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Jinyong Hahn

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.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. Hahn, Jinyong & Todd, Petra & Van der Klaauw, Wilbert, 2001. "Identification and Estimation of Treatment Effects with a Regression-Discontinuity Design," Econometrica, Econometric Society, vol. 69(1), pages 201-209, January.

    Mentioned in:

    1. Sharp Regression Discontinuity Example and Limitations
      by Francis Smart in Econometrics by Simulation on 2012-08-22 19:00:00

Working papers

  1. Denis Chetverikov & Jinyong Hahn & Zhipeng Liao & Andres Santos, 2023. "Standard errors when a regressor is randomly assigned," Papers 2303.10306, arXiv.org.

    Cited by:

    1. Johannes W. Ligtenberg, 2023. "Inference in IV models with clustered dependence, many instruments and weak identification," Papers 2306.08559, arXiv.org, revised Mar 2024.

  2. Jinyong Hahn & Jerry Hausman & Josh Lustig, 2017. "Specification test on mixed logit models," CeMMAP working papers 58/17, Institute for Fiscal Studies.

    Cited by:

    1. Ji, Pengfei & Wei, Lei, 2023. "Hedging with derivatives to increase firm value," Finance Research Letters, Elsevier, vol. 55(PB).

  3. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.

    Cited by:

    1. Younes Ben Zaied & Béchir Ben Lahouel, 2021. "Does environmental CSR performance matter for corporate financial performance? Evidence from panel quantile regression," Economics Bulletin, AccessEcon, vol. 41(3), pages 938-951.
    2. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.
    3. Patrick Kline & Raffaele Saggio & Mikkel Sølvsten, 2020. "Leave‐Out Estimation of Variance Components," Econometrica, Econometric Society, vol. 88(5), pages 1859-1898, September.
    4. Xiao, Zhijie & Xu, Lan, 2019. "What do mean impacts miss? Distributional effects of corporate diversification," Journal of Econometrics, Elsevier, vol. 213(1), pages 92-120.
    5. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
    6. Lethiwe Nzama & Thanda Sithole & Sezer Bozkus Kahyaoglu, 2022. "The Impact of Government Effectiveness on Trade and Financial Openness: The Generalized Quantile Panel Regression Approach," JRFM, MDPI, vol. 16(1), pages 1-20, December.
    7. Antonio F. Galvao & Jiaying Gu & Stanislav Volgushev, 2018. "On the Unbiased Asymptotic Normality of Quantile Regression with Fixed Effects," Papers 1807.11863, arXiv.org, revised Feb 2020.
    8. Belloni, Alexandre & Chen, Mingli & Madrid Padilla, Oscar Hernan & Wang, Zixuan (Kevin), 2019. "High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing," The Warwick Economics Research Paper Series (TWERPS) 1230, University of Warwick, Department of Economics.
    9. Jennifer Betz & Maximilian Nagl & Daniel Rösch, 2022. "Credit line exposure at default modelling using Bayesian mixed effect quantile regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2035-2072, October.
    10. Bresson, Georges & Lacroix, Guy & Arshad Rahman, Mohammad, 2020. "Bayesian Panel Quantile Regression for Binary Outcomes with Correlated Random Effects: An Application on Crime Recidivism in Canada," IZA Discussion Papers 12928, Institute of Labor Economics (IZA).
    11. BELAÏD, Fateh & Elsayed, Ahmed H. & Omri, Anis, 2021. "Key drivers of renewable energy deployment in the MENA Region: Empirical evidence using panel quantile regression," Structural Change and Economic Dynamics, Elsevier, vol. 57(C), pages 225-238.
    12. Liang Chen & Yulong Huo, 2019. "A Simple Estimator for Quantile Panel Data Models Using Smoothed Quantile Regressions," Papers 1911.04729, arXiv.org.
    13. Jungmo Yoon & Antonio F. Galvao, 2020. "Cluster robust covariance matrix estimation in panel quantile regression with individual fixed effects," Quantitative Economics, Econometric Society, vol. 11(2), pages 579-608, May.
    14. Ming Li, 2021. "A Time-Varying Endogenous Random Coefficient Model with an Application to Production Functions," Papers 2110.00982, arXiv.org.
    15. Liang Chen, 2019. "Nonparametric Quantile Regressions for Panel Data Models with Large T," Papers 1911.01824, arXiv.org, revised Sep 2020.
    16. Fateh Belaid & Ahmed H. Elsayed, 2019. "What drives renewable energy production in MENA Region? Investigating the roles of political stability, governance and financial sector," Working Papers 1322, Economic Research Forum, revised 21 Aug 2019.
    17. Panagiotidis, Theodore & Printzis, Panagiotis, 2021. "Investment and uncertainty: Are large firms different from small ones?," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 302-317.
    18. Yonggang Ji & Haifang Shi, 2020. "Bayesian variable selection in linear quantile mixed models for longitudinal data with application to macular degeneration," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-34, October.
    19. Jaepil Han, 2020. "Identifying the effects of technology transfer policy using a quantile regression: the case of South Korea," The Journal of Technology Transfer, Springer, vol. 45(6), pages 1690-1717, December.
    20. Sungwon Lee, 2020. "Nonparametric Identification and Estimation of Panel Quantile Models with Sample Selection," Working Papers 2012, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    21. Baruník, Jozef & Čech, František, 2021. "Measurement of common risks in tails: A panel quantile regression model for financial returns," Journal of Financial Markets, Elsevier, vol. 52(C).
    22. Asfaw, Solomon & Pallante, Giacomo & Palma, Alessandro, 2020. "Distributional impacts of soil erosion on agricultural productivity and welfare in Malawi," Ecological Economics, Elsevier, vol. 177(C).

  4. Ruoyao Shi & Jinyong Hahn, 2016. "Synthetic Control and Inference," Working Papers 201802, University of California at Riverside, Department of Economics, revised Nov 2017.

    Cited by:

    1. Bruno Ferman & Cristine Pinto & Vitor Possebom, 2020. "Cherry Picking with Synthetic Controls," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(2), pages 510-532, March.
    2. Yi‐Ting Chen, 2020. "A distributional synthetic control method for policy evaluation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 505-525, August.
    3. Manuel Funke & Moritz Schularick & Christoph Trebesch, 2023. "Populist Leaders and the Economy," American Economic Review, American Economic Association, vol. 113(12), pages 3249-3288, December.
    4. Maximiliano Marzetti & Rok Spruk, 2023. "Long-Term Economic Effects of Populist Legal Reforms: Evidence from Argentina," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 65(1), pages 60-95, March.
    5. Born, Benjamin & Müller, Gernot & Schularick, Moritz & SedlÃ¡Ä ek, Petr, 2017. "The Costs of Economic Nationalism: Evidence from the Brexit Experiment," CEPR Discussion Papers 12454, C.E.P.R. Discussion Papers.
    6. Jason Poulos & Shuxi Zeng, 2021. "RNN‐based counterfactual prediction, with an application to homestead policy and public schooling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 1124-1139, August.
    7. James Gaughan & Nils Gutacker & Katja Grasic & Noemi Kreif & Luigi Siciliani & Andrew Street, 2018. "Paying for Efficiency: Incentivising same-day discharges in the English NHS," Working Papers 157cherp, Centre for Health Economics, University of York.
    8. Dmitry Arkhangelsky & Susan Athey & David A. Hirshberg & Guido W. Imbens & Stefan Wager, 2019. "Synthetic Difference In Differences," NBER Working Papers 25532, National Bureau of Economic Research, Inc.
    9. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    10. Ferman, Bruno, 2017. "Matching Estimators with Few Treated and Many Control Observations," MPRA Paper 78940, University Library of Munich, Germany.
    11. Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," SciencePo Working papers Main hal-03455978, HAL.
    12. Cordeiro Guerra, Susana & Lastra-Anadón, Carlos Xabel, 2019. "The quality-access tradeoff in decentralizing public services: Evidence from education in the OECD and Spain," Journal of Comparative Economics, Elsevier, vol. 47(2), pages 295-316.
    13. Fredriksen, Kaja & Runst, Petrik, 2018. "Are estimates of the "natural experiment" in the German crafts sector causal?," ifh Working Papers 16/2018, Volkswirtschaftliches Institut für Mittelstand und Handwerk an der Universität Göttingen (ifh).
    14. Eli Ben-Michael & Avi Feller & Jesse Rothstein, 2018. "The Augmented Synthetic Control Method," Papers 1811.04170, arXiv.org, revised Jul 2020.
    15. Denis Fougère & Nicolas Jacquemet, 2019. "Causal Inference and Impact Evaluation," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 510-511-5, pages 181-200.
    16. David Gilchrist & Thomas Emery & Nuno Garoupa & Rok Spruk, 2023. "Synthetic Control Method: A tool for comparative case studies in economic history," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 409-445, April.
    17. Ahmed Hanifi, S.M. Manzoor & Menon, Nidhiya & Quisumbing, Agnes, 2022. "The impact of climate change on children's nutritional status in coastal Bangladesh," Social Science & Medicine, Elsevier, vol. 294(C).
    18. Jianfei Cao & Connor Dowd, 2019. "Estimation and Inference for Synthetic Control Methods with Spillover Effects," Papers 1902.07343, arXiv.org, revised Nov 2019.
    19. Chung, Bobby W., 2022. "The costs and potential benefits of occupational licensing: A case of real estate license reform," Labour Economics, Elsevier, vol. 76(C).
    20. Benjamin Born & Gernot J. Müller & Moritz Schularick & Petr Sedláček, 2021. "The macroeconomic impact of Trump," Policy Studies, Taylor & Francis Journals, vol. 42(5-6), pages 580-591, November.
    21. Giovanni Peri & Derek Rury & Justin C. Wiltshire, 2020. "The Economic Impact of Migrants from Hurricane Maria," NBER Working Papers 27718, National Bureau of Economic Research, Inc.
    22. Christian Beer & Janine Maniora & Christiane Pott, 2023. "COVID-19 pandemic and capital markets: the role of government responses," Journal of Business Economics, Springer, vol. 93(1), pages 11-57, January.
    23. Nikolay Doudchenko & Guido W. Imbens, 2016. "Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis," NBER Working Papers 22791, National Bureau of Economic Research, Inc.
    24. Bruno Ferman & Gaute Torsvik & Kjell Vaage, 2023. "Skipping the doctor: evidence from a case with extended self-certification of paid sick leave," Journal of Population Economics, Springer;European Society for Population Economics, vol. 36(2), pages 935-971, April.
    25. Chen, Qiang & Yan, Guanpeng, 2023. "A mixed placebo test for synthetic control method," Economics Letters, Elsevier, vol. 224(C).
    26. Ferman, Bruno & Pinto, Cristine, 2017. "Placebo Tests for Synthetic Controls," MPRA Paper 78079, University Library of Munich, Germany.
    27. Guido W. Imbens & Davide Viviano, 2023. "Identification and Inference for Synthetic Controls with Confounding," Papers 2312.00955, arXiv.org.
    28. Wenyuan Hua & Zhihan Chen & Liangguo Luo, 2022. "The Effect of the Major-Grain-Producing-Areas Oriented Policy on Crop Production: Evidence from China," Land, MDPI, vol. 11(9), pages 1-28, August.
    29. Justin Wiltshire, 2021. "allsynth: Synthetic control bias-corrections utilities for Stata," 2021 Stata Conference 15, Stata Users Group.
    30. Samuel Verevis & Murat Üngör, 2021. "What has New Zealand gained from The FTA with China?: Two counterfactual analyses†," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(1), pages 20-50, February.
    31. Marina Dias & Demian Pouzo, 2021. "Inference for multi-valued heterogeneous treatment effects when the number of treated units is small," Papers 2105.10965, arXiv.org.
    32. Giulio Grossi & Marco Mariani & Alessandra Mattei & Patrizia Lattarulo & Ozge Oner, 2020. "Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach," Papers 2004.05027, arXiv.org, revised Nov 2023.

