 124(C).
    3. Jiti Gao & Degui Li & Dag Tjøstheim, 2011. "Uniform Consistency for Nonparametric Estimators in Null Recurrent Time Series," Monash Econometrics and Business Statistics Working Papers 13/11, Monash University, Department of Econometrics and Business Statistics.
    4. Dennis Kristensen, 2009. "Semiparametric modelling and estimation (in Russian)," Quantile, Quantile, issue 7, pages 53-83, September.
    5. Tobias Adrian & Richard K. Crump & Emanuel Moench, 2011. "Regression-based estimation of dynamic asset pricing models," Staff Reports 493, Federal Reserve Bank of New York.
    6. 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.
    7. 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.
    8. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
    9. Andrew Ang & Dennis Kristensen, 2011. "Testing Conditional Factor Models," NBER Working Papers 17561, National Bureau of Economic Research, Inc.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. Li, Degui & Phillips, Peter C. B. & Gao, Jiti, 2016. "Uniform Consistency Of Nonstationary Kernel-Weighted Sample Covariances For Nonparametric Regression," Econometric Theory, Cambridge University Press, vol. 32(3), pages 655-685, June.
    15. 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.
    16. Nikolay Gospodinov & Taisuke Otsu, 2008. "Local GMM Estimation of Time Series Models with Conditional Moment Restrictions," Working Papers 08010, Concordia University, Department of Economics.
    17. Debopam Bhattacharya & Shin Kanaya & Margaret Stevens, 2014. "Are University Admissions Academically Fair?," CREATES Research Papers 2014-06, Department of Economics and Business Economics, Aarhus University.
    18. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    19. 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.
    20. Michael Creel & Dennis Kristensen, "undated". "Indirect Likelihood Inference," Working Papers 558, Barcelona School of Economics.
    21. Xiaohong Chen & Timothy M. Christensen, 2014. "Optimal uniform convergence rates and asymptotic normality for series estimators under weak dependence and weak conditions," CeMMAP working papers 46/14, Institute for Fiscal Studies.
    22. Christian Brownlees & Gu{dh}mundur Stef'an Gu{dh}mundsson, 2021. "Performance of Empirical Risk Minimization for Linear Regression with Dependent Data," Papers 2104.12127, arXiv.org, revised May 2023.
    23. Kristensen, Dennis, 2011. "Semi-nonparametric estimation and misspecification testing of diffusion models," Journal of Econometrics, Elsevier, vol. 164(2), pages 382-403, October.
    24. 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.
    25. Michael Creel & Dennis Kristensen, 2014. "ABC of SV: Limited Information Likelihood Inference in Stochastic Volatility Jump-Diffusion Models," CREATES Research Papers 2014-30, Department of Economics and Business Economics, Aarhus University.
    26. Masayuki Hirukawa & Irina Murtazashvili & Artem Prokhorov, 2022. "Uniform convergence rates for nonparametric estimators smoothed by the beta kernel," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1353-1382, September.
    27. Kukacka, Jiri & Sacht, Stephen, 2023. "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    28. Dennis Kristensen, 2009. "Semiparametric Modelling and Estimation: A Selective Overview," CREATES Research Papers 2009-44, Department of Economics and Business Economics, Aarhus University.
    29. 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.
    30. Byrne, Joseph P & Ibrahim, Boulis Maher & Sakemoto, Ryuta, 2017. "The Time-Varying Risk Price of Currency Carry Trades," MPRA Paper 80788, University Library of Munich, Germany.
    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. Jiti Gao & Han Hong, 2014. "Nonparametric Regression Approach to Bayesian Estimation," Monash Econometrics and Business Statistics Working Papers 25/14, Monash University, Department of Econometrics and Business Statistics.
    33. Koo, Bonsoo & Linton, Oliver, 2012. "Estimation of semiparametric locally stationary diffusion models," Journal of Econometrics, Elsevier, vol. 170(1), pages 210-233.
    34. Xiaohong Chen & Timothy M. Christensen, 2014. "Optimal Uniform Convergence Rates and Asymptotic Normality for Series Estimators under Weak Dependence and Weak Conditions," Cowles Foundation Discussion Papers 1976, Cowles Foundation for Research in Economics, Yale University.
    35. 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.
    36. Juan Carlos Escanciano, 2020. "Uniform Rates for Kernel Estimators of Weakly Dependent Data," Papers 2005.09951, arXiv.org.
    37. Kukacka, Jiri & Barunik, Jozef, 2016. "Estimation of financial agent-based models with simulated maximum likelihood," FinMaP-Working Papers 63, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    38. Harold D. Chiang & Bing Yang Tan, 2020. "Empirical likelihood and uniform convergence rates for dyadic kernel density estimation," Papers 2010.08838, arXiv.org, revised May 2022.
    39. 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.
    40. 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.
    41. Maria Mohr & Leonie Selk, 2020. "Estimating change points in nonparametric time series regression models," Statistical Papers, Springer, vol. 61(4), pages 1437-1463, August.
    42. 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.
    43. 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.
    44. Michael Creel & Dennis Kristensen, 2013. "Indirect Likelihood Inference (revised)," UFAE and IAE Working Papers 931.13, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).

  26. Dennis Kristensen & Yongseok Shin, 2008. "Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood," CREATES Research Papers 2008-58, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Dennis Kristensen, 2007. "Nonparametric Estimation and Misspecification Testing of Diffusion Models," CREATES Research Papers 2007-01, Department of Economics and Business Economics, Aarhus University.
    2. Heejoon Han & Dennis Kristensen, 2014. "Asymptotic Theory for the QMLE in GARCH-X Models With Stationary and Nonstationary Covariates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 416-429, July.
    3. Kukacka, Jiri & Jang, Tae-Seok & Sacht, Stephen, 2018. "On the estimation of behavioral macroeconomic models via simulated maximum likelihood," Economics Working Papers 2018-11, Christian-Albrechts-University of Kiel, Department of Economics.
    4. Jozef Barunik & Cathy Yi-Hsuan Chen & Jan Vecer, 2019. "Sentiment-Driven Stochastic Volatility Model: A High-Frequency Textual Tool for Economists," Papers 1906.00059, arXiv.org.
    5. Jiti Gao & Han Hong, 2014. "A Computational Implementation of GMM," Monash Econometrics and Business Statistics Working Papers 24/14, Monash University, Department of Econometrics and Business Statistics.
    6. Dennis Kristensen & Patrick K. Mogensen & Jong Myun Moon & Bertel Schjerning, 2019. "Solving Dynamic Discrete Choice Models Using Smoothing and Sieve Methods," Papers 1904.05232, arXiv.org, revised Feb 2020.
    7. 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.
    8. Giesecke, K. & Schwenkler, G., 2019. "Simulated likelihood estimators for discretely observed jump–diffusions," Journal of Econometrics, Elsevier, vol. 213(2), pages 297-320.
    9. Bu, Ruijun & Hadri, Kaddour & Kristensen, Dennis, 2021. "Diffusion copulas: Identification and estimation," Journal of Econometrics, Elsevier, vol. 221(2), pages 616-643.
    10. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Oct 2021.
    11. Cameron Fen, 2022. "Fast Simulation-Based Bayesian Estimation of Heterogeneous and Representative Agent Models using Normalizing Flow Neural Networks," Papers 2203.06537, arXiv.org.
    12. Michael Creel & Dennis Kristensen, "undated". "Indirect Likelihood Inference," Working Papers 558, Barcelona School of Economics.
    13. ROMBOUTS, Jeroen V.K. & STENTOFT, Lars, 2009. "Bayesian option pricing using mixed normal heteroskedasticity models," LIDAM Discussion Papers CORE 2009013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers CWP45/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Mathias Barkhagen & Jörgen Blomvall & Eckhard Platen, 2015. "Recovering the Real-World Density and Liquidity Premia From Option Data," Research Paper Series 363, Quantitative Finance Research Centre, University of Technology, Sydney.
    16. Guay, François & Schwenkler, Gustavo, 2021. "Efficient estimation and filtering for multivariate jump–diffusions," Journal of Econometrics, Elsevier, vol. 223(1), pages 251-275.
    17. Valentina Corradi & Norman R. Swanson, 2009. "Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models," Working Papers 09-29, Federal Reserve Bank of Philadelphia.
    18. Kristensen, Dennis, 2011. "Semi-nonparametric estimation and misspecification testing of diffusion models," Journal of Econometrics, Elsevier, vol. 164(2), pages 382-403, October.
    19. Diep Duong & Norman Swanson, 2013. "Density and Conditional Distribution Based Specification Analysis," Departmental Working Papers 201312, Rutgers University, Department of Economics.
    20. Johan Hagenbjörk & Jörgen Blomvall, 2019. "Simulation and evaluation of the distribution of interest rate risk," Computational Management Science, Springer, vol. 16(1), pages 297-327, February.
    21. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    22. Mario Martinoli & Raffaello Seri & Fulvio Corsi, 2024. "Generalized Optimization Algorithms for Complex Models," LEM Papers Series 2024/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    23. Kukacka, Jiri & Sacht, Stephen, 2023. "Estimation of heuristic switching in behavioral macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 146(C).
    24. Kristensen, Dennis, 2008. "Estimation of partial differential equations with applications in finance," Journal of Econometrics, Elsevier, vol. 144(2), pages 392-408, June.
    25. Marianne Bruins & James A. Duffy & Michael P. Keane & Anthony A. Smith, Jr, 2015. "Generalized Indirect Inference for Discrete Choice Models," Economics Papers 2015-W08, Economics Group, Nuffield College, University of Oxford.
    26. Jakob Grazzini & Matteo G. Richiardi, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," LABORatorio R. Revelli Working Papers Series 130, LABORatorio R. Revelli, Centre for Employment Studies.
    27. Paola Stolfi & Mauro Bernardi & Lea Petrella, 2018. "The sparse method of simulated quantiles: An application to portfolio optimization," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 375-398, August.
    28. Dennis Kristensen, 2008. "Uniform Convergence Rates of Kernel Estimators with Heterogenous, Dependent Data," CREATES Research Papers 2008-37, Department of Economics and Business Economics, Aarhus University.
    29. Jiti Gao & Han Hong, 2014. "Nonparametric Regression Approach to Bayesian Estimation," Monash Econometrics and Business Statistics Working Papers 25/14, Monash University, Department of Econometrics and Business Statistics.
    30. Dennis Kristensen & Young Jun Lee & Antonio Mele, 2023. "Closed-form approximations of moments and densities of continuous-time Markov models," Papers 2308.09009, arXiv.org.
    31. Judge, George G., 2012. "The information theoretic foundations of a probabilistic and predictive micro and macro economics," CUDARE Working Papers 122890, University of California, Berkeley, Department of Agricultural and Resource Economics.
    32. 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.
    33. Yanqiao Zheng & Xiaobing Zhao & Xiaoqi Zhang & Xinyue Ye & Qiwen Dai, 2019. "Mining the Hidden Link Structure from Distribution Flows for a Spatial Social Network," Complexity, Hindawi, vol. 2019, pages 1-17, May.
    34. Kukacka, Jiri & Barunik, Jozef, 2016. "Estimation of financial agent-based models with simulated maximum likelihood," FinMaP-Working Papers 63, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    35. Jean-Jacques Forneron, 2019. "A Sieve-SMM Estimator for Dynamic Models," Papers 1902.01456, arXiv.org, revised Jan 2023.
    36. Kerem Tuzcuoglu, 2019. "Composite Likelihood Estimation of an Autoregressive Panel Probit Model with Random Effects," Staff Working Papers 19-16, Bank of Canada.
    37. Shiono, Takashi, 2021. "Estimation of agent-based models using Bayesian deep learning approach of BayesFlow," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    38. Lee, Donghoon & Song, Kyungchul, 2015. "Simulated maximum likelihood estimation for discrete choices using transformed simulated frequencies," Journal of Econometrics, Elsevier, vol. 187(1), pages 131-153.
    39. Brownlees, Christian T., 2019. "Hierarchical GARCH," Journal of Empirical Finance, Elsevier, vol. 51(C), pages 17-27.
    40. Michael Creel & Dennis Kristensen, 2013. "Indirect Likelihood Inference (revised)," UFAE and IAE Working Papers 931.13, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).