  5. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile regression with panel data," CeMMAP working papers 12/15, Institute for Fiscal Studies.

    Cited by:

    1. Jorge E. Galán, 2020. "The benefits are at the tail: uncovering the impact of macroprudential policy on growth-at-risk," Working Papers 2007, Banco de España.
    2. Pietro Santoleri, 2020. "Innovation and job creation in (high-growth) new firms," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 29(3), pages 731-756.
    3. Sandra Kendo & Josephine Tchakounte, 2022. "Impact of asset size on performance and outreach using panel quantile regression with non-additive fixed effects," Empirical Economics, Springer, vol. 62(1), pages 65-92, January.
    4. George S. Atsalakis & Elie Bouri & Fotios Pasiouras, 2021. "Natural disasters and economic growth: a quantile on quantile approach," Annals of Operations Research, Springer, vol. 306(1), pages 83-109, November.
    5. Callaway, Brantly & Li, Tong & Oka, Tatsushi, 2018. "Quantile treatment effects in difference in differences models under dependence restrictions and with only two time periods," Journal of Econometrics, Elsevier, vol. 206(2), pages 395-413.
    6. Frantisek Cech & Jozef Barunik, 2017. "Measurement of Common Risk Factors: A Panel Quantile Regression Model for Returns," Working Papers IES 2017/20, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Sep 2017.
    7. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154, arXiv.org, revised Jun 2020.
    8. Manuel Arellano & Stéphane Bonhomme, 2015. "Nonlinear panel data estimation via quantile regressions," CeMMAP working papers 40/15, Institute for Fiscal Studies.
    9. Kendo, Sandra & Tchakounte, Josephine, 2022. "The drivers of the financial integration of microfinance Institutions: Do financial development, agency costs and microfinance performance matter?," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 128-142.
    10. Yanay Farja & Avi Tillman & Ori Zax, 2022. "The Gender Gap: Looking at the Entire Distribution," Journal of Interdisciplinary Economics, , vol. 34(1), pages 51-68, January.
    11. Borsati, Mattia & Nocera, Silvio & Percoco, Marco, 2022. "Questioning the spatial association between the initial spread of COVID-19 and transit usage in Italy," Research in Transportation Economics, Elsevier, vol. 95(C).
    12. Klayme, Tania & Gokmenoglu, Korhan K. & Rustamov, Bezhan, 2023. "Economic policy uncertainty, COVID-19 and corporate investment: Evidence from the gold mining industry," Resources Policy, Elsevier, vol. 85(PA).
    13. Talan, Amogh & Rao, Amar & Sharma, Gagan Deep & Apostu, Simona-Andreea & Abbas, Shujaat, 2023. "Transition towards clean energy consumption in G7: Can financial sector, ICT and democracy help?," Resources Policy, Elsevier, vol. 82(C).
    14. Wei Feng & Yanrui Wu & Yue Fu, 2021. "Dialect Diversity and Foreign Direct Investment in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 29(2), pages 49-72, March.
    15. Yuya Sasaki & Takuya Ura, 2021. "Slow Movers in Panel Data," Papers 2110.12041, arXiv.org.

  6. Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn, 2014. "Asymptotic efficiency of semiparametric two-step GMM," CeMMAP working papers 28/14, Institute for Fiscal Studies.

    Cited by:

    1. Michael Jansson & Demian Pouzo, 2019. "Towards a general large sample theory for regularized estimators," CeMMAP working papers CWP63/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Xiaohong Chen & Andres Santos, 2015. "Overidentification in Regular Models," Cowles Foundation Discussion Papers 1999R, Cowles Foundation for Research in Economics, Yale University, revised Jun 2018.
    3. Sokbae Lee & Bernard Salani'e, 2020. "Treatment Effects with Targeting Instruments," Papers 2007.10432, arXiv.org, revised Nov 2023.
    4. Xiaohong Chen & Yin Jia Jeff Qiu, 2016. "Methods for Nonparametric and Semiparametric Regressions with Endogeneity: A Gentle Guide," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 259-290, October.
    5. Sung Jae Jun & Sokbae Lee, 2020. "Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions," Papers 2004.08318, arXiv.org, revised Oct 2023.
    6. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    7. Vanhems, Anne & Van Keilegom, Ingrid, 2013. "Semiparametric transformation model with endogeneity: a control function approach," LIDAM Discussion Papers ISBA 2013018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    9. Victor Aguirregabiria & Allan Collard-Wexler & Stephen P. Ryan, 2021. "Dynamic Games in Empirical Industrial Organization," Papers 2109.01725, arXiv.org, revised Sep 2021.
    10. 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.
    11. Sung Jae Jun & Sokbae (Simon) Lee, 2020. "Causal inference in case-control studies," CeMMAP working papers CWP19/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Sung Jae Jun & Sokbae (Simon) Lee, 2019. "Identifying the effect of persuasion," CeMMAP working papers CWP69/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Minji Bang & Wayne Gao & Andrew Postlewaite & Holger Sieg, 2021. "Using Monotonicity Restrictions to Identify Models with Partially Latent Covariates," NBER Working Papers 28436, National Bureau of Economic Research, Inc.
    14. Lee, Sungwon, 2023. "Efficient estimation of a triangular system of equations for quantile regression," Economics Letters, Elsevier, vol. 226(C).
    15. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    16. Karun Adusumilli & Dita Eckardt, 2019. "Temporal-Difference estimation of dynamic discrete choice models," Papers 1912.09509, arXiv.org, revised Dec 2022.
    17. Luis Alvarez & Ciro Biderman, 2023. "The learning effects of subsidies to bundled goods: a semiparametric approach," Papers 2311.01217, arXiv.org, revised Jan 2024.
    18. Haitian Xie, 2020. "Efficient and Robust Estimation of the Generalized LATE Model," Papers 2001.06746, arXiv.org, revised Feb 2022.
    19. Salanié, Bernard & Lee, Sokbae, 2020. "Filtered and Unfiltered Treatment Effects with Targeting Instruments," CEPR Discussion Papers 15092, C.E.P.R. Discussion Papers.
    20. Amandeep Singh & Ye Liu & Hema Yoganarasimhan, 2023. "Choice Models and Permutation Invariance: Demand Estimation in Differentiated Products Markets," Papers 2307.07090, arXiv.org, revised Feb 2024.
    21. Ruoyao Shi, 2022. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202211, University of California at Riverside, Department of Economics.
    22. Semenova, Vira, 2023. "Debiased machine learning of set-identified linear models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1725-1746.
    23. Yusuke Narita & Shota Yasui & Kohei Yata, 2018. "Efficient Counterfactual Learning from Bandit Feedback," Cowles Foundation Discussion Papers 2155, Cowles Foundation for Research in Economics, Yale University.
    24. Kai Quan Zhang & Hsing Hung Chen, 2017. "Environmental Performance and Financing Decisions Impact on Sustainable Financial Development of Chinese Environmental Protection Enterprises," Sustainability, MDPI, vol. 9(12), pages 1-14, December.
    25. Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
    26. Liqiong Chen & Antonio F. Galvao & Suyong Song, 2021. "Quantile Regression with Generated Regressors," Econometrics, MDPI, vol. 9(2), pages 1-35, April.

  7. Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn, 2011. "A practical asymptotic variance estimator for two-step semiparametric estimators," CeMMAP working papers CWP22/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Wu, Ximing & Sickles, Robin, 2018. "Semiparametric estimation under shape constraints," Econometrics and Statistics, Elsevier, vol. 6(C), pages 74-89.
    2. Maican, Florin & Orth, Matilda, 2008. "Productivity Dynamics and the Role of “Big-Box” Entrants in Retailing," Working Papers in Economics 328, University of Gothenburg, Department of Economics.
    3. Victor Aguirregabiria & Arvind Magesan, "undated". "Soultion and Estimation of Dynamic Discrete Choice Structural Models Using Euler Equations," Working Papers 2016-32, Department of Economics, University of Calgary, revised 24 May 2016.
    4. Sokbae Lee & Bernard Salani'e, 2020. "Treatment Effects with Targeting Instruments," Papers 2007.10432, arXiv.org, revised Nov 2023.
    5. Le-Yu Chen & Sokbae (Simon) Lee & Myung Jae Sung, 2014. "Maximum score estimation with nonparametrically generated regressors," CeMMAP working papers CWP27/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Aguirregabiria, Victor & Magesan, Arvind, 2013. "Euler Equations for the Estimation of Dynamic Discrete Choice Structural," MPRA Paper 46056, University Library of Munich, Germany.
    7. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," Papers 2402.05030, arXiv.org.
    8. Xiaohong Chen & Yin Jia Jeff Qiu, 2016. "Methods for Nonparametric and Semiparametric Regressions with Endogeneity: A Gentle Guide," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 259-290, October.
    9. Sung Jae Jun & Sokbae Lee, 2020. "Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions," Papers 2004.08318, arXiv.org, revised Oct 2023.
    10. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    11. Joachim Freyberger & Bradley J. Larsen, 2022. "Identification in ascending auctions, with an application to digital rights management," Quantitative Economics, Econometric Society, vol. 13(2), pages 505-543, May.
    12. Maican, Florin & Orth, Matilda, 2015. "A dynamic analysis of entry regulations and productivity in retail trade," International Journal of Industrial Organization, Elsevier, vol. 40(C), pages 67-80.
    13. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    14. Xiaohong Chen & Jinyong Hahn, 2012. "Asymptotic efficiency of semiparametric two-step GMM," CeMMAP working papers CWP31/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. 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.
    16. Christoph Engel, 2019. "Estimating Heterogeneous Reactions to Experimental Treatments," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2019_01, Max Planck Institute for Research on Collective Goods.
    17. Maican, Florin & Orth, Matilda, 2021. "Entry Regulations and Product Variety in Retail," Working Papers in Economics 802, University of Gothenburg, Department of Economics.
    18. Xiaohong Chen & Zhipeng Liao, 2015. "Sieve Semiparametric Two-Step GMM under Weak Dependence," Cowles Foundation Discussion Papers 2012, Cowles Foundation for Research in Economics, Yale University.
    19. Huse, Cristian & Lucinda, Claudio & Cardoso, Andre Ribeiro, 2020. "Consumer response to energy label policies: Evidence from the Brazilian energy label program," Energy Policy, Elsevier, vol. 138(C).
    20. Maican, Florin & Orth, Matilda, 2020. "Determinants of Economies of Scope in Retail," CEPR Discussion Papers 15084, C.E.P.R. Discussion Papers.
    21. Sung Jae Jun & Sokbae (Simon) Lee, 2020. "Causal inference in case-control studies," CeMMAP working papers CWP19/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    22. Przemysław Jeziorski, 2014. "Estimation of cost efficiencies from mergers: application to US radio," RAND Journal of Economics, RAND Corporation, vol. 45(4), pages 816-846, December.
    23. Abadir, Karim M. & Distaso, Walter & Žikeš, Filip, 2014. "Design-free estimation of variance matrices," Journal of Econometrics, Elsevier, vol. 181(2), pages 165-180.
    24. Maican, Florin & Orth, Matilda, 2018. "Inventory Behavior, Demand, and Productivity in Retail," CEPR Discussion Papers 13308, C.E.P.R. Discussion Papers.
    25. Minji Bang & Wayne Gao & Andrew Postlewaite & Holger Sieg, 2021. "Using Monotonicity Restrictions to Identify Models with Partially Latent Covariates," NBER Working Papers 28436, National Bureau of Economic Research, Inc.
    26. Maican, Florin G., 2012. "From Boom to Bust and Back Again: A dynamic analysis of IT services," Working Papers in Economics 543, University of Gothenburg, Department of Economics.
    27. Paolo Frumento & Matteo Bottai, 2017. "Parametric modeling of quantile regression coefficient functions with censored and truncated data," Biometrics, The International Biometric Society, vol. 73(4), pages 1179-1188, December.
    28. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    29. Le-Yu Chen & Sokbae (Simon) Lee & Myung Jae Sung, 2013. "Maximum score estimation of preference parameters for a binary choice model under uncertainty," CeMMAP working papers CWP14/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    30. Victor Aguirregabiria & Arvind Magesan, 2013. "Euler Equations for the Estimation of Dynamic Discrete Choice Structural Models," Working Papers tecipa-489, University of Toronto, Department of Economics.
    31. Victor Aguiar & Roberto Serrano, 2015. "Slutsky Matrix Norms and Revealed Preference Tests of Consumer Behaviour," Working Papers 2015-1, Brown University, Department of Economics.
    32. Hong, Han & Mahajan, Aprajit & Nekipelov, Denis, 2015. "Extremum estimation and numerical derivatives," Journal of Econometrics, Elsevier, vol. 188(1), pages 250-263.
    33. Ming Li, 2021. "A Time-Varying Endogenous Random Coefficient Model with an Application to Production Functions," Papers 2110.00982, arXiv.org.
    34. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
    35. Aristide Houndetoungan & Abdoul Haki Maoude, 2024. "Inference for Two-Stage Extremum Estimators," THEMA Working Papers 2024-01, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    36. Frumento, Paolo & Bottai, Matteo, 2017. "An estimating equation for censored and truncated quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 53-63.
    37. Salanié, Bernard & Lee, Sokbae, 2020. "Filtered and Unfiltered Treatment Effects with Targeting Instruments," CEPR Discussion Papers 15092, C.E.P.R. Discussion Papers.
    38. Serafin J. Grundl & Yu Zhu, 2015. "Identification and Estimation of Risk Aversion in First Price Auctions With Unobserved Auction Heterogeneity," Finance and Economics Discussion Series 2015-89, Board of Governors of the Federal Reserve System (U.S.).
    39. Armstrong, Timothy B. & Bertanha, Marinho & Hong, Han, 2014. "A fast resample method for parametric and semiparametric models," Journal of Econometrics, Elsevier, vol. 179(2), pages 128-133.
    40. Gupta, A, 2015. "Nonparametric specification testing via the trinity of tests," Economics Discussion Papers 23824, University of Essex, Department of Economics.
    41. Patrick Bajari & Victor Chernozhukov & Han Hong & Denis Nekipelov, 2015. "Identification and Efficient Semiparametric Estimation of a Dynamic Discrete Game," NBER Working Papers 21125, National Bureau of Economic Research, Inc.