  27. Dennis Kristensen & Anders Rahbek, 2007. "Likelihood-Based Inference in Nonlinear Error-Correction Models," CREATES Research Papers 2007-38, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Nedeljkovic, Milan, 2008. "Testing for Smooth Transition Nonlinearity in Adjustments of Cointegrating Systems," The Warwick Economics Research Paper Series (TWERPS) 876, University of Warwick, Department of Economics.
    2. Dirk G Baur & Duy T. Tran, 2012. "The Long-run Relationship of Gold and Silver and the Influence of Bubbles and Financial Crises," Working Paper Series 172, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    3. Marçal, Emerson Fernandes & Pereira, Pedro L. Valls, 2012. "Evaluating the existence of structural change in the brazilian term structure of interest: evidence based on cointegration models with structural break," Textos para discussão 314, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).

  28. Dennis Kristensen, 2007. "Nonparametric Estimation and Misspecification Testing of Diffusion Models," CREATES Research Papers 2007-01, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Kristensen, Dennis, 2011. "Semi-nonparametric estimation and misspecification testing of diffusion models," Journal of Econometrics, Elsevier, vol. 164(2), pages 382-403, October.
    2. Kristensen, Dennis, 2008. "Estimation of partial differential equations with applications in finance," Journal of Econometrics, Elsevier, vol. 144(2), pages 392-408, June.
    3. Papanicolaou, Alex & Giesecke, Kay, 2016. "Variation-based tests for volatility misspecification," Journal of Econometrics, Elsevier, vol. 191(1), pages 217-230.

  29. Dennis Kristensen, 2007. "Nonparametric Filtering of the Realised Spot Volatility: A Kernel-based Approach," CREATES Research Papers 2007-02, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Kanaya, Shin & Kristensen, Dennis, 2016. "Estimation Of Stochastic Volatility Models By Nonparametric Filtering," Econometric Theory, Cambridge University Press, vol. 32(4), pages 861-916, August.
    2. Bellia, Mario & Christensen, Kim & Kolokolov, Aleksey & Pelizzon, Loriana & Renò, Roberto, 2022. "Do designated market makers provide liquidity during a flash crash?," SAFE Working Paper Series 270, Leibniz Institute for Financial Research SAFE, revised 2022.
    3. 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.
    4. Kanaya, Shin, 2016. "Convergence rates of sums of α-mixing triangular arrays : with an application to non-parametric drift function estimation of continuous-time processes," Discussion Paper Series 646, Institute of Economic Research, Hitotsubashi University.
    5. Christensen, Kim & Oomen, Roel & Renò, Roberto, 2022. "The drift burst hypothesis," Journal of Econometrics, Elsevier, vol. 227(2), pages 461-497.
    6. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2017. "Decoupling the short- and long-term behavior of stochastic volatility," CREATES Research Papers 2017-26, Department of Economics and Business Economics, Aarhus University.
    7. 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.
    8. Cecilia Mancini & Vanessa Mattiussi & Roberto Reno', 2012. "Spot Volatility Estimation Using Delta Sequences," Working Papers - Mathematical Economics 2012-10, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    9. Ouimet, Frédéric & Tolosana-Delgado, Raimon, 2022. "Asymptotic properties of Dirichlet kernel density estimators," Journal of Multivariate Analysis, Elsevier, vol. 187(C).
    10. Andrew Ang & Dennis Kristensen, 2011. "Testing Conditional Factor Models," NBER Working Papers 17561, National Bureau of Economic Research, Inc.
    11. Todorov, Viktor & Zhang, Yang, 2023. "Bias reduction in spot volatility estimation from options," Journal of Econometrics, Elsevier, vol. 234(1), pages 53-81.
    12. Müller, Hans-Georg & Sen, Rituparna & Stadtmüller, Ulrich, 2011. "Functional data analysis for volatility," Journal of Econometrics, Elsevier, vol. 165(2), pages 233-245.
    13. He, Lidan & Liu, Qiang & Liu, Zhi, 2020. "Edgeworth corrections for spot volatility estimator," Statistics & Probability Letters, Elsevier, vol. 164(C).
    14. Kris Boudt & Sébastien Laurent & Asger Lunde & Rogier Quaedvlieg & Orimar Sauri, 2017. "Positive semidefinite integrated covariance estimation, factorizations and asynchronicity," Post-Print hal-01505775, HAL.
    15. 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.
    16. Liu, Qiang & Liu, Yiqi & Liu, Zhi, 2018. "Estimating spot volatility in the presence of infinite variation jumps," Stochastic Processes and their Applications, Elsevier, vol. 128(6), pages 1958-1987.
    17. Mikkel Bennedsen & Asger Lunde & Mikko S. Pakkanen, 2016. "Decoupling the short- and long-term behavior of stochastic volatility," Papers 1610.00332, arXiv.org, revised Jan 2021.
    18. Bandi, Federico & Corradi, Valentina & Moloche, Guillermo, 2009. "Bandwidth selection for continuous-time Markov processes," MPRA Paper 43682, University Library of Munich, Germany.
    19. Bech, Morten L. & Lengwiler, Yvan, 2012. "The Financial Crisis and the Changing Dynamics of the Yield Curve," Working papers 2012/06, Faculty of Business and Economics - University of Basel.
    20. Federico M. Bandi & Roberto Reno, 2009. "Nonparametric Stochastic Volatility," Global COE Hi-Stat Discussion Paper Series gd08-035, Institute of Economic Research, Hitotsubashi University.
    21. Tim Bollerslev & Jia Li & Andrew J. Patton & Rogier Quaedvlieg, 2020. "Realized Semicovariances," Econometrica, Econometric Society, vol. 88(4), pages 1515-1551, July.
    22. Bollerslev, Tim & Li, Jia & Li, Qiyuan, 2024. "Optimal nonparametric range-based volatility estimation," Journal of Econometrics, Elsevier, vol. 238(1).
    23. Ilze Kalnina & Natalia Sizova, 2015. "Estimation of volatility measures using high frequency data (in Russian)," Quantile, Quantile, issue 13, pages 3-14, May.
    24. Mustafayeva, Konul & Wang, Weining, 2020. "Non-Parametric Estimation of Spot Covariance Matrix with High-Frequency Data," IRTG 1792 Discussion Papers 2020-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    25. Jia Li & Dacheng Xiu, 2016. "Generalized Method of Integrated Moments for High‐Frequency Data," Econometrica, Econometric Society, vol. 84, pages 1613-1633, July.
    26. Funke, Benedikt & Hirukawa, Masayuki, 2019. "Nonparametric estimation and testing on discontinuity of positive supported densities: a kernel truncation approach," Econometrics and Statistics, Elsevier, vol. 9(C), pages 156-170.
    27. Almut E. D. Veraart, 2010. "How precise is the finite sample approximation of the asymptotic distribution of realised variation measures in the presence of jumps?," CREATES Research Papers 2010-65, Department of Economics and Business Economics, Aarhus University.
    28. Hautsch, Nikolaus & Scheuch, Christoph & Voigt, Stefan, 2018. "Limits to arbitrage in markets with stochastic settlement latency," CFS Working Paper Series 616, Center for Financial Studies (CFS).
    29. Li, Gang & Zhang, Chu, 2016. "On the relationship between conditional jump intensity and diffusive volatility," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 196-213.
    30. Nikolaus Hautsch & Christoph Scheu & Stefan Voigt, 2024. "Building trust takes time: limits to arbitrage for blockchain-based assets," Review of Finance, European Finance Association, vol. 28(4), pages 1345-1381.
    31. Mark Podolskij & Mathieu Rosenbaum, 2012. "Testing the local volatility assumption: a statistical approach," Annals of Finance, Springer, vol. 8(1), pages 31-48, February.
    32. Tim Bollerslev & Jia Li & Zhipeng Liao, 2021. "Fixed‐k inference for volatility," Quantitative Economics, Econometric Society, vol. 12(4), pages 1053-1084, November.
    33. 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.
    34. 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.
    35. Selma Chaker, 2013. "Volatility and Liquidity Costs," Staff Working Papers 13-29, Bank of Canada.
    36. Masayuki Hirukawa & Irina Murtazashvili & Artem Prokhorov, 2022. "Uniform convergence rates for nonparametric estimators smoothed by the beta kernel," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1353-1382, September.
    37. Li, Degui, 2024. "Estimation of Large Dynamic Covariance Matrices: A Selective Review," Econometrics and Statistics, Elsevier, vol. 29(C), pages 16-30.
    38. Isabel Casas & Irene Gijbels, 2009. "Unstable volatility functions: the break preserving local linear estimator," CREATES Research Papers 2009-48, Department of Economics and Business Economics, Aarhus University.
    39. Boudt, Kris & Cornelissen, Jonathan & Croux, Christophe, 2012. "Jump robust daily covariance estimation by disentangling variance and correlation components," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 2993-3005.
    40. Ghysels, Eric, 2014. "Factor Analysis with Large Panels of Volatility Proxies," CEPR Discussion Papers 10034, C.E.P.R. Discussion Papers.
    41. Dalderop, Jeroen, 2020. "Nonparametric filtering of conditional state-price densities," Journal of Econometrics, Elsevier, vol. 214(2), pages 295-325.
    42. Richard Y. Chen, 2019. "The Fourier Transform Method for Volatility Functional Inference by Asynchronous Observations," Papers 1911.02205, arXiv.org.
    43. Ilze KALNINA & Kokouvi TEWOU, 2015. "Cross-sectional Dependence in Idiosyncratic Volatility," Cahiers de recherche 08-2015, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    44. Song Yuping & Hou Weijie & Zhou Shengyi, 2019. "Variance reduction estimation for return models with jumps using gamma asymmetric kernels," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(5), pages 1-38, December.
    45. Kalnina, Ilze, 2011. "Subsampling high frequency data," Journal of Econometrics, Elsevier, vol. 161(2), pages 262-283, April.
    46. 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.
    47. Liu, Qiang & Liu, Yiqi & Liu, Zhi & Wang, Li, 2018. "Estimation of spot volatility with superposed noisy data," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 62-79.
    48. Dennis Kristensen, 2008. "Uniform Convergence Rates of Kernel Estimators with Heterogenous, Dependent Data," CREATES Research Papers 2008-37, Department of Economics and Business Economics, Aarhus University.
    49. José E. Figueroa-López & Cheng Li & Jeffrey Nisen, 2020. "Optimal iterative threshold-kernel estimation of jump diffusion processes," Statistical Inference for Stochastic Processes, Springer, vol. 23(3), pages 517-552, October.
    50. Chao Yu & Yue Fang & Zeng Li & Bo Zhang & Xujie Zhao, 2014. "Non-Parametric Estimation Of High-Frequency Spot Volatility For Brownian Semimartingale With Jumps," Journal of Time Series Analysis, Wiley Blackwell, vol. 35(6), pages 572-591, November.
    51. Ruijun Bu & Degui Li & Oliver Linton & Hanchao Wang, 2022. "Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data," Working Papers 202212, University of Liverpool, Department of Economics.
    52. Torben G. Andersen & Martin Thyrsgaard & Viktor Todorov, 2021. "Recalcitrant betas: Intraday variation in the cross‐sectional dispersion of systematic risk," Quantitative Economics, Econometric Society, vol. 12(2), pages 647-682, May.
    53. Gospodinov, Nikolay & Hirukawa, Masayuki, 2012. "Nonparametric estimation of scalar diffusion models of interest rates using asymmetric kernels," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 595-609.
    54. Jessen, Cathrine & Lando, David, 2015. "Robustness of distance-to-default," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 493-505.
    55. 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.
    56. Park, Joon Y. & Wang, Bin, 2021. "Nonparametric estimation of jump diffusion models," Journal of Econometrics, Elsevier, vol. 222(1), pages 688-715.
    57. Li, Jia & Todorov, Viktor & Tauchen, George, 2017. "Adaptive estimation of continuous-time regression models using high-frequency data," Journal of Econometrics, Elsevier, vol. 200(1), pages 36-47.
    58. Fulvio Corsi & Davide Pirino & Roberto Renò, 2008. "Volatility forecasting: the jumps do matter," Department of Economics University of Siena 534, Department of Economics, University of Siena.
    59. Zu, Yang & Peter Boswijk, H., 2014. "Estimating spot volatility with high-frequency financial data," Journal of Econometrics, Elsevier, vol. 181(2), pages 117-135.
    60. Mohamed Chikhi & Ali Bendob, 2018. "Nonparametric NAR-ARCH Modelling of Stock Prices by the Kernel Methodology," Journal of Economics and Financial Analysis, Tripal Publishing House, vol. 2(2), pages 105-120.
    61. Figueroa-López, José E. & Li, Cheng, 2020. "Optimal kernel estimation of spot volatility of stochastic differential equations," Stochastic Processes and their Applications, Elsevier, vol. 130(8), pages 4693-4720.
    62. Qiang Liu & Zhi Liu & Chuanhai Zhang, 2020. "Heteroscedasticity test of high-frequency data with jumps and microstructure noise," Papers 2010.07659, arXiv.org.
    63. Yu, Chao & Fang, Yue & Zhao, Xujie & Zhang, Bo, 2013. "Kernel filtering of spot volatility in presence of Lévy jumps and market microstructure noise," MPRA Paper 63293, University Library of Munich, Germany, revised 10 Mar 2014.
    64. Cuchiero, Christa & Teichmann, Josef, 2015. "Fourier transform methods for pathwise covariance estimation in the presence of jumps," Stochastic Processes and their Applications, Elsevier, vol. 125(1), pages 116-160.
    65. Li, Jia & Patton, Andrew J., 2018. "Asymptotic inference about predictive accuracy using high frequency data," Journal of Econometrics, Elsevier, vol. 203(2), pages 223-240.
    66. Zhang, Congshan & Li, Jia & Bollerslev, Tim, 2022. "Occupation density estimation for noisy high-frequency data," Journal of Econometrics, Elsevier, vol. 227(1), pages 189-211.
    67. 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.
    68. Nikolay Gospodinov & Masayuki Hirukawa, 2008. "Nonparametric Estimation of Scalar Diffusion Processes of Interest Rates Using Asymmetric Kernels," Working Papers 08011, Concordia University, Department of Economics, revised Dec 2008.
    69. Sujin Park & Oliver Linton, 2012. "Estimating the Quadratic Covariation Matrix for an Asynchronously Observed Continuous Time Signal Masked by Additive Noise," FMG Discussion Papers dp703, Financial Markets Group.
    70. Curato, Imma Valentina & Mancino, Maria Elvira & Recchioni, Maria Cristina, 2018. "Spot volatility estimation using the Laplace transform," Econometrics and Statistics, Elsevier, vol. 6(C), pages 22-43.
    71. Olivier F'eron & Peter Tankov & Laura Tinsi, 2020. "Price formation and optimal trading in intraday electricity markets," Papers 2009.04786, arXiv.org, revised Jun 2021.
    72. B. Cooper Boniece & Jos'e E. Figueroa-L'opez & Yuchen Han, 2023. "Data-driven fixed-point tuning for truncated realized variations," Papers 2311.00905, arXiv.org, revised Oct 2024.
    73. Jos'e E. Figueroa-L'opez & Cheng Li, 2016. "Optimal Kernel Estimation of Spot Volatility of Stochastic Differential Equations," Papers 1612.04507, arXiv.org.