  8. Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn, 2011. "Asymptotic Variance Estimator for Two-Step Semiparametric Estimators," Cowles Foundation Discussion Papers 1803, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Maican, Florin & Orth, Matilda, 2008. "Productivity Dynamics and the Role of “Big-Box” Entrants in Retailing," Working Papers in Economics 328, University of Gothenburg, Department of Economics.
    2. Maican, Florin & Orth, Matilda, 2015. "A dynamic analysis of entry regulations and productivity in retail trade," International Journal of Industrial Organization, Elsevier, vol. 40(C), pages 67-80.
    3. Hu, Yingyao & Huang, Guofang & Sasaki, Yuya, 2020. "Estimating production functions with robustness against errors in the proxy variables," Journal of Econometrics, Elsevier, vol. 215(2), pages 375-398.
    4. Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn, 2011. "A practical asymptotic variance estimator for two-step semiparametric estimators," CeMMAP working papers CWP22/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Armstrong, Timothy B. & Bertanha, Marinho & Hong, Han, 2014. "A fast resample method for parametric and semiparametric models," Journal of Econometrics, Elsevier, vol. 179(2), pages 128-133.
    6. Satimanon, Monthien & Lupi, Frank, 2010. "Comparison of Approaches to Estimating Demand for Payment for Environmental Services," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61288, Agricultural and Applied Economics Association.
    7. Patrick Bajari & Victor Chernozhukov & Han Hong & Denis Nekipelov, 2015. "Identification and Efficient Semiparametric Estimation of a Dynamic Discrete Game," NBER Working Papers 21125, National Bureau of Economic Research, Inc.

  9. Jinyong Hahn & Geert Ridder, 2010. "The asymptotic variance of semi-parametric estimators with generated regressors," CeMMAP working papers CWP23/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

    Cited by:

    1. Xiaohong Chen & Yin Jia Jeff Qiu, 2016. "Methods for Nonparametric and Semiparametric Regressions with Endogeneity: A Gentle Guide," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 259-290, October.
    2. Imbens, Guido W., 2014. "Matching Methods in Practice: Three Examples," IZA Discussion Papers 8049, Institute of Labor Economics (IZA).
    3. Enno Mammen & Christoph Rothe & Melanie Schienle, 2011. "Semiparametric Estimation with Generated Covariates," SFB 649 Discussion Papers SFB649DP2011-064, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    4. Victor Chernozhukov & Juan Carlos Escanciano & Hidehiko Ichimura & Whitney K. Newey & James M. Robins, 2022. "Locally Robust Semiparametric Estimation," Econometrica, Econometric Society, vol. 90(4), pages 1501-1535, July.
    5. Vanhems, Anne & Van Keilegom, Ingrid, 2013. "Semiparametric transformation model with endogeneity: a control function approach," LIDAM Discussion Papers ISBA 2013018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Li, XiaoLi & You, JinHong, 2012. "Error covariance matrix correction based approach to functional coefficient regression models with generated covariates," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 263-281.
    7. Ying-Ying Lee, 2015. "Efficient propensity score regression estimators of multi-valued treatment effects for the treated," Economics Series Working Papers 738, University of Oxford, Department of Economics.
    8. Juan Carlos Escanciano & Telmo P'erez-Izquierdo, 2023. "Automatic Locally Robust Estimation with Generated Regressors," Papers 2301.10643, arXiv.org, revised Nov 2023.
    9. 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.
    10. Huang, Liquan & Khalil, Umair & Yıldız, Neşe, 2019. "Identification and estimation of a triangular model with multiple endogenous variables and insufficiently many instrumental variables," Journal of Econometrics, Elsevier, vol. 208(2), pages 346-366.
    11. Hidehiko Ichimura & Whitney K. Newey, 2017. "The influence function of semiparametric estimators," CeMMAP working papers 06/17, Institute for Fiscal Studies.
    12. Simar, Leopold & Vanhems, Anne & Van Keilegom, Ingrid, 2013. "Unobserved heterogeneity and endogeneity in nonparametric frontier estimation," LIDAM Discussion Papers ISBA 2013054, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    13. Escanciano, Juan Carlos & Jacho-Chávez, David T. & Lewbel, Arthur, 2014. "Uniform convergence of weighted sums of non and semiparametric residuals for estimation and testing," Journal of Econometrics, Elsevier, vol. 178(P3), pages 426-443.
    14. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
    15. Ida Johnsson & Hyungsik Roger Moon, 2017. "Estimation of Peer Effects in Endogenous Social Networks: Control Function Approach," Papers 1709.10024, arXiv.org, revised Jul 2019.
    16. Rothe, Christoph, 2016. "The Value of Knowing the Propensity Score for Estimating Average Treatment Effects," IZA Discussion Papers 9989, Institute of Labor Economics (IZA).
    17. Julian Martinez-Iriarte & YiXiao Sun, 2022. "Identification and Estimation of Unconditional Policy Effects of an Endogenous Binary Treatment: an Unconditional MTE Approach," Working Papers 131, Red Nacional de Investigadores en Economía (RedNIE).
    18. Otsu, Taisuke & Taniguchi, Go, 2020. "Kolmogorov–Smirnov type test for generated variables," Economics Letters, Elsevier, vol. 195(C).
    19. Matsushita, Yukitoshi & Otsu, Taisuke, 2018. "Likelihood inference on semiparametric models: average derivative and treatment effect," LSE Research Online Documents on Economics 85870, London School of Economics and Political Science, LSE Library.
    20. Christis Katsouris, 2023. "Estimating Conditional Value-at-Risk with Nonstationary Quantile Predictive Regression Models," Papers 2311.08218, arXiv.org, revised Apr 2024.
    21. Jayeeta Bhattacharya, 2020. "Quantile regression with generated dependent variable and covariates," Papers 2012.13614, arXiv.org.
    22. Jinyong Hahn & John Ham & Geert Ridder & Shuyang Sheng, 2024. "Stratifying on Treatment Status," Papers 2404.04700, arXiv.org.
    23. Hahn, Jinyong & Ridder, Geert, 2017. "Instrumental variable estimation of nonlinear models with nonclassical measurement error using control variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 238-250.
    24. Elia Lapenta, 2022. "A Bootstrap Specification Test for Semiparametric Models with Generated Regressors," Papers 2212.11112, arXiv.org, revised Oct 2023.
    25. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    26. Matsushita, Yukitoshi & Otsu, Taisuke, 2020. "Likelihood inference on semiparametric models with generated regressors," LSE Research Online Documents on Economics 102696, London School of Economics and Political Science, LSE Library.
    27. Le-Yu Chen & Sokbae (Simon) Lee & Myung Jae Sung, 2013. "Maximum score estimation of preference parameters for a binary choice model under uncertainty," CeMMAP working papers CWP14/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    28. Cattaneo, Matias D & Jansson, Michael & Ma, Xinwei, 2019. "Two-Step Estimation and Inference with Possibly Many Included Covariates," University of California at San Diego, Economics Working Paper Series qt86c7x315, Department of Economics, UC San Diego.
    29. Hahn, Jinyong & Ridder, Geert, 2019. "Three-stage semi-parametric inference: Control variables and differentiability," Journal of Econometrics, Elsevier, vol. 211(1), pages 262-293.
    30. Julian Martinez-Iriarte & Yixiao Sun, 2020. "Identification and Estimation of Unconditional Policy Effects of an Endogenous Binary Treatment: An Unconditional MTE Approach," Papers 2010.15864, arXiv.org, revised Mar 2024.
    31. Ming Li, 2021. "A Time-Varying Endogenous Random Coefficient Model with an Application to Production Functions," Papers 2110.00982, arXiv.org.
    32. Michael Zimmert & Michael Lechner, 2019. "Nonparametric estimation of causal heterogeneity under high-dimensional confounding," Papers 1908.08779, arXiv.org.
    33. Yukitoshi Matsushita & Taisuke Otsu, 2018. "Likelihood Inference on Semiparametric Models: Average Derivative and Treatment Effect," The Japanese Economic Review, Springer, vol. 69(2), pages 133-155, June.
    34. Yukitoshi Matsushita & Taisuke Otsu, 2016. "Likelihood inference on semiparametric models with generated regressors," STICERD - Econometrics Paper Series 587, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    35. Zhang, Junfu & Zhao, Zhong, 2013. "Measuring the Income-Distance Tradeoff for Rural-Urban Migrants in China," IZA Discussion Papers 7160, Institute of Labor Economics (IZA).
    36. Otsu, Taisuke & Taniguchi, Go, 2020. "Kolmogorov-Smirnov type test for generated variables," LSE Research Online Documents on Economics 105571, London School of Economics and Political Science, LSE Library.
    37. Eric Auerbach, 2019. "Identification and Estimation of a Partially Linear Regression Model using Network Data," Papers 1903.09679, arXiv.org, revised Jun 2021.
    38. Lee, Ying-Ying, 2018. "Efficient propensity score regression estimators of multivalued treatment effects for the treated," Journal of Econometrics, Elsevier, vol. 204(2), pages 207-222.
    39. Martínez-Iriarte, Julian & Sun, Yixiao, 2021. "Identification and Estimation of Unconditional Policy Effects of an Endogenous Binary Treatment: an Unconditional MTE Approach," University of California at San Diego, Economics Working Paper Series qt2bc57830, Department of Economics, UC San Diego.
    40. Liqiong Chen & Antonio F. Galvao & Suyong Song, 2021. "Quantile Regression with Generated Regressors," Econometrics, MDPI, vol. 9(2), pages 1-35, April.
    41. Song, Kyungchul, 2014. "Semiparametric models with single-index nuisance parameters," Journal of Econometrics, Elsevier, vol. 178(P3), pages 471-483.
    42. Ying-Ying Lee, 2014. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Economics Series Working Papers 706, University of Oxford, Department of Economics.