  30. Kristensen, Dennis, 2004. "A semiparametric single-factor model of the term structure," LSE Research Online Documents on Economics 24741, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. 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.
    2. Choi Seungmoon, 2009. "Regime-Switching Univariate Diffusion Models of the Short-Term Interest Rate," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(1), pages 1-41, March.
    3. Dennis Kristensen, 2004. "Estimation in Two Classes of Semiparametric Diffusion Models," FMG Discussion Papers dp500, Financial Markets Group.
    4. Kristensen, Dennis, 2008. "Estimation of partial differential equations with applications in finance," Journal of Econometrics, Elsevier, vol. 144(2), pages 392-408, June.
    5. Petros Dellaportas & David G. T. Denison & Chris Holmes, 2007. "Flexible Threshold Models for Modelling Interest Rate Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 419-437.

  31. Kristensen, Dennis, 2004. "Estimation of partial differential equations with applications in finance," LSE Research Online Documents on Economics 24738, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. Dennis Kristensen & Antonio Mele, 2009. "Adding and Subtracting Black-Scholes: A New Approach to Approximating Derivative Prices in Continuous Time Models," CREATES Research Papers 2009-14, Department of Economics and Business Economics, Aarhus University.
    2. 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.
    3. 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.
    4. Kristensen, Dennis, 2011. "Semi-nonparametric estimation and misspecification testing of diffusion models," Journal of Econometrics, Elsevier, vol. 164(2), pages 382-403, October.
    5. Koo, Bonsoo & Linton, Oliver, 2012. "Estimation of semiparametric locally stationary diffusion models," Journal of Econometrics, Elsevier, vol. 170(1), pages 210-233.
    6. Gospodinov, Nikolay & Hirukawa, Masayuki, 2012. "Nonparametric estimation of scalar diffusion models of interest rates using asymmetric kernels," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 595-609.
    7. 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.
    8. Nikolay Gospodinov & Masayuki Hirukawa, 2008. "Nonparametric Estimation of Scalar Diffusion Processes of Interest Rates Using Asymmetric Kernels," Working Papers 08011, Concordia University, Department of Economics, revised Dec 2008.
    9. 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.

  32. Kristensen, Dennis, 2004. "Estimation in two classes of semiparametric diffusion models," LSE Research Online Documents on Economics 24739, London School of Economics and Political Science, LSE Library.

    Cited by:

    1. 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.
    2. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    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. Kristensen, Dennis, 2008. "Estimation of partial differential equations with applications in finance," Journal of Econometrics, Elsevier, vol. 144(2), pages 392-408, June.
    5. Fuchun Li, 2005. "Testing the Parametric Specification of the Diffusion Function in a Diffusion Process," Staff Working Papers 05-35, Bank of Canada.
    6. Xu, Ke-Li, 2009. "Empirical likelihood-based inference for nonparametric recurrent diffusions," Journal of Econometrics, Elsevier, vol. 153(1), pages 65-82, November.
    7. Yu, Jialin, 2007. "Closed-form likelihood approximation and estimation of jump-diffusions with an application to the realignment risk of the Chinese Yuan," Journal of Econometrics, Elsevier, vol. 141(2), pages 1245-1280, December.

  33. Richard Blundell & Xiaohong Chen & Dennis Kristensen, 2003. "Nonparametric IV estimation of shape-invariant Engel curves," CeMMAP working papers CWP15/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    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. Giuseppe De Luca & Franco Peracchi, 2010. "Estimating Engel curves under unit and item nonresponse," EIEF Working Papers Series 1004, Einaudi Institute for Economics and Finance (EIEF), revised Nov 2010.
    3. Dennis Kristensen, 2009. "Semiparametric modelling and estimation (in Russian)," Quantile, Quantile, issue 7, pages 53-83, September.
    4. Laurent Davezies & Thomas Le Barbanchon, 2014. "Regression Discontinuity Design with Continuous Measurement Error in the Running Variable," Working Papers 2014-27, Center for Research in Economics and Statistics.
    5. 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.
    6. 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).
    7. Cherchye, L.J.H. & Demuynck, T. & de Rock, B., 2009. "Degrees of Cooperation in Household Consumption Models : A Revealed Preference Analysis," Other publications TiSEM 097597d5-7724-4d31-b044-e, Tilburg University, School of Economics and Management.
    8. Carrasco, Marine & Florens, Jean-Pierre, 2002. "Spectral Method for Deconvolving a Density," IDEI Working Papers 138, Institut d'Économie Industrielle (IDEI), Toulouse, revised 2009.
    9. Yingyao Hu & Ji-Liang Shiu, 2011. "Nonparametric identification using instrumental variables: sufficient conditions for completeness," CeMMAP working papers CWP25/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Victor Chernozhukov & Ivan Fernandez-Val & Amanda Kowalski, 2011. "Quantile Regression with Censoring and Endogeneity," Cowles Foundation Discussion Papers 1797, Cowles Foundation for Research in Economics, Yale University.
    11. Oulton, Nicholas, 2009. "How to measure living standards and productivity," LSE Research Online Documents on Economics 28678, London School of Economics and Political Science, LSE Library.
    12. Xavier d'Haultfoeuille, 2006. "On the Completeness Condition in Nonparametric Instrumental Problems," Working Papers 2006-32, Center for Research in Economics and Statistics.
    13. Breunig, Christoph, 2012. "Goodness-of-fit tests based on series estimators in nonparametric instrumental regression," Working Papers 12-13, University of Mannheim, Department of Economics.
    14. Ai, Chunrong & Chen, Xiaohong, 2012. "The semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions," Journal of Econometrics, Elsevier, vol. 170(2), pages 442-457.
    15. JOHANNES, Jan & VAN BELLEGEM, Sébastien & VANHEMS, Anne, 2011. "Convergence rates for ill-posed inverse problems with an unknown operator," LIDAM Reprints CORE 2330, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    16. Stefan Hoderlein & Lars Nesheim & Anna Simoni, 2012. "Semiparametric estimation of random coefficients in structural economic models," CeMMAP working papers CWP09/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. Pendakur, Krishna & Scholz, Michael & Sperlich, Stefan, 2010. "Semiparametric indirect utility and consumer demand," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2763-2775, November.
    18. Barigozzi, Matteo & Alessi, Lucia & Capasso, Marco & Fagiolo, Giorgio, 2009. "The distribution of households consumption-expenditure budget shares," Working Paper Series 1061, European Central Bank.
    19. Arthur Lewbel & Krishna Pendakur, 2006. "Tricks With Hicks: The EASI Demand System," Boston College Working Papers in Economics 651, Boston College Department of Economics, revised 26 Nov 2008.
    20. Syed Abul Hasan, 2012. "Engel Curves and Equivalence Scales for Bangladesh," ASARC Working Papers 2012-15, The Australian National University, Australia South Asia Research Centre.
    21. Dennis Kristensen, 2009. "Semiparametric Modelling and Estimation: A Selective Overview," CREATES Research Papers 2009-44, Department of Economics and Business Economics, Aarhus University.
    22. Antonio Merlo & Aureo de Paula, 2010. "Identification and Estimation of Preference Distributions When Voters Are Ideological, Second Version," PIER Working Paper Archive 13-055, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 13 Oct 2013.
    23. Joel L. Horowitz, 2004. "Testing a parametric model against a nonparametric alternative with identification through instrumental variables," CeMMAP working papers CWP14/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    24. Xavier d'Haultfoeuille, 2008. "A New Instrumental Method for Dealing with Endogenous Selection," Working Papers 2008-23, Center for Research in Economics and Statistics.
    25. Yingyao Hu & Susanne M. Schennach, 2008. "Instrumental Variable Treatment of Nonclassical Measurement Error Models," Econometrica, Econometric Society, vol. 76(1), pages 195-216, January.
    26. Horowitz, Joel L. & Lee, Sokbae, 2009. "Testing a parametric quantile-regression model with an endogenous explanatory variable against a nonparametric alternative," Journal of Econometrics, Elsevier, vol. 152(2), pages 141-152, October.
    27. Yevgeniy Kovchegov & Nese Yildiz, 2012. "Identification via completeness for discrete covariates and orthogonal polynomials," Koç University-TUSIAD Economic Research Forum Working Papers 1203, Koc University-TUSIAD Economic Research Forum.
    28. Yonghong An & Yingyao Hu, 2009. "Well-posedness of measurement error models for self-reported data," CeMMAP working papers CWP35/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Krishna Pendakur & Stefan Sperlich, 2010. "Semiparametric estimation of consumer demand systems in real expenditure," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(3), pages 420-457.
    30. Richard Blundell & Joel L. Horowitz, 2004. "A nonparametric test of exogeneity," CeMMAP working papers CWP15/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    31. Senay Sokullu, 2012. "Nonparametric Analysis of Two-Sided Markets," Bristol Economics Discussion Papers 12/628, School of Economics, University of Bristol, UK.
    32. Matteo Barigozzi & Lucia Alessi & Marco Capasso & Giorgio Fagiolo, 2008. "The Distribution of Consumption-Expenditure Budget Shares. Evidence from Italian Households," Papers on Economics and Evolution 2008-09, Philipps University Marburg, Department of Geography.

Articles

  1. Mogens Fosgerau & Dennis Kristensen, 2021. "Identification of a class of index models: A topological approach," The Econometrics Journal, Royal Economic Society, vol. 24(1), pages 121-133.
    See citations under working paper version above.
  2. Kristensen, Dennis & Mogensen, Patrick K. & Moon, Jong Myun & Schjerning, Bertel, 2021. "Solving dynamic discrete choice models using smoothing and sieve methods," Journal of Econometrics, Elsevier, vol. 223(2), pages 328-360.
    See citations under working paper version above.
  3. Kristensen, Dennis & Salanié, Bernard, 2017. "Higher-order properties of approximate estimators," Journal of Econometrics, Elsevier, vol. 198(2), pages 189-208.
    See citations under working paper version above.
  4. Agosto, Arianna & Cavaliere, Giuseppe & Kristensen, Dennis & Rahbek, Anders, 2016. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 640-663.
    See citations under working paper version above.
  5. Kanaya, Shin & Kristensen, Dennis, 2016. "Estimation Of Stochastic Volatility Models By Nonparametric Filtering," Econometric Theory, Cambridge University Press, vol. 32(4), pages 861-916, August.
    See citations under working paper version above.
  6. Creel, Michael & Kristensen, Dennis, 2016. "On selection of statistics for approximate Bayesian computing (or the method of simulated moments)," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 99-114.
    See citations under working paper version above.
  7. 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.
    See citations under working paper version above.
  8. Creel, Michael & Kristensen, Dennis, 2015. "ABC of SV: Limited information likelihood inference in stochastic volatility jump-diffusion models," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 85-108.
    See citations under working paper version above.
  9. Heejoon Han & Dennis Kristensen, 2014. "Asymptotic Theory for the QMLE in GARCH-X Models With Stationary and Nonstationary Covariates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 416-429, July.
    See citations under working paper version above.
  10. Blundell, Richard & Kristensen, Dennis & Matzkin, Rosa, 2014. "Bounding quantile demand functions using revealed preference inequalities," Journal of Econometrics, Elsevier, vol. 179(2), pages 112-127.
    See citations under working paper version above.
  11. Kristensen, Dennis & Rahbek, Anders, 2013. "Testing And Inference In Nonlinear Cointegrating Vector Error Correction Models," Econometric Theory, Cambridge University Press, vol. 29(6), pages 1238-1288, December.
    See citations under working paper version above.
  12. Richard Blundell & Dennis Kristensen & Rosa L. Matzkin, 2013. "Control Functions and Simultaneous Equations Methods," American Economic Review, American Economic Association, vol. 103(3), pages 563-569, May.

    Cited by:

    1. Steven Berry & Philip Haile, 2023. "Nonparametric Identification of Differentiated Products Demand Using Micro Data," Cowles Foundation Discussion Papers 2357, Cowles Foundation for Research in Economics, Yale University.
    2. Xin Geng & Carlos Martins-Filho & Feng Yao, 2015. "Estimation of a Partially Linear Regression in Triangular Systems," Working Papers 15-46, Department of Economics, West Virginia University.
    3. 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.
    4. Meinen, Philipp & Parrotta, Pierpaolo & Sala, Davide & Yalcin, Erdal, 2022. "Managers as knowledge carriers – Explaining firms’ internationalization success with manager mobility," Journal of International Economics, Elsevier, vol. 138(C).
    5. Cheuk Yin Ho, 2016. "Better Health With More Friends: The Role of Social Capital in Producing Health," Health Economics, John Wiley & Sons, Ltd., vol. 25(1), pages 91-100, January.
    6. Zorlu, Aslan & Hartog, Joop, 2018. "The Impact of Language on Socioeconomic Integration of Immigrants," IZA Discussion Papers 11485, Institute of Labor Economics (IZA).
    7. Blundell, Richard & Kristensen, Dennis & Matzkin, Rosa, 2014. "Bounding quantile demand functions using revealed preference inequalities," Journal of Econometrics, Elsevier, vol. 179(2), pages 112-127.
    8. Brown, Sarah & Taylor, Karl, 2015. "Charitable Behaviour and the Big Five Personality Traits: Evidence from UK Panel Data," IZA Discussion Papers 9318, Institute of Labor Economics (IZA).
    9. Julia Pullbeck & Firmin Doko Tchatoka, 2020. "Inherent effects of corruption on the erosion of political trust in developing countries:Evidence from Ghana," School of Economics and Public Policy Working Papers 2020-01, University of Adelaide, School of Economics and Public Policy.

  13. Dennis Kristensen, 2012. "Non‐parametric detection and estimation of structural change," Econometrics Journal, Royal Economic Society, vol. 15(3), pages 420-461, October.
    See citations under working paper version above.
  14. Michael Creel & Dennis Kristensen, 2012. "Estimation of dynamic latent variable models using simulated non‐parametric moments," Econometrics Journal, Royal Economic Society, vol. 15(3), pages 490-515, October.
    See citations under working paper version above.
  15. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    See citations under working paper version above.
  16. Ang, Andrew & Kristensen, Dennis, 2012. "Testing conditional factor models," Journal of Financial Economics, Elsevier, vol. 106(1), pages 132-156.
    See citations under working paper version above.
  17. Kristensen, Dennis, 2011. "Semi-nonparametric estimation and misspecification testing of diffusion models," Journal of Econometrics, Elsevier, vol. 164(2), pages 382-403, October.
    See citations under working paper version above.
  18. Kristensen, Dennis & Mele, Antonio, 2011. "Adding and subtracting Black-Scholes: A new approach to approximating derivative prices in continuous-time models," Journal of Financial Economics, Elsevier, vol. 102(2), pages 390-415.
    See citations under working paper version above.
  19. Kristensen, Dennis, 2010. "Nonparametric Filtering Of The Realized Spot Volatility: A Kernel-Based Approach," Econometric Theory, Cambridge University Press, vol. 26(1), pages 60-93, February.
    See citations under working paper version above.
  20. Kristensen, Dennis, 2010. "Pseudo-maximum likelihood estimation in two classes of semiparametric diffusion models," Journal of Econometrics, Elsevier, vol. 156(2), pages 239-259, June.
    See citations under working paper version above.
  21. Kristensen, Dennis & Rahbek, Anders, 2010. "Likelihood-based inference for cointegration with nonlinear error-correction," Journal of Econometrics, Elsevier, vol. 158(1), pages 78-94, September.