  10. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney Newey, 2009. "Identification and Estimation of Marginal Effects in Nonlinear Panel Models," Boston University - Department of Economics - Working Papers Series wp2009-b, Boston University - Department of Economics.

    Cited by:

    1. Martin Browning & Jesus M. Carro, 2009. "Dynamic binary outcome models with maximal heterogeneity," Economics Series Working Papers 426, University of Oxford, Department of Economics.
    2. Andrei Markevich & Ekaterina Zhuravskaya, 2009. "Career Concerns in a Political Hierarchy: A Case of Regional Leaders in Soviet Russia," Working Papers w0040, Center for Economic and Financial Research (CEFIR).
    3. Ali Fakih, 2014. "Vacation Leave, Work Hours and Wages: New Evidence from Linked Employer-Employee Data," CIRANO Working Papers 2014s-40, CIRANO.
    4. Hoderlein, Stefan & White, Halbert, 2012. "Nonparametric identification in nonseparable panel data models with generalized fixed effects," Journal of Econometrics, Elsevier, vol. 168(2), pages 300-314.
    5. Khan, Shakeeb & Ponomareva, Maria & Tamer, Elie, 2011. "Identification of Panel Data Models with Endogenous Censoring," MPRA Paper 30373, University Library of Munich, Germany.
    6. Adam Rosen, 2009. "Set identification via quantile restrictions in short panels," CeMMAP working papers CWP26/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Philip Kostov & Julie Le Gallo, 2015. "Convergence: A Story of Quantiles and Spillovers," Kyklos, Wiley Blackwell, vol. 68(4), pages 552-576, November.
    8. Markevich, Andrei & Zhuravskaya, Ekaterina, 2011. "M-form hierarchy with poorly-diversified divisions: A case of Khrushchev's reform in Soviet Russia," Journal of Public Economics, Elsevier, vol. 95(11), pages 1550-1560.
    9. Ji-Liang Shiu & Yingyao Hu, 2010. "Identification and Estimation of Nonlinear Dynamic Panel Data Models with Unobserved Covariates," Economics Working Paper Archive 557, The Johns Hopkins University,Department of Economics.
    10. Manuel Arellano & Stéphane Bonhomme, 2009. "Identifying distributional characteristics in random coefficients panel data models," CeMMAP working papers CWP22/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    11. Ciani, Emanuele, 2012. "Informal adult care and caregivers' employment in Europe," Labour Economics, Elsevier, vol. 19(2), pages 155-164.
    12. Bryan S. Graham & James Powell, 2008. "Identification and Estimation of 'Irregular' Correlated Random Coefficient Models," NBER Working Papers 14469, National Bureau of Economic Research, Inc.
    13. Hyland, Marie & Bertsch, Valentin, 2018. "The Role of Community Involvement Mechanisms in Reducing Resistance to Energy Infrastructure Development," Ecological Economics, Elsevier, vol. 146(C), pages 447-474.
    14. Kyungchul Song, 2009. "Point Decisions for Interval-Identified Parameters," PIER Working Paper Archive 09-036, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    15. Bertsch, Valentin & Hyland, Marie & Mahony, Michael, 2017. "What drives people's opinions of electricity infrastructure? Empirical evidence from Ireland," Energy Policy, Elsevier, vol. 106(C), pages 472-497.
    16. Amaresh Tiwari & Franz Palm, 2011. "Nonlinear Panel Data Models with Expected a Posteriori Values of Correlated Random Effects," CREPP Working Papers 1113, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.
    17. Lewbel, Arthur & Yang, Thomas Tao, 2016. "Identifying the average treatment effect in ordered treatment models without unconfoundedness," Journal of Econometrics, Elsevier, vol. 195(1), pages 1-22.
    18. Bester, C. Alan & Hansen, Christian B., 2016. "Grouped effects estimators in fixed effects models," Journal of Econometrics, Elsevier, vol. 190(1), pages 197-208.
    19. Hu, Yingyao, 2017. "The Econometrics of Unobservables -- Latent Variable and Measurement Error Models and Their Applications in Empirical Industrial Organization and Labor Economics [The Econometrics of Unobservables]," Economics Working Paper Archive 64578, The Johns Hopkins University,Department of Economics, revised 2021.

  11. Hahn, Jinyong & Hirano, Keisuke & Karlan, Dean S., 2009. "Adaptive Experimental Design Using the Propensity Score," Center Discussion Papers 47107, Yale University, Economic Growth Center.

    Cited by:

    1. Masahiro Kato & Takuya Ishihara & Junya Honda & Yusuke Narita, 2020. "Efficient Adaptive Experimental Design for Average Treatment Effect Estimation," Papers 2002.05308, arXiv.org, revised Oct 2021.
    2. Masahiro Kato & Kaito Ariu, 2021. "The Role of Contextual Information in Best Arm Identification," Papers 2106.14077, arXiv.org, revised Feb 2024.
    3. Carneiro, Pedro & Lee, Sokbae & Wilhelm, Daniel, 2016. "Optimal Data Collection for Randomized Control Trials," IZA Discussion Papers 9908, Institute of Labor Economics (IZA).
    4. Alan Andre Borges da Costa & Sergio Pinheiro Firpo, 2018. "An analysis of the distributive effects of public policies and their spillovers," Working Papers, Department of Economics 2018_06, University of São Paulo (FEA-USP).
    5. Debopam Bhattacharya & Pascaline Dupas, 2008. "Inferring Welfare Maximizing Treatment Assignment under Budget Constraints," NBER Working Papers 14447, National Bureau of Economic Research, Inc.
    6. Aufenanger, Tobias, 2017. "Machine learning to improve experimental design," FAU Discussion Papers in Economics 16/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2017.
    7. Castillo-Manzano, José I. & López-Valpuesta, Lourdes & Sánchez-Braza, Antonio, 2018. "When the mall is in the airport: Measuring the effect of the airport mall on passengers’ consumer behavior," Journal of Air Transport Management, Elsevier, vol. 72(C), pages 32-38.
    8. Masahiro Kato & Shota Yasui & Kenichiro McAlinn, 2020. "The Adaptive Doubly Robust Estimator for Policy Evaluation in Adaptive Experiments and a Paradox Concerning Logging Policy," Papers 2010.03792, arXiv.org, revised Jun 2021.
    9. Jiang, Liang & Phillips, Peter C.B. & Tao, Yubo & Zhang, Yichong, 2023. "Regression-adjusted estimation of quantile treatment effects under covariate-adaptive randomizations," Journal of Econometrics, Elsevier, vol. 234(2), pages 758-776.
    10. Masahiro Kato, 2020. "Confidence Interval for Off-Policy Evaluation from Dependent Samples via Bandit Algorithm: Approach from Standardized Martingales," Papers 2006.06982, arXiv.org.
    11. Max Tabord-Meehan, 2018. "Stratification Trees for Adaptive Randomization in Randomized Controlled Trials," Papers 1806.05127, arXiv.org, revised Jul 2022.
    12. Masahiro Kato & Masaaki Imaizumi & Takuya Ishihara & Toru Kitagawa, 2023. "Asymptotically Optimal Fixed-Budget Best Arm Identification with Variance-Dependent Bounds," Papers 2302.02988, arXiv.org, revised Jul 2023.
    13. Liang Jiang & Xiaobin Liu & Peter C.B. Phillips & Yichong Zhang, 2020. "Bootstrap Inference for Quantile Treatment Effects in Randomized Experiments with Matched Pairs," Cowles Foundation Discussion Papers 2249, Cowles Foundation for Research in Economics, Yale University.
    14. John List & Sally Sadoff & Mathis Wagner, 2011. "So you want to run an experiment, now what? Some simple rules of thumb for optimal experimental design," Experimental Economics, Springer;Economic Science Association, vol. 14(4), pages 439-457, November.
    15. Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 45/17, Institute for Fiscal Studies.
    16. Masahiro Kato, 2021. "Adaptive Doubly Robust Estimator from Non-stationary Logging Policy under a Convergence of Average Probability," Papers 2102.08975, arXiv.org, revised Mar 2021.
    17. G�nther Fink & Margaret McConnell & Sebastian Vollmer, 2014. "Testing for heterogeneous treatment effects in experimental data: false discovery risks and correction procedures," Journal of Development Effectiveness, Taylor & Francis Journals, vol. 6(1), pages 44-57, January.
    18. Ahnaf Rafi, 2023. "Efficient Semiparametric Estimation of Average Treatment Effects Under Covariate Adaptive Randomization," Papers 2305.08340, arXiv.org.
    19. Yong Cai & Ahnaf Rafi, 2022. "On the Performance of the Neyman Allocation with Small Pilots," Papers 2206.04643, arXiv.org, revised Mar 2024.
    20. Timothy B. Armstrong & Shu Shen, 2013. "Inference on Optimal Treatment Assignments," Cowles Foundation Discussion Papers 1927, Cowles Foundation for Research in Economics, Yale University.
    21. Kyungchul Song, 2009. "Efficient Estimation of Average Treatment Effects under Treatment-Based Sampling," PIER Working Paper Archive 09-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    22. Dean Karlan & Daniel H. Wood, 2014. "The Effect of Effectiveness: Donor Response to Aid Effectiveness in a Direct Mail Fundraising Experiment," NBER Working Papers 20047, National Bureau of Economic Research, Inc.
    23. Yusuke Narita, 2018. "Toward an Ethical Experiment," Cowles Foundation Discussion Papers 2127, Cowles Foundation for Research in Economics, Yale University.
    24. Masahiro Kato & Masaaki Imaizumi & Takuya Ishihara & Toru Kitagawa, 2022. "Best Arm Identification with Contextual Information under a Small Gap," Papers 2209.07330, arXiv.org, revised Jan 2023.
    25. Masahiro Kato & Kenshi Abe & Kaito Ariu & Shota Yasui, 2020. "A Practical Guide of Off-Policy Evaluation for Bandit Problems," Papers 2010.12470, arXiv.org.
    26. Yusuke Narita, 2019. "Experiment-as-Market: Incorporating Welfare into Randomized Controlled Trials," Working Papers 2019-025, Human Capital and Economic Opportunity Working Group.
    27. Ravichandran Arun & Pashley Nicole E. & Dasgupta Tirthankar & Libgober Brian, 2024. "Optimal allocation of sample size for randomization-based inference from 2K factorial designs," Journal of Causal Inference, De Gruyter, vol. 12(1), pages 1-18, January.
    28. Harrison H. Li & Art B. Owen, 2023. "Double machine learning and design in batch adaptive experiments," Papers 2309.15297, arXiv.org.
    29. Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2017. "Optimal Design of Experiments in the Presence of Interference*, Second Version," PIER Working Paper Archive 16-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 30 Nov 2017.
    30. Masahiro Kato & Akihiro Oga & Wataru Komatsubara & Ryo Inokuchi, 2024. "Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choices," Papers 2403.03589, arXiv.org.
    31. Yichong Zhang & Xin Zheng, 2020. "Quantile treatment effects and bootstrap inference under covariate‐adaptive randomization," Quantitative Economics, Econometric Society, vol. 11(3), pages 957-982, July.
    32. Liang Jiang & Oliver B. Linton & Haihan Tang & Yichong Zhang, 2022. "Improving Estimation Efficiency via Regression-Adjustment in Covariate-Adaptive Randomizations with Imperfect Compliance," Papers 2201.13004, arXiv.org, revised Jun 2023.
    33. Max Cytrynbaum, 2021. "Optimal Stratification of Survey Experiments," Papers 2111.08157, arXiv.org, revised Aug 2023.
    34. Masahiro Kato & Yusuke Kaneko, 2020. "Off-Policy Evaluation of Bandit Algorithm from Dependent Samples under Batch Update Policy," Papers 2010.13554, arXiv.org.
    35. Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2017. "Optimal data collection for randomized control trials," CeMMAP working papers 15/17, Institute for Fiscal Studies.
    36. Masahiro Kato, 2023. "Worst-Case Optimal Multi-Armed Gaussian Best Arm Identification with a Fixed Budget," Papers 2310.19788, arXiv.org, revised Mar 2024.
    37. Pedro Carneiro & Sokbae (Simon) Lee & Daniel Wilhelm, 2016. "Optimal data collection for randomized control trials," CeMMAP working papers 15/16, Institute for Fiscal Studies.
    38. Víctor Casero-Alonso & Jesús López-Fidalgo, 2015. "Experimental designs in triangular simultaneous equations models," Statistical Papers, Springer, vol. 56(2), pages 273-290, May.
    39. Masahiro Kato, 2023. "Locally Optimal Fixed-Budget Best Arm Identification in Two-Armed Gaussian Bandits with Unknown Variances," Papers 2312.12741, arXiv.org, revised Mar 2024.
    40. Aufenanger, Tobias, 2018. "Treatment allocation for linear models," FAU Discussion Papers in Economics 14/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics, revised 2018.

  12. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney Newey, 2009. "Average and Quantile Effects in Nonseparable Panel Models," Papers 0904.1990, arXiv.org, revised Mar 2013.

    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. Demetrescu, Matei & Hosseinkouchack, Mehdi & Rodrigues, Paulo M. M., 2023. "Tests of no cross-sectional error dependence in panel quantile regressions," Ruhr Economic Papers 1041, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    3. Ivan Fernandez-Val & Hugo Freeman & Martin Weidner, 2020. "Low-rank approximations of nonseparable panel models," CeMMAP working papers CWP52/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Kate Ho & Adam M. Rosen, 2015. "Partial Identification in Applied Research: Benefits and Challenges," NBER Working Papers 21641, National Bureau of Economic Research, Inc.
    5. Carro, Jesús M. & Pronkina, Elizaveta, 2021. "The heterogeneous effects of the Great Recession on informal care to the elderly," UC3M Working papers. Economics 33444, Universidad Carlos III de Madrid. Departamento de Economía.
    6. Christopher Dobronyi & Jiaying Gu & Kyoo il Kim, 2021. "Identification of Dynamic Panel Logit Models with Fixed Effects," Papers 2104.04590, arXiv.org, revised Apr 2021.
    7. Brantly Callaway & Tong Li, 2019. "Quantile treatment effects in difference in differences models with panel data," Quantitative Economics, Econometric Society, vol. 10(4), pages 1579-1618, November.
    8. Kevin Dano, 2023. "Transition Probabilities and Moment Restrictions in Dynamic Fixed Effects Logit Models," Papers 2303.00083, arXiv.org, revised Dec 2023.
    9. Pedro H. C. Sant'Anna & Jun B. Zhao, 2018. "Doubly Robust Difference-in-Differences Estimators," Papers 1812.01723, arXiv.org, revised May 2020.
    10. Desire Kedagni & Kala Krishna & Rigissa Megalokonomou & Yingyan Zhao, 2019. "Does Class Size Matter? How, and at What Cost?," NBER Working Papers 25736, National Bureau of Economic Research, Inc.
    11. Shu Yang & Yunshu Zhang, 2023. "Multiply robust matching estimators of average and quantile treatment effects," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 235-265, March.
    12. 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.
    13. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods and an Application on the Minimum Wage and Employment," DETU Working Papers 1804, Department of Economics, Temple University.
    14. 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.
    15. Brantly Callaway & Pedro H. C. Sant'Anna, 2018. "Difference-in-Differences with Multiple Time Periods," Papers 1803.09015, arXiv.org, revised Dec 2020.
    16. Clément de Chaisemartin & Xavier D’haultfœuille, 2022. "Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey," Post-Print hal-03873885, HAL.
    17. Ghanem, Dalia, 2017. "Testing identifying assumptions in nonseparable panel data models," Journal of Econometrics, Elsevier, vol. 197(2), pages 202-217.
    18. Pauline Givord & Lionel Wilner, 2015. "When Does the Stepping‐Stone Work? Fixed‐Term Contracts Versus Temporary Agency Work in Changing Economic Conditions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(5), pages 787-805, August.
    19. Michelle Marcus & Pedro H. C. Sant’Anna, 2021. "The Role of Parallel Trends in Event Study Settings: An Application to Environmental Economics," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 8(2), pages 235-275.
    20. Xavier D'Haultfoeuille & Stefan Hoderlein & Yuya Sasaki, 2013. "Nonlinear Difference-in-Differences in Repeated Cross Sections with Continuous Treatments," Boston College Working Papers in Economics 839, Boston College Department of Economics.
    21. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.
    22. Carro, Jesús M. & Traferri, Alejandra, 2011. "State dependence and heterogeneity in health using a bias corrected fixed effects estimator," UC3M Working papers. Economics we1118, Universidad Carlos III de Madrid. Departamento de Economía.
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    7. Laura Hospido, 2007. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," Working Papers wp2007_0717, CEMFI.
    8. Manuel Arellano & Stéphane Bonhomme & Micole De Vera & Laura Hospido & Siqi Wei, 2021. "Income Risk Inequality: Evidence from Spanish Administrative Records," Working Papers 2136, Banco de España.
    9. Geert Dhaene & Koen Jochmans, 2016. "Likelihood Inference in an Autoregression with Fixed Effects," Post-Print hal-03391995, HAL.
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    28. Jan Engelmann & Alejandro Hirmas & Joël van der Weele, 2021. "Top Down or Bottom Up? Disentangling the Channels of Attention in Risky Choice," Tinbergen Institute Discussion Papers 21-031/I, Tinbergen Institute.
    29. Pakel, Cavit, 2019. "Bias reduction in nonlinear and dynamic panels in the presence of cross-section dependence," Journal of Econometrics, Elsevier, vol. 213(2), pages 459-492.
    30. Amaresh Tiwari & Franz Palm, 2011. "Nonlinear Panel Data Models with Expected a Posteriori Values of Correlated Random Effects," CREPP Working Papers 1113, Centre de Recherche en Economie Publique et de la Population (CREPP) (Research Center on Public and Population Economics) HEC-Management School, University of Liège.
    31. Vasilis Sarafidis & Tom Wansbeek, 2020. "Celebrating 40 Years of Panel Data Analysis: Past, Present and Future," Monash Econometrics and Business Statistics Working Papers 6/20, Monash University, Department of Econometrics and Business Statistics.
    32. Dhaene, Geert & Sun, Yutao, 2021. "Second-order corrected likelihood for nonlinear panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 220(2), pages 227-252.
    33. Francesco Bartolucci & Francesco Valentini & Claudia Pigini, 2023. "Recursive Computation of the Conditional Probability Function of the Quadratic Exponential Model for Binary Panel Data," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 529-557, February.
    34. Fernández-Val, Iván, 2009. "Fixed effects estimation of structural parameters and marginal effects in panel probit models," Journal of Econometrics, Elsevier, vol. 150(1), pages 71-85, May.
    35. Lai, Hung-pin & Kumbhakar, Subal C., 2019. "Technical and allocative efficiency in a panel stochastic production frontier system model," European Journal of Operational Research, Elsevier, vol. 278(1), pages 255-265.
    36. Dmitry Arkhangelsky & Guido Imbens, 2018. "Fixed Effects and the Generalized Mundlak Estimator," Papers 1807.02099, arXiv.org, revised Aug 2023.
    37. Xuan Leng & Jiaming Mao & Yutao Sun, 2023. "Debiased inference for dynamic nonlinear models with two-way fixed effects," Papers 2305.03134, arXiv.org, revised Oct 2023.
    38. Carro, Jesús M. & Traferri, Alejandra, 2009. "Correcting the bias in the estimation of a dynamic ordered probit with fixed effects of self-assessed health status," UC3M Working papers. Economics we094021, Universidad Carlos III de Madrid. Departamento de Economía.
    39. Geert Dhaene & Martin Weidner, 2023. "Approximate Functional Differencing," Papers 2301.13736, arXiv.org, revised May 2023.

  14. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2005. "Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed E¤ects," Boston University - Department of Economics - Working Papers Series WP2005-024, Boston University - Department of Economics.