    Cited by:

    1. Giuseppe Cavaliere & Thomas Mikosch & Anders Rahbek & Frederik Vilandt, 2022. "The Econometrics of Financial Duration Modeling," Papers 2208.02098, arXiv.org, revised Dec 2022.
    2. Heejoon Han & Dennis Kristensen, 2014. "Asymptotic Theory for the QMLE in GARCH-X Models With Stationary and Nonstationary Covariates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 416-429, July.
    3. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    4. Georg Keilbar & Yanfen Zhang, 2021. "On cointegration and cryptocurrency dynamics," Digital Finance, Springer, vol. 3(1), pages 1-23, March.
    5. Dark, Jonathan, 2015. "Futures hedging with Markov switching vector error correction FIEGARCH and FIAPARCH," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 269-285.
    6. Kazuhiko Hayakawa & M. Hashem Pesaran & L. Vanessa Smith, 2023. "Short T dynamic panel data models with individual, time and interactive effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 940-967, September.
    7. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    8. Vanessa Berenguer-Rico & Bent Nielsen, 2015. "Cumulated sum of squares statistics for non-linear and non-stationary regressions," Economics Papers 2015-W09, Economics Group, Nuffield College, University of Oxford.
    9. Andreas Hetland, 2018. "The Stochastic Stationary Root Model," Econometrics, MDPI, vol. 6(3), pages 1-33, August.
    10. Skrobotov, Anton, 2021. "Structural breaks in cointegration models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 117-141.
    11. Escribano, Alvaro & Peña, Daniel & Ruiz, Esther, 2021. "30 years of cointegration and dynamic factor models forecasting and its future with big data: Editorial," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1333-1337.
    12. James A. Duffy & Sophocles Mavroeidis & Sam Wycherley, 2022. "Cointegration with Occasionally Binding Constraints," Papers 2211.09604, arXiv.org, revised Jul 2023.
    13. James A. Duffy & Sophocles Mavroeidis, 2024. "Common Trends and Long-Run Identification in Nonlinear Structural VARs," Papers 2404.05349, arXiv.org, revised Sep 2024.
    14. Cavaliere, Giuseppe & Mikosch, Thomas & Rahbek, Anders & Vilandt, Frederik, 2024. "Tail behavior of ACD models and consequences for likelihood-based estimation," Journal of Econometrics, Elsevier, vol. 238(2).

  22. Kristensen, Dennis, 2009. "Uniform Convergence Rates Of Kernel Estimators With Heterogeneous Dependent Data," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1433-1445, October.
    See citations under working paper version above.
  23. Dennis Kristensen, 2009. "On stationarity and ergodicity of the bilinear model with applications to GARCH models," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 125-144, January.

    Cited by:

    1. Elena Andreou, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," University of Cyprus Working Papers in Economics 03-2016, University of Cyprus Department of Economics.
    2. Abdelouahab Bibi & Ahmed Ghezal, 2016. "On periodic time-varying bilinear processes: structure and asymptotic inference," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(3), pages 395-420, August.
    3. Marcella Niglio & Cosimo Damiano Vitale, 2012. "Local Unit Roots and Global Stationarity of TARMA Models," Methodology and Computing in Applied Probability, Springer, vol. 14(1), pages 17-34, March.
    4. Abdelhakim Aknouche & Nadia Rabehi, 2010. "On an independent and identically distributed mixture bilinear time‐series model," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(2), pages 113-131, March.
    5. Martinez, O. & Olmo, J., 2008. "A Nonlinear Threshold Model for the Dependence of Extremes of Stationary Sequences," Working Papers 08/08, Department of Economics, City University London.
    6. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," Journal of Econometrics, Elsevier, vol. 193(2), pages 367-389.
    7. Ahmed Ghezal & Maddalena Cavicchioli & Imane Zemmouri, 2024. "On the existence of stationary threshold bilinear processes," Statistical Papers, Springer, vol. 65(6), pages 3739-3767, August.
    8. Kristensen Dennis & Rahbek Anders, 2009. "Asymptotics of the QMLE for Non-Linear ARCH Models," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-38, April.
    9. Bibi, Abdelouahab & Lescheb, Ines, 2012. "On general periodic time-varying bilinear processes," Economics Letters, Elsevier, vol. 114(3), pages 353-357.
    10. Iqbal Owadally, 2014. "Tail risk in pension funds: an analysis using ARCH models and bilinear processes," Review of Quantitative Finance and Accounting, Springer, vol. 43(2), pages 301-331, August.
    11. Predrag M. Popović & Hassan S. Bakouch, 2020. "A bivariate integer-valued bilinear autoregressive model with random coefficients," Statistical Papers, Springer, vol. 61(5), pages 1819-1840, October.
    12. Andreou, Elena, 2016. "On the use of high frequency measures of volatility in MIDAS regressions," CEPR Discussion Papers 11307, C.E.P.R. Discussion Papers.
    13. 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.
    14. Shiqing Ling & Liang Peng & Fukang Zhu, 2015. "Inference For A Special Bilinear Time-Series Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(1), pages 61-66, January.
    15. Bibi, Abdelouahab & Ghezal, Ahmed, 2015. "Consistency of quasi-maximum likelihood estimator for Markov-switching bilinear time series models," Statistics & Probability Letters, Elsevier, vol. 100(C), pages 192-202.

  24. Kristensen Dennis & Rahbek Anders, 2009. "Asymptotics of the QMLE for Non-Linear ARCH Models," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-38, April.

    Cited by:

    1. Peter Reinhard Hansen & Zhuo Huang, 2012. "Exponential GARCH Modeling with Realized Measures of Volatility," CREATES Research Papers 2012-44, Department of Economics and Business Economics, Aarhus University.
    2. Sucarrat, Genaro & Grønneberg, Steffen & Escribano, Alvaro, 2016. "Estimation and inference in univariate and multivariate log-GARCH-X models when the conditional density is unknown," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 582-594.
    3. Kurt Brannas & Albina Soultanaeva, 2011. "Influence of news from Moscow and New York on returns and risks of Baltic States’ stock markets," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 11(1), pages 109-124, July.
    4. Meitz, Mika & Saikkonen, Pentti, 2011. "Parameter Estimation In Nonlinear Ar–Garch Models," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1236-1278, December.
    5. Kristensen, Dennis & Rahbek, Anders, 2010. "Likelihood-based inference for cointegration with nonlinear error-correction," Journal of Econometrics, Elsevier, vol. 158(1), pages 78-94, September.
    6. Francq, Christian & Wintenberger, Olivier & Zakoïan, Jean-Michel, 2013. "GARCH models without positivity constraints: Exponential or log GARCH?," Journal of Econometrics, Elsevier, vol. 177(1), pages 34-46.

  25. Kristensen, Dennis, 2008. "Estimation of partial differential equations with applications in finance," Journal of Econometrics, Elsevier, vol. 144(2), pages 392-408, June.
    See citations under working paper version above.
  26. Richard Blundell & Xiaohong Chen & Dennis Kristensen, 2007. "Semi-Nonparametric IV Estimation of Shape-Invariant Engel Curves," Econometrica, Econometric Society, vol. 75(6), pages 1613-1669, November.

    Cited by:

    1. Denis Chetverikov & Daniel Wilhelm, 2017. "Nonparametric instrumental variable estimation under monotonicity," CeMMAP working papers 14/17, Institute for Fiscal Studies.
    2. Sam Cosaert & Thomas Demuynck, 2018. "Nonparametric welfare and demand analysis with unobserved individual heterogeneity," ULB Institutional Repository 2013/251988, ULB -- Universite Libre de Bruxelles.
    3. Joel L. Horowitz & Sokbae (Simon) Lee, 2010. "Uniform confidence bands for functions estimated nonparametrically with instrumental variables," CeMMAP working papers CWP19/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Timofeeva, Anastasiia, 2015. "On endogeneity of consumer expenditures in the estimation of households demand system," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 37(1), pages 87-106.
    5. Xiaohong Chen & Markus Reiss, 2007. "On Rate Optimality for Ill-posed Inverse Problems in Econometrics," Cowles Foundation Discussion Papers 1626, Cowles Foundation for Research in Economics, Yale University.
    6. Victor Chernozhukov & Ivan Fernandez-Val & Stefan Hoderlein & Hajo Holzmann & Whitney K. Newey, 2013. "Nonparametric identification in panels using quantiles," CeMMAP working papers 66/13, Institute for Fiscal Studies.
    7. Giuseppe De Luca & Franco Peracchi, 2010. "Estimating Engel curves under unit and item nonresponse," EIEF Working Papers Series 1004, Einaudi Institute for Economics and Finance (EIEF), revised Nov 2010.
    8. Babii, Andrii, 2020. "Honest Confidence Sets In Nonparametric Iv Regression And Other Ill-Posed Models," Econometric Theory, Cambridge University Press, vol. 36(4), pages 658-706, August.
    9. Syed Abul Hasan & Pallab Mozumder, 2017. "Income and energy use in Bangladesh: A household level analysis," Crawford School Research Papers 1701, Crawford School of Public Policy, The Australian National University.
    10. Muller, Christophe, 2018. "Heterogeneity and nonconstant effect in two-stage quantile regression," Econometrics and Statistics, Elsevier, vol. 8(C), pages 3-12.
    11. Jumrani, Jaya, 2023. "How responsive are nutrients in India? Some recent evidence," Food Policy, Elsevier, vol. 114(C).
    12. Dennis Kristensen, 2009. "Semiparametric modelling and estimation (in Russian)," Quantile, Quantile, issue 7, pages 53-83, September.
    13. Laurent Davezies & Thomas Le Barbanchon, 2014. "Regression Discontinuity Design with Continuous Measurement Error in the Running Variable," Working Papers 2014-27, Center for Research in Economics and Statistics.
    14. Tadao Hoshino, 2024. "Functional Spatial Autoregressive Models," Papers 2402.14763, arXiv.org, revised Oct 2024.
    15. 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.
    16. Olivier Bargain & Guy Lacroix & Luca Tiberti, 2021. "Intrahousehold Resource Allocation and Individual Poverty: Assessing Collective Model Predictions against Direct Evidence on Sharing," Working Papers hal-03432676, HAL.
    17. Christoph Breunig, 2019. "Goodness-of-Fit Tests based on Series Estimators in Nonparametric Instrumental Regression," Papers 1909.10133, arXiv.org.
    18. 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.
    19. Chen, Qihui, 2021. "Robust and optimal estimation for partially linear instrumental variables models with partial identification," Journal of Econometrics, Elsevier, vol. 221(2), pages 368-380.
    20. Shoya Ishimaru, 2021. "Empirical Decomposition of the IV-OLS Gap with Heterogeneous and Nonlinear Effects," Papers 2101.04346, arXiv.org, revised Jun 2022.
    21. FLORENS, Jean-Pierre & JOHANNES, Jan & VAN BELLEGEM, Sébastien, 2007. "Identification and estimation by penalization in nonparametric instrumental regression," LIDAM Discussion Papers CORE 2007085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    22. 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).
    23. Andrii Babii & Jean-Pierre Florens, 2017. "Are Unobservables Separable?," Papers 1705.01654, arXiv.org, revised Mar 2021.
    24. Gagliardini, Patrick & Scaillet, Olivier, 2012. "Tikhonov regularization for nonparametric instrumental variable estimators," Journal of Econometrics, Elsevier, vol. 167(1), pages 61-75.
    25. 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.
    26. Thomas A. Severini & Gautam Tripathi, 2007. "Efficiency Bounds for Estimating Linear Functionals of Nonparametric Regression Models with Endogenous Regressors," Working papers 2007-18, University of Connecticut, Department of Economics.
    27. Andrew Chesher & Adam M. Rosen, 2021. "Counterfactual Worlds," Annals of Economics and Statistics, GENES, issue 142, pages 311-335.
    28. Juan Carlos Escanciano & Wei Li, 2018. "Optimal Linear Instrumental Variables Approximations," Papers 1805.03275, arXiv.org, revised Feb 2020.
    29. Antonio Merlo & Áureo de Paula, 2015. "Identification and estimation of preference distributions when voters are ideological," CeMMAP working papers 50/15, Institute for Fiscal Studies.
    30. 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.
    31. Sokullu, Senay, 2023. "More Is Better, Or Not? An Empirical Analysis of Buyer Preferences for Variety on the E-Market," Journal of Economic Behavior & Organization, Elsevier, vol. 209(C), pages 450-470.
    32. Kim Kyoo il & Petrin Amil, 2022. "A Generalized Non-Parametric Instrumental Variable-Control Function Approach to Estimation in Nonlinear Settings," Journal of Econometric Methods, De Gruyter, vol. 11(1), pages 91-125, January.
    33. Xavier IRZ & Mario MAZZOCCHI & Vincent RÉQUILLART & Louis-Georges SOLER, 2015. "Research in Food Economics: past trends and new challenges," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement, INRA Department of Economics, vol. 96(1), pages 187-237.
    34. 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.
    35. Arnab Bhattacharjee & Eduardo Castro & João Marques, 2012. "Spatial Interactions in Hedonic Pricing Models: The Urban Housing Market of Aveiro, Portugal," Spatial Economic Analysis, Taylor & Francis Journals, vol. 7(1), pages 133-167, March.
    36. Clark, Andrew E & Lepinteur, Anthony, 2021. "Pandemic Policy and Life Satisfaction in Europe," CEPREMAP Working Papers (Docweb) 2108, CEPREMAP.
    37. Ramírez–Hassan, Andrés & López-Vera, Alejandro, 2024. "Welfare implications of a tax on electricity: A semi-parametric specification of the incomplete EASI demand system," Energy Economics, Elsevier, vol. 131(C).
    38. Xiaohong Chen & Timothy M. Christensen, 2015. "Optimal sup-norm rates, adaptivity and inference in nonparametric instrumental variables estimation," CeMMAP working papers 32/15, Institute for Fiscal Studies.
    39. Andr'es Ram'irez-Hassan & Alejandro L'opez-Vera, 2021. "Semi-parametric estimation of the EASI model: Welfare implications of taxes identifying clusters due to unobserved preference heterogeneity," Papers 2109.07646, arXiv.org.
    40. Yingyao Hu & Ji-Liang Shiu, 2011. "Nonparametric identification using instrumental variables: sufficient conditions for completeness," CeMMAP working papers CWP25/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    41. Stefan Hoderlein & Liangjun Su & Halbert White & Thomas Tao Yang, 2015. "Testing for Monotonicity in Unobservables under Unconfoundedness," Boston College Working Papers in Economics 899, Boston College Department of Economics.
    42. Florens, Jean-Pierre & Simoni, Anna, 2016. "Regularizing Priors For Linear Inverse Problems," Econometric Theory, Cambridge University Press, vol. 32(1), pages 71-121, February.
    43. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2018. "Nonparametric estimation in case of endogenous selection," Journal of Econometrics, Elsevier, vol. 202(2), pages 268-285.
    44. Vadym Lepetyuk & Christian A. Stoltenberg, 2013. "Reconciling Consumption Inequality with Income Inequality," Tinbergen Institute Discussion Papers 13-124/VI, Tinbergen Institute.
    45. Lechene, Valérie & Pendakur, Krishna & Wolf, Alexander, 2021. "OLS Estimation of the Intra-Household Distribution of Expenditure," CEPR Discussion Papers 15955, C.E.P.R. Discussion Papers.
    46. Victor Chernozhukov & Whitney Newey & Rahul Singh & Vasilis Syrgkanis, 2020. "Adversarial Estimation of Riesz Representers," Papers 2101.00009, arXiv.org, revised Apr 2024.
    47. Dharmasena, Senarath & Capps, Oral, Jr., 2014. "U.S. Demand for Wellness and Functional Beverages and Implications on Nutritional Intake: An Application of EASI Demand System Capturing Diverse Preference Heterogeniety," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169811, Agricultural and Applied Economics Association.
    48. Frédérique Fève & Jean-Pierre Florens, 2010. "The practice of non-parametric estimation by solving inverse problems: the example of transformation models," Econometrics Journal, Royal Economic Society, vol. 13(3), pages 1-27, October.
    49. Jad Beyhum & Elia Lapenta & Pascal Lavergne, 2023. "One-step smoothing splines instrumental regression," Papers 2307.14867, arXiv.org, revised Apr 2024.
    50. Victor Chernozhukov & Ivan Fernandez-Val & Amanda Kowalski, 2011. "Quantile Regression with Censoring and Endogeneity," Cowles Foundation Discussion Papers 1797, Cowles Foundation for Research in Economics, Yale University.
    51. Oulton, Nicholas, 2009. "How to measure living standards and productivity," LSE Research Online Documents on Economics 28678, London School of Economics and Political Science, LSE Library.
    52. 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.
    53. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers 34/15, Institute for Fiscal Studies.
    54. Santos, Andres, 2011. "Instrumental variable methods for recovering continuous linear functionals," Journal of Econometrics, Elsevier, vol. 161(2), pages 129-146, April.
    55. Rodrigo Adao & Costas Arkolakis & Sharat Ganapati, 2020. "Aggregate Implications of Firm Heterogeneity: A Nonparametric Analysis of Monopolistic Competition Trade Models," Cowles Foundation Discussion Papers 2265, Cowles Foundation for Research in Economics, Yale University.
    56. Breunig, Christoph & Haan, Peter, 2021. "Nonparametric regression with selectively missing covariates," Journal of Econometrics, Elsevier, vol. 223(1), pages 28-52.
    57. Feng Yao & Junsen Zhang, 2013. "Efficient Kernel-Based Semiparametric IV Estimation with an Application to Resolving a Puzzle on the Estimates of the Return to Schooling," Working Papers 13-01, Department of Economics, West Virginia University.
    58. Ivan A. Canay & Andres Santos & Azeem M. Shaikh, 2012. "On the testability of identification in some nonparametric models with endogeneity," CeMMAP working papers CWP18/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    59. Li, Lianyou & Song, Ze & Ma, Chao, 2015. "Engel curves and price elasticity in urban Chinese Households," Economic Modelling, Elsevier, vol. 44(C), pages 236-242.
    60. Nishanth Dikkala & Greg Lewis & Lester Mackey & Vasilis Syrgkanis, 2020. "Minimax Estimation of Conditional Moment Models," Papers 2006.07201, arXiv.org.
    61. Florens, Jean-Pierre & Simoni, Anna, 2012. "Nonparametric estimation of an instrumental regression: A quasi-Bayesian approach based on regularized posterior," Journal of Econometrics, Elsevier, vol. 170(2), pages 458-475.
    62. Denis Chetverikov & Daniel Wilhelm, 2017. "Nonparametric Instrumental Variable Estimation Under Monotonicity," Econometrica, Econometric Society, vol. 85, pages 1303-1320, July.
    63. Di Xiang & Lue Zhan & Massimo Bordignon, 2018. "A Reconsideration of the Sugar Sweetened Beverage Tax in a Household Production Model," CESifo Working Paper Series 7087, CESifo.
    64. Ai, Chunrong & Chen, Xiaohong, 2012. "The semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions," Journal of Econometrics, Elsevier, vol. 170(2), pages 442-457.
    65. Breunig, Christoph & Mammen, Enno & Simoni, Anna, 2020. "Ill-posed estimation in high-dimensional models with instrumental variables," Journal of Econometrics, Elsevier, vol. 219(1), pages 171-200.
    66. Christoph Breunig & Xiaohong Chen, 2020. "Adaptive, Rate-Optimal Hypothesis Testing in Nonparametric IV Models," Cowles Foundation Discussion Papers 2238R, Cowles Foundation for Research in Economics, Yale University, revised Dec 2021.
    67. JOHANNES, Jan & VAN BELLEGEM, Sébastien & VANHEMS, Anne, 2011. "Convergence rates for ill-posed inverse problems with an unknown operator," LIDAM Reprints CORE 2330, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    68. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    69. Stefan Hoderlein, 2009. "How Many Consumers are Rational?," Boston College Working Papers in Economics 748, Boston College Department of Economics.
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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.
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    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.
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    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, September.
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    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.