    Cited by:

    1. Jerry Hausman & Guido Kuersteiner, 2005. "Difference in Difference Meets Generalized Least Squares: Higher Order Properties of Hypotheses Tests," Boston University - Department of Economics - Working Papers Series WP2005-010, Boston University - Department of Economics.
    2. Arcand Jean-Louis & Béatrice d'Hombres, 2005. "Explaining the Negative Coefficient Associated with Human Capital in Augmented Solow Growth Regressions," Macroeconomics 0510010, University Library of Munich, Germany.
    3. Lawrence J. Christiano & Martin S. Eichenbaum & Robert J. Vigfusson, 2003. "What happens after a technology shock?," International Finance Discussion Papers 768, Board of Governors of the Federal Reserve System (U.S.).
    4. Peter C.B. Phillips & Donggyu Sul, 2004. "Bias in Dynamic Panel Estimation with Fixed Effects, Incidental Trends and Cross Section Dependence," Yale School of Management Working Papers ysm428, Yale School of Management.
    5. Chihwa Kao & Yongmiao Hong, 2004. "Detecting Neglected Nonlinearity in Dynamic Panel Data with Time-Varying Conditional Heteroskedasticity," Econometric Society 2004 Far Eastern Meetings 753, Econometric Society.
    6. Phillips, Peter & Sul, Donggyu, 2002. "Dynamic Panel Estimation and Homogenity Testing Under Cross Section Dependence," Working Papers 194, Department of Economics, The University of Auckland.
    7. John Chao & Norman R. Swanson, 2003. "Alternative Approximations of the Bias and MSE of the IV Estimator under Weak Identification with an Application to Bias Correction," Cowles Foundation Discussion Papers 1418, Cowles Foundation for Research in Economics, Yale University.
    8. Hyungsik Roger Moon & Peter C. B. Phillips, 2004. "GMM Estimation of Autoregressive Roots Near Unity with Panel Data," Econometrica, Econometric Society, vol. 72(2), pages 467-522, March.
    9. Coen Teulings & Thijs van Rens, 2008. "Education, Growth, and Income Inequality," The Review of Economics and Statistics, MIT Press, vol. 90(1), pages 89-104, February.
    10. Rodrigo Alfaro & Helmut Franken & Carlos García & Alejandro Jara, 2003. "Bank Lending Channel and the Monetary Transmission Mechanism: the Case of Chile," Working Papers Central Bank of Chile 223, Central Bank of Chile.
    11. Rodrigo Alfaro & Helmut Franken & Carlos García & Alejandro Jara, 2004. "The Bank Lending Channel in Chile," Central Banking, Analysis, and Economic Policies Book Series, in: Luis Antonio Ahumada & J. Rodrigo Fuentes & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Se (ed.),Banking Market Structure and Monetary Policy, edition 1, volume 7, chapter 4, pages 121-146, Central Bank of Chile.
    12. Philip Brock & Helmut Franken M., 2003. "Measuring the Determinants of Average and Marginal Bank Interest Rate Spreads in Chile, 1994-2001," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 6(3), pages 45-65, December.
    13. Daron Acemoglu & Suresh Naidu & Pascual Restrepo & James A. Robinson, 2014. "Democracy Does Cause Growth," NBER Working Papers 20004, National Bureau of Economic Research, Inc.
    14. Carlos Budnevich L. & Helmut Franken M., 2003. "Market Discipline in Depositors’ Behavior and the Role of Risk-Rating Agencies: The Case of Chile," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 6(2), pages 45-70, August.
    15. Kazuhiko Hayakawa, 2006. "Efficient GMM Estimation of Dynamic Panel Data Models Where Large Heterogeneity May Be Present," Hi-Stat Discussion Paper Series d05-130, Institute of Economic Research, Hitotsubashi University.
    16. Kazuhiko Hayakawa, 2005. "Small Sample Bias Propreties of the System GMM Estimator in Dynamic Panel Data Models," Hi-Stat Discussion Paper Series d05-82, Institute of Economic Research, Hitotsubashi University.

  15. Manuel Arellano & Jinyong Hahn, 2005. "Understanding Bias in Nonlinear Panel Models: Some Recent Developments," Working Papers wp2005_0507, CEMFI.

    Cited by:

    1. Beatriz Domínguez & Juan José Ganuza & Gerard Llobet, 2005. "R&D in the pharmaceutical industry: A world of small innovations," Economics Working Papers 936, Department of Economics and Business, Universitat Pompeu Fabra.
    2. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile and probability curves without crossing," CeMMAP working papers CWP10/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Xiaoming Li, 2011. "Fixed Effects Estimation in Panel Nonlinear Fractional Response Models," Working papers 2011-11, University of Connecticut, Department of Economics.
    4. Manuel Arellano & Stéphane Bonhomme, 2007. "Robust priors in nonlinear panel data models," CeMMAP working papers CWP07/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Martin Browning & Jesus Carro, 2006. "Heterogeneity and Microeconometrics Modelling," CAM Working Papers 2006-03, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    6. Khalifa, Sherin & Petri, Svetlana & Henning, Christian H. C. A., 2020. "If climate change can trigger civil conflict, can good policy trigger peace? Empirical evidence from cross-country panel data," Working Papers of Agricultural Policy WP2020-01, University of Kiel, Department of Agricultural Economics, Chair of Agricultural Policy.
    7. Dötz, Niko & Fischer, Christoph, 2010. "What can EMU countries' sovereign bond spreads tell us about market perceptions of default probabilities during the recent financial crisis?," Discussion Paper Series 1: Economic Studies 2010,11, Deutsche Bundesbank.
    8. Vicente Royuela, 2015. "The role of urbanisation on international migrations: a case study of EU and ENP countries," International Journal of Manpower, Emerald Group Publishing Limited, vol. 36(4), pages 469-490, July.
    9. Wang, Xichen & Yan, Ji (Karena) & Yan, Cheng & Gozgor, Giray, 2021. "Emerging stock market exuberance and international short-term flows," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    10. Javier Diaz-Gimenez & Josep Pijoan-Mas, 2006. "Flat Tax Reforms in the U.S.: a Boon for the Income Poor," Computing in Economics and Finance 2006 400, Society for Computational Economics.
    11. Galvao Jr, A. F. & Montes-Rojas, G., 2009. "Instrumental variables quantile regression for panel data with measurement errors," Working Papers 09/06, Department of Economics, City University London.
    12. José Cerón & Javier Suarez, 2006. "Hot and Cold Housing Markets: International Evidence," Working Papers wp2006_0603, CEMFI.
    13. Fernández-Val, Iván & Vella, Francis, 2011. "Bias corrections for two-step fixed effects panel data estimators," Journal of Econometrics, Elsevier, vol. 163(2), pages 144-162, August.
    14. Tomohiro Ando & Jushan Bai, 2016. "Panel Data Models with Grouped Factor Structure Under Unknown Group Membership," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 163-191, January.
    15. Innocent BAYAI & Sylvanus IKHIDE, 2018. "FINANCING STRUCTURE AND FINANCIAL SUSTAINABILITY OF SELECTED SADC MICROFINANCE INSTITUTIONS (MFIs)," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 89(4), pages 665-696, December.
    16. Xiaokun Wang & Kara M. Kockelman, 2009. "Baysian Inference For Ordered Response Data With A Dynamic Spatial‐Ordered Probit Model," Journal of Regional Science, Wiley Blackwell, vol. 49(5), pages 877-913, December.
    17. Contoyannis, Paul & Li, Jinhu, 2011. "The evolution of health outcomes from childhood to adolescence," Journal of Health Economics, Elsevier, vol. 30(1), pages 11-32, January.
    18. Aleix Calveras & Juan José Ganuza & Gerard Llobet, 2005. "Regulation and opportunism: How much activism do we need?," Economics Working Papers 935, Department of Economics and Business, Universitat Pompeu Fabra.
    19. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    20. Yang, Zhenlin & Yu, Jihai & Liu, Shew Fan, 2016. "Bias correction and refined inferences for fixed effects spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 52-72.
    21. Orcun Kaya, 2014. "Is perceived financial inadequacy persistent?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(4), pages 636-654, December.

  16. Jinyong Hahn & Hyungsik Roger Moon, 2004. "Reducing Bias of MLE in a Dynamic Panel Model," IEPR Working Papers 04.5, Institute of Economic Policy Research (IEPR).

    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. Ivan Fernandez-Val & Martin Weidner, 2018. "Fixed effect estimation of large T panel data models," CeMMAP working papers CWP22/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Martin Weidner & Thomas Zylkin, 2021. "Bias and consistency in three-way gravity models," CeMMAP working papers CWP11/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Hyungsik Roger Moon & Martin Weidner, 2013. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers CWP63/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Pesaran, Hashem & Chudik, Alexander, 2013. "Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Data Models with Weakly Exogenous Regressors," Cambridge Working Papers in Economics 1317, Faculty of Economics, University of Cambridge.
    6. Alexander Chudik & M. Hashem Pesaran, 2017. "An Augmented Anderson-Hsiao Estimator for Dynamic Short-T Panels," Globalization Institute Working Papers 327, Federal Reserve Bank of Dallas, revised 27 Mar 2021.
    7. Devdatta Ray & Mikael Linden, 2020. "Health expenditure, longevity, and child mortality: dynamic panel data approach with global data," International Journal of Health Economics and Management, Springer, vol. 20(1), pages 99-119, March.
    8. Dhaene, Geert & Jochmans, Koen, 2016. "Bias-corrected estimation of panel vector autoregressions," Economics Letters, Elsevier, vol. 145(C), pages 98-103.
    9. William F. Lincoln & Andrew H. McCallum & Michael Siemer, 2019. "The Great Recession and a Missing Generation of Exporters," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 67(4), pages 703-745, December.
    10. Ivan Fernandez-Val & Martin Weidner, 2015. "Individual and time effects in nonlinear panel models with large N , T," CeMMAP working papers 17/15, Institute for Fiscal Studies.
    11. Ivan Fernandez-Val & Martin Weidner, 2017. "Fixed effect estimation of large T panel data models," CeMMAP working papers 42/17, Institute for Fiscal Studies.
    12. Badi H. Baltagi, 2013. "Dynamic panel data models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 10, pages 229-248, Edward Elgar Publishing.
    13. Arturas Juodis, 2015. "Iterative Bias Correction Procedures Revisited: A Small Scale Monte Carlo Study," UvA-Econometrics Working Papers 15-02, Universiteit van Amsterdam, Dept. of Econometrics.
    14. William F. Lincoln & Andrew H. McCallum & Michael Siemer, 2017. "The Great Recession and a Missing Generation of Exporters," Finance and Economics Discussion Series 2017-108, Board of Governors of the Federal Reserve System (U.S.).
    15. David Emanuel Andersson & Åke E. Andersson & Björn Hårsman & Xiyi Yang, 2020. "The geography of science in 12 European countries: a NUTS2-level analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1099-1125, August.
    16. William F. Lincoln & Andrew H. McCallum & Michael Siemer, 2018. "The Great Recession and a Missing Generation of Exporters," Working Papers 18-33, Center for Economic Studies, U.S. Census Bureau.
    17. Alexander Chudik & M. Hashem Pesaran & Jui-Chung Yang, 2016. "Half-panel jackknife fixed effects estimation of panels with weakly exogenous regressor," Globalization Institute Working Papers 281, Federal Reserve Bank of Dallas.
    18. Arturas Juodis & Simon Reese, 2018. "The Incidental Parameters Problem in Testing for Remaining Cross-section Correlation," Papers 1810.03715, arXiv.org, revised Feb 2021.
    19. Alexander Chudik & M. Hashem Pesaran, 2017. "A Bias-Corrected Method of Moments Approach to Estimation of Dynamic Short-T Panels," CESifo Working Paper Series 6688, CESifo.
    20. Alexander Chudik & M. Hashem Pesaran & Jui‐Chung Yang, 2018. "Half‐panel jackknife fixed‐effects estimation of linear panels with weakly exogenous regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(6), pages 816-836, September.
    21. Chambers, Marcus J., 2013. "Jackknife estimation of stationary autoregressive models," Journal of Econometrics, Elsevier, vol. 172(1), pages 142-157.
    22. Ivan Fernandez-Val & Martin Weidner, 2014. "Individual and time effects in nonlinear panel models with large N , T," CeMMAP working papers 32/14, Institute for Fiscal Studies.
    23. Chihwa Kao & Long Liu & Rui Sun, 2021. "A bias-corrected fixed effects estimator in the dynamic panel data model," Empirical Economics, Springer, vol. 60(1), pages 205-225, January.
    24. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    25. Haruo Iwakura & Ryo Okui, 2014. "Asymptotic Efficiency in Factor Models and Dynamic Panel Data Models," KIER Working Papers 887, Kyoto University, Institute of Economic Research.
    26. Yang, Zhenlin & Yu, Jihai & Liu, Shew Fan, 2016. "Bias correction and refined inferences for fixed effects spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 52-72.
    27. Okui, Ryo, 2011. "Asymptotically unbiased estimation of autocovariances and autocorrelations for panel data with incidental trends," Economics Letters, Elsevier, vol. 112(1), pages 49-52, July.
    28. Xuan Leng & Jiaming Mao & Yutao Sun, 2023. "Debiased inference for dynamic nonlinear models with two-way fixed effects," Papers 2305.03134, arXiv.org, revised Oct 2023.
    29. Ivan Fernandez-Val & Martin Weidner, 2013. "Individual and time effects in nonlinear panel models with large N, T," CeMMAP working papers 60/13, Institute for Fiscal Studies.
    30. Hyungsik Roger Roger Moon & Martin Weidner, 2013. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers 63/13, Institute for Fiscal Studies.
    31. Khalaf, Lynda & Saunders, Charles J., 2020. "Monte Carlo two-stage indirect inference (2SIF) for autoregressive panels," Journal of Econometrics, Elsevier, vol. 218(2), pages 419-434.
    32. William Lincoln & Andrew McCallum & Michael Siemer, 2018. "The Great Recession and a Missing Generation of Exporters," 2018 Meeting Papers 558, Society for Economic Dynamics.

  17. Jinyong Hahn & Whitney K. Newey, 2003. "Jackknife and analytical bias reduction for nonlinear panel models," CeMMAP working papers 17/03, 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. Fatima Olanike Kareem & Bernhard Brümmer & Inmaculada Martinez-Zarzoso, 2017. "European Union Market Access Conditions and Africa's Extensive Margin of Food Trade," The World Economy, Wiley Blackwell, vol. 40(10), pages 2277-2300, October.
    3. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2022. "Discretizing Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 90(2), pages 625-643, March.
    4. Qingyan Shang & Lung-fei Lee, 2011. "Two-Step Estimation of Endogenous and Exogenous Group Effects," Econometric Reviews, Taylor & Francis Journals, vol. 30(2), pages 173-207.
    5. David W. Hughes, 2021. "Estimating Nonlinear Network Data Models with Fixed Effects," Boston College Working Papers in Economics 1058, Boston College Department of Economics.
    6. Cheng Hsiao & Qiankun Zhou, 2017. "JIVE for Panel Dynamic Simultaneous Equations Models," Departmental Working Papers 2017-10, Department of Economics, Louisiana State University.
    7. Yang, Zhenlin, 2015. "A general method for third-order bias and variance corrections on a nonlinear estimator," Journal of Econometrics, Elsevier, vol. 186(1), pages 178-200.
    8. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile and probability curves without crossing," CeMMAP working papers CWP10/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Taisuke Otsu & Martin Pesendorfer & Yuya Sasaki & Yuya Takahashi, 2020. "Estimation of (static or dynamic) games under equilibrium multiplicity," STICERD - Econometrics Paper Series 611, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    10. Hahn, Jinyong & Kuersteiner, Guido & Cho, Myeong Hyeon, 2004. "Asymptotic distribution of misspecified random effects estimator for a dynamic panel model with fixed effects when both n and T are large," Economics Letters, Elsevier, vol. 84(1), pages 117-125, July.
    11. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.
    12. Eric Fesselmeyer & Haoming Liu & Alberto Salvo, 2022. "Declining discount rates in Singapore's market for privately developed apartments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 330-350, March.
    13. Martin Weidner & Thomas Zylkin, 2021. "Bias and consistency in three-way gravity models," CeMMAP working papers CWP11/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Freyberger, Joachim, 2015. "Asymptotic theory for differentiated products demand models with many markets," Journal of Econometrics, Elsevier, vol. 185(1), pages 162-181.
    15. David S Jacks & Krishna Pendakur & Hitoshi Shigeoka, 2021. "Infant Mortality and the Repeal of Federal Prohibition," The Economic Journal, Royal Economic Society, vol. 131(639), pages 2955-2983.
    16. John Chao & Norman Swanson, 2004. "Consistent Estimation with a Large Number of Weak Instruments," Departmental Working Papers 200421, Rutgers University, Department of Economics.
    17. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers 45/13, Institute for Fiscal Studies.
    18. 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.
    19. Koen Jochmans, 2015. "Two-way models for gravity," Sciences Po publications 2015-09, Sciences Po.
    20. Liu, Yanbo & Phillips, Peter C. B. & Yu, Jun, 2022. "A Panel Clustering Approach to Analyzing Bubble Behavior," Economics and Statistics Working Papers 1-2022, Singapore Management University, School of Economics.
    21. Dzemski, Andreas, 2017. "An empirical model of dyadic link formation in a network with unobserved heterogeneity," Working Papers in Economics 698, University of Gothenburg, Department of Economics, revised Apr 2018.
    22. Kunz, Johannes S. & Staub, Kevin E. & Winkelmann, Rainer, 2017. "Estimating Fixed Effects: Perfect Prediction and Bias in Binary Response Panel Models, with an Application to the Hospital Readmissions Reduction Program," IZA Discussion Papers 11182, Institute of Labor Economics (IZA).
    23. Lee, Yoonseok & Phillips, Peter C.B., 2015. "Model selection in the presence of incidental parameters," Journal of Econometrics, Elsevier, vol. 188(2), pages 474-489.
    24. DHAENE, Geert & JOCHMANS, Koen, 2010. "Split-panel jackknife estimation of fixed-effect models," LIDAM Discussion Papers CORE 2010003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Pigini, Claudia, 2021. "Penalized maximum likelihood estimation of logit-based early warning systems," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1156-1172.
    26. Hyungsik Roger Moon & Martin Weidner, 2013. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers CWP63/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    27. Bali Swain, Ranjula & Kambhampati, Uma S. & Karimu, Amin, 2020. "Regulation, governance and the role of the informal sector in influencing environmental quality?," Ecological Economics, Elsevier, vol. 173(C).
    28. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2016. "A quantile correlated random coefficients panel data model," CeMMAP working papers 34/16, Institute for Fiscal Studies.
    29. Hoderlein, Stefan & White, Halbert, 2012. "Nonparametric identification in nonseparable panel data models with generalized fixed effects," Journal of Econometrics, Elsevier, vol. 168(2), pages 300-314.
    30. Carro, Jesús M. & Traferri, Alejandra, 2011. "State dependence and heterogeneity in health using a bias corrected fixed effects estimator," UC3M Working papers. Economics we1118, Universidad Carlos III de Madrid. Departamento de Economía.
    31. Hansen, Christian B., 2007. "Asymptotic properties of a robust variance matrix estimator for panel data when T is large," Journal of Econometrics, Elsevier, vol. 141(2), pages 597-620, December.
    32. Laura Hospido, 2007. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," Working Papers wp2007_0717, CEMFI.
    33. Sun, Yixiao & Kim, Min Seong, 2009. "k-step Bootstrap Bias Correction for Fixed Effects Estimators in Nonlinear Panel Models," University of California at San Diego, Economics Working Paper Series qt9gn6n5mr, Department of Economics, UC San Diego.
    34. Manuel Arellano & Stéphane Bonhomme, 2007. "Robust priors in nonlinear panel data models," CeMMAP working papers CWP07/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    35. Aman Ullah & Yoonseok Lee & Debasri Mukherjee, 2018. "Nonparametric Estimation of the Marginal Effect in Fixed-Effect Panel Data Models," Working Papers 201901, University of California at Riverside, Department of Economics.
    36. Jinyong Hahn & Ruoyao Shi, 2021. "Breusch and Pagan’s (1980) Test Revisited," Working Papers 202110, University of California at Riverside, Department of Economics.
    37. 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.
    38. Pesaran, Hashem & Chudik, Alexander, 2013. "Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Data Models with Weakly Exogenous Regressors," Cambridge Working Papers in Economics 1317, Faculty of Economics, University of Cambridge.
    39. Dubois, Pierre & Griffith, Rachel & O'Connell, Martin, 2017. "How well targeted are soda taxes?," CEPR Discussion Papers 12484, C.E.P.R. Discussion Papers.
    40. Martin M. Andreasen & Jens H.E. Christensen & Glenn D. Rudebusch, 2017. "Term Structure Analysis with Big Data," CREATES Research Papers 2017-31, Department of Economics and Business Economics, Aarhus University.
    41. Julia Rechlitz & Luis Sarmiento & Aleksandar Zaklan, 2020. "Make Sure the Kids are OK: Indirect Effects of Ground-Level Ozone on Well-Being," Discussion Papers of DIW Berlin 1877, DIW Berlin, German Institute for Economic Research.
    42. Ossola, Elisa & Gagilardini, Patrick & Scaillet, Olivier, 2015. "Time-varying risk premium in large cross-sectional equity datasets," Working Papers unige:76321, University of Geneva, Geneva School of Economics and Management.
    43. Natalia Bailey & Zvi Hochman & Yufeng Mao & Mervyn J. Silvapulle & Param Silvapulle, 2020. "Statistical Modelling and Forecast Evaluation of the Impact of Extreme Temperatures on Wheat Crops in North Western Victoria," Monash Econometrics and Business Statistics Working Papers 18/20, Monash University, Department of Econometrics and Business Statistics.
    44. Hyungsik Roger Moon & Matthew Shum & Martin Weidner, 2012. "Estimation of random coefficients logit demand models with interactive fixed effects," CeMMAP working papers CWP08/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    45. Andersen, Torben G. & Fusari, Nicola & Todorov, Viktor & Varneskov, Rasmus T., 2019. "Unified inference for nonlinear factor models from panels with fixed and large time span," Journal of Econometrics, Elsevier, vol. 212(1), pages 4-25.
    46. Lucchetti, Riccardo & Pigini, Claudia, 2017. "DPB: Dynamic Panel Binary Data Models in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i08).
    47. Bryan S. Graham, 2017. "An econometric model of network formation with degree heterogeneity," CeMMAP working papers CWP08/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    48. Martin Browning & Jesus Carro, 2006. "Heterogeneity and Microeconometrics Modelling," CAM Working Papers 2006-03, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    49. Geert Dhaene & Koen Jochmans, 2016. "Likelihood Inference in an Autoregression with Fixed Effects," Post-Print hal-03391995, HAL.
    50. Shew Fan Liu & Zhenlin Yang, 2015. "Asymptotic Distribution and Finite Sample Bias Correction of QML Estimators for Spatial Error Dependence Model," Econometrics, MDPI, vol. 3(2), pages 1-36, May.
    51. Wang, Fa, 2017. "Maximum likelihood estimation and inference for high dimensional nonlinear factor models with application to factor-augmented regressions," MPRA Paper 93484, University Library of Munich, Germany, revised 19 May 2019.
    52. Bo E. Honor√ & Daniel Kaufmann & Sarah Lein, 2012. "Asymmetries in Price-Setting Behavior: New Microeconometric Evidence from Switzerland," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44, pages 211-236, December.
    53. Daniel Shapiro & Yao Tang & Miaojun Wang & Weiying Zhang, 2017. "Monetary incentives and innovation in Chinese SMEs," Asian Business & Management, Palgrave Macmillan, vol. 16(3), pages 130-157, July.
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    205. St'ephane Bonhomme & Kevin Dano, 2023. "Functional Differencing in Networks," Papers 2307.11484, arXiv.org.
    206. Bedre Defolie, Özlem & Alexandrov, Alexei & Grodzicki, Daniel, 2017. "Consumer Demand for Credit Card Services," CEPR Discussion Papers 12506, C.E.P.R. Discussion Papers.
    207. Xuan Leng & Jiaming Mao & Yutao Sun, 2023. "Debiased inference for dynamic nonlinear models with two-way fixed effects," Papers 2305.03134, arXiv.org, revised Oct 2023.
    208. Blair Alexander & Robert Breunig, 2012. "A Monte Carlo Study of Bias Corrections for Panel Probit Models," CEPR Discussion Papers 662, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    209. Shiyun Cao & Yonghui Zhang & Qiankun Zhou, 2021. "2SLS and IV Estimation of Dynamic Panel Models with Heterogeneous Trend," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(6), pages 1408-1431, December.
    210. Orcun Kaya, 2014. "Is perceived financial inadequacy persistent?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(4), pages 636-654, December.
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    215. Golovan, Sergei & Volchkova, Natalya, 2022. "How costly is exporting? An empirical assessment of trade model with heterogeneous firms," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 68, pages 93-116.
    216. Cristian Bartolucci & Mathis Wagner & Claudia Villosio, 2013. "Who Migrates and Why?," Carlo Alberto Notebooks 333, Collegio Carlo Alberto.
    217. Carro, Jesús M. & Traferri, Alejandra, 2009. "Correcting the bias in the estimation of a dynamic ordered probit with fixed effects of self-assessed health status," UC3M Working papers. Economics we094021, Universidad Carlos III de Madrid. Departamento de Economía.
    218. Irene Botosaru & Chris Muris & Krishna Pendakur, 2020. "Intertemporal Collective Household Models: Identification in Short Panels with Unobserved Heterogeneity in Resource Shares," Department of Economics Working Papers 2020-09, McMaster University.
    219. Hyungsik Roger Roger Moon & Martin Weidner, 2013. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers 63/13, Institute for Fiscal Studies.
    220. Victor Chernozhukov & Hiroyuki Kasahara & Paul Schrimpf, 2021. "The Association of Opening K-12 Schools with the Spread of COVID-19 in the United States: County-Level Panel Data Analysis," Papers 2102.10453, arXiv.org, revised Jun 2021.
    221. Keita Abe & Christopher M. Anderson & Matthew N. Reimer, 2022. "Catch More to Catch Less: Estimating Timing Choice as Dynamic Bycatch Avoidance Behavior," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 82(4), pages 953-984, August.
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    230. Marta F. Arroyabe & Martin Schumann, 2022. "On the Estimation of True State Dependence in the Persistence of Innovation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 850-893, August.
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    235. Geert Dhaene & Martin Weidner, 2023. "Approximate Functional Differencing," Papers 2301.13736, arXiv.org, revised May 2023.
    236. Mingli Chen & Kengo Kato & Chenlei Leng, 2019. "Analysis of Networks via the Sparse $\beta$-Model," Papers 1908.03152, arXiv.org, revised Dec 2020.
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  18. Peter Christoffersen & Jinyong Hahn & Atsushi Inoue, 2001. "Testing and Comparing Value-at-Risk Measures," CIRANO Working Papers 2001s-03, CIRANO.

    Cited by:

    1. Marmer, Vadim & Otsu, Taisuke, 2008. "Optimal Comparison of Misspecified Moment Restriction Models under a Chosen Measure of Fit," Microeconomics.ca working papers vadim_marmer-2008-13, Vancouver School of Economics, revised 25 Jul 2011.
    2. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    3. Giacomini, Raffaella & Komunjer, Ivana, 2002. "Evaluation and Combination of Conditional Quantile Forecasts," University of California at San Diego, Economics Working Paper Series qt4n99t4wz, Department of Economics, UC San Diego.
    4. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    5. Kimera Naradh & Retius Chifurira & Knowledge Chinhamu, 2022. "Analysis of stock exchange risk and currency in South African Financial Markets using stable parameter estimation," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 11(1), pages 120-131, January.
    6. Wong, Woon K., 2010. "Backtesting value-at-risk based on tail losses," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 526-538, June.
    7. Kerkhof, F.L.J. & Melenberg, B. & Schumacher, J.M., 2003. "Testing Expected Shortfall Models for Derivative Positions," Discussion Paper 2003-24, Tilburg University, Center for Economic Research.
    8. David E. Allen & Mohammad A. Ashraf & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2013. "Financial Dependence Analysis: Applications of Vine Copulae," Tinbergen Institute Discussion Papers 13-022/III, Tinbergen Institute.
    9. Ngozi G. Emenogu & Monday Osagie Adenomon & Nwaze Obini Nweze, 2020. "On the volatility of daily stock returns of Total Nigeria Plc: evidence from GARCH models, value-at-risk and backtesting," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-25, December.
    10. David E. Allen & Michael McAleer & Abhay K. Singh, 2014. "Risk Measurement and Risk Modelling using Applications of Vine Copulas," Tinbergen Institute Discussion Papers 14-054/III, Tinbergen Institute.
    11. Santos, André A. P. & Nogales, Francisco J. & Ruiz Ortega, Esther, 2009. "Comparing univariate and multivariate models to forecast portfolio value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws097222, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Wessam M. T. Abouarghoub & Iris Biefang-Frisancho Mariscal, 2011. "Measuring level of risk exposure in tanker Shipping freight markets," International Journal of Business and Social Research, LAR Center Press, vol. 1(1), pages 20-44, December.
    13. Yuichi Kitamura, 2006. "Empirical Likelihood Methods in Econometrics: Theory and Practice," CIRJE F-Series CIRJE-F-430, CIRJE, Faculty of Economics, University of Tokyo.
    14. Abdul Hakim, 2009. "Forcasting portofolio value-at-risk for international stocks, bonds, and foreign exchange emerging market evidence," Economic Journal of Emerging Markets, Universitas Islam Indonesia, vol. 1(1), pages 13-26, April.
    15. Hasna Fadhila & Nora Amelda Rizal, 2013. "Analysis of Risk using Value at Risk (VaR) After Crisis in 2008 Study in Stocks of Bank Mandiri, Bank BRI and Bank BNI in 2009-2011," Information Management and Business Review, AMH International, vol. 5(8), pages 394-400.
    16. Roberta Fiori & Simonetta Iannotti, 2006. "Scenario Based Principal Component Value-at-Risk: an Application to Italian Banks' Interest Rate Risk Exposure," Temi di discussione (Economic working papers) 602, Bank of Italy, Economic Research and International Relations Area.
    17. Chen, Xiaohong & Hong, Han & Shum, Matthew, 2007. "Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models," Journal of Econometrics, Elsevier, vol. 141(1), pages 109-140, November.
    18. Zhijie Xiao, 2009. "Quantile Cointegrating Regression," Boston College Working Papers in Economics 708, Boston College Department of Economics.
    19. Chesney, Marc & Reshetar, Ganna & Karaman, Mustafa, 2011. "The impact of terrorism on financial markets: An empirical study," Journal of Banking & Finance, Elsevier, vol. 35(2), pages 253-267, February.
    20. Sueishi, Naoya, 2013. "Identification problem of the exponential tilting estimator under misspecification," Economics Letters, Elsevier, vol. 118(3), pages 509-511.
    21. Valentina Corradi & Norman Swanson, 2004. "Predective Density and Conditional Confidence Interval Accuracy Tests," Departmental Working Papers 200423, Rutgers University, Department of Economics.
    22. Minglian Lin & Indranil SenGupta & William Wilson, 2023. "Estimation of VaR with jump process: application in corn and soybean markets," Papers 2311.00832, arXiv.org, revised Dec 2023.
    23. Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel R. Smith, 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 150-160, January.
    24. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    25. Peter Christoffersen & Denis Pelletier, 2003. "Backtesting Value-at-Risk: A Duration-Based Approach," CIRANO Working Papers 2003s-05, CIRANO.
    26. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    27. Jakub Micha'nk'ow & {L}ukasz Kwiatkowski & Janusz Morajda, 2023. "Combining Deep Learning and GARCH Models for Financial Volatility and Risk Forecasting," Papers 2310.01063, arXiv.org.
    28. Vijverberg, Chu-Ping C. & Vijverberg, Wim P.M. & Taşpınar, Süleyman, 2016. "Linking Tukey’s legacy to financial risk measurement," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 595-615.
    29. Wessam Abouarghoub & Iris Biefang-Frisancho Mariscal, 2013. "Measuring the level of risk exposure in tanker shipping freight markets," Working Papers 20131313, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    30. Metiu, N., 2011. "Financial contagion in developed sovereign bond markets," Research Memorandum 004, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    31. Krzysztof Echaust & Małgorzata Just, 2021. "Tail Dependence between Crude Oil Volatility Index and WTI Oil Price Movements during the COVID-19 Pandemic," Energies, MDPI, vol. 14(14), pages 1-21, July.
    32. Schmidt, Ulrich, 2003. "The axiomatic basis of risk-value models," European Journal of Operational Research, Elsevier, vol. 145(1), pages 216-220, February.
    33. Gaglianone, Wagner Piazza & Marins, Jaqueline Terra Moura, 2017. "Evaluation of exchange rate point and density forecasts: An application to Brazil," International Journal of Forecasting, Elsevier, vol. 33(3), pages 707-728.
    34. Elena Andreou & Eric Ghysels, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," CIRANO Working Papers 2004s-25, CIRANO.
    35. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    36. Ana-Maria Fuertes & Jose Olmo, 2016. "On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?," JRFM, MDPI, vol. 9(3), pages 1-20, September.
    37. Jeffrey Chu & Stephen Chan & Saralees Nadarajah & Joerg Osterrieder, 2017. "GARCH Modelling of Cryptocurrencies," JRFM, MDPI, vol. 10(4), pages 1-15, October.
    38. Li, Leon, 2017. "Testing and comparing the performance of dynamic variance and correlation models in value-at-risk estimation," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 116-135.
    39. Nikola Radivojevic & Milena Cvjetkovic & Saša Stepanov, 2016. "The new hybrid value at risk approach based on the extreme value theory," Estudios de Economia, University of Chile, Department of Economics, vol. 43(1 Year 20), pages 29-52, June.
    40. Olmo Jose & Pouliot William, 2011. "Early Detection Techniques for Market Risk Failure," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(4), pages 1-55, September.
    41. Kerkhof, F.L.J. & Melenberg, B., 2002. "Backtesting for Risk-Based Regulatory Capital," Other publications TiSEM 2363cf81-9720-41f2-913c-f, Tilburg University, School of Economics and Management.
    42. L. Kourouma & Denis Dupré & G. Sanfilippo & O. Taramasco, 2011. "Extreme Value at Risk and Expected Shortfall during Financial Crisis," Post-Print halshs-00658495, HAL.
    43. Otsu, Taisuke, 2008. "Conditional empirical likelihood estimation and inference for quantile regression models," Journal of Econometrics, Elsevier, vol. 142(1), pages 508-538, January.
    44. DeRossi, G. & Harvey, A., 2006. "Time-Varying Quantiles," Cambridge Working Papers in Economics 0649, Faculty of Economics, University of Cambridge.
    45. Fabozzi Frank J. & Stoyanov Stoyan V. & Rachev Svetlozar T., 2013. "Computational aspects of portfolio risk estimation in volatile markets: a survey," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(1), pages 103-120, February.
    46. Escanciano, J. C. & Olmo, J., 2007. "Estimation risk effects on backtesting for parametric value-at-risk models," Working Papers 07/11, Department of Economics, City University London.
    47. Carol Alexander & Jose Maria Sarabia, 2010. "Endogenizing Model Risk to Quantile Estimates," ICMA Centre Discussion Papers in Finance icma-dp2010-07, Henley Business