  28. Kristensen, Dennis & Rahbek, Anders, 2005. "ASYMPTOTICS OF THE QMLE FOR A CLASS OF ARCH(q) MODELS," Econometric Theory, Cambridge University Press, vol. 21(5), pages 946-961, October.

    Cited by:

    1. Giuseppe Cavaliere & Heino Bohn Nielsen & Anders Rahbek, 2016. "On the Consistency of Bootstrap Testing for a Parameter on the Boundary of the Parameter Space," Quaderni di Dipartimento 6, Department of Statistics, University of Bologna.
    2. Heejoon Han & Dennis Kristensen, 2014. "Asymptotic Theory for the QMLE in GARCH-X Models With Stationary and Nonstationary Covariates," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 416-429, July.
    3. Iglesias, Emma M., 2006. "Higher-order asymptotic properties of QML in [beta]-ARCH and [mu]-ARCH models," Economics Letters, Elsevier, vol. 93(2), pages 261-266, November.
    4. Giuseppe Cavaliere & Rasmus Søndergaard Pedersen & Anders Rahbek, 2018. "The Fixed Volatility Bootstrap for a Class of Arch(q) Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 39(6), pages 920-941, November.
    5. Peter Reinhard Hansen & Zhuo Huang, 2012. "Exponential GARCH Modeling with Realized Measures of Volatility," CREATES Research Papers 2012-44, Department of Economics and Business Economics, Aarhus University.
    6. 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.
    7. Kristensen, Dennis & Shin, Yongseok, 2012. "Estimation of dynamic models with nonparametric simulated maximum likelihood," Journal of Econometrics, Elsevier, vol. 167(1), pages 76-94.
    8. Hallin, Marc & La Vecchia, Davide, 2017. "R-estimation in semiparametric dynamic location-scale models," Journal of Econometrics, Elsevier, vol. 196(2), pages 233-247.
    9. Meitz, Mika & Saikkonen, Pentti, 2011. "Parameter Estimation In Nonlinear Ar–Garch Models," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1236-1278, December.
    10. Giuseppe Cavaliere & Anders Rahbek & A.M.Robert Taylor, 2009. "Co-integration Rank Testing under Conditional Heteroskedasticity," CREATES Research Papers 2009-22, Department of Economics and Business Economics, Aarhus University.
    11. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers CWP45/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Hafner, Christian M. & Preminger, Arie, 2009. "On asymptotic theory for multivariate GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2044-2054, October.
    13. Christian M. HAFNER & Arie PREMINGER, 2015. "An ARCH Model Without Intercept," LIDAM Reprints CORE 2770, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Kristensen, Dennis & Rahbek, Anders, 2010. "Likelihood-based inference for cointegration with nonlinear error-correction," Journal of Econometrics, Elsevier, vol. 158(1), pages 78-94, September.
    15. Arianna Agosto & Giuseppe Cavaliere & Dennis Kristensen & Anders Rahbek, 2015. "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)," CREATES Research Papers 2015-11, Department of Economics and Business Economics, Aarhus University.
    16. 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.).
    17. 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.
    18. Kristensen Dennis & Rahbek Anders, 2009. "Asymptotics of the QMLE for Non-Linear ARCH Models," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-38, April.
    19. Stanislav Anatolyev, 2006. "Dynamic modeling under linear-exponential loss," Working Papers w0092, New Economic School (NES).
    20. 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.
    21. Péter Elek & László Márkus, 2008. "A light‐tailed conditionally heteroscedastic model with applications to river flows," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 14-36, January.
    22. 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.).
    23. Mengya Liu & Qi Li & Fukang Zhu, 2020. "Self-excited hysteretic negative binomial autoregression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(3), pages 385-415, September.
    24. 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.
    25. Giuseppe Cavaliere & Anders Rahbek & A. M. Robert Taylor, 2009. "Co-integration rank tests under conditional heteroskedasticity," Discussion Papers 09/02, University of Nottingham, Granger Centre for Time Series Econometrics.
    26. Pedersen, Rasmus Søndergaard & Rahbek, Anders, 2016. "Nonstationary GARCH with t-distributed innovations," Economics Letters, Elsevier, vol. 138(C), pages 19-21.

  29. 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.

  30. 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.

    Cited by:

    1. Peter C. B. Phillips & Jun Yu, 2005. "Comments on “A selective overview of nonparametric methods in financial econometricsâ€Â," Finance Working Papers 22469, East Asian Bureau of Economic Research.
    2. Yu, Jun, 2014. "Econometric Analysis Of Continuous Time Models: A Survey Of Peter Phillips’S Work And Some New Results," Econometric Theory, Cambridge University Press, vol. 30(4), pages 737-774, August.
    3. Olivier Feron & Pierre Gruet, 2020. "Estimation of the number of factors in a multi-factorial Heath-Jarrow-Morton model in electricity markets," Working Papers hal-02880824, HAL.
    4. Jun Yu, 2009. "Econometric Analysis of Continuous Time Models : A Survey of Peter Phillips’ Work and Some New Results," Microeconomics Working Papers 23046, East Asian Bureau of Economic Research.
    5. Renò, Roberto, 2008. "Nonparametric Estimation Of The Diffusion Coefficient Of Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 24(5), pages 1174-1206, October.
    6. Kristensen, Dennis, 2008. "Estimation of partial differential equations with applications in finance," Journal of Econometrics, Elsevier, vol. 144(2), pages 392-408, June.
    7. Valerii Maltsev & Michael Pokojovy, 2021. "Applying Heath-Jarrow-Morton Model to Forecasting the US Treasury Daily Yield Curve Rates," Mathematics, MDPI, vol. 9(2), pages 1-25, January.
    8. Xu, Ke-Li, 2010. "Reweighted Functional Estimation Of Diffusion Models," Econometric Theory, Cambridge University Press, vol. 26(2), pages 541-563, April.
    9. Laurini, Márcio Poletti & Mauad, Roberto Baltieri, 2012. "Non-Parametric Pricing of Interest Rates Options," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 32(2), April.
    10. Christensen, Bent Jesper & van der Wel, Michel, 2019. "An asset pricing approach to testing general term structure models," Journal of Financial Economics, Elsevier, vol. 134(1), pages 165-191.
    11. Peter C. B. Phillips & Jun Yu, 2005. "Comments on “A Selective Overview of Nonparametric Methods in Financial Econometrics” by Jianqing Fan," Working Papers 08-2005, Singapore Management University, School of Economics.

  31. 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).

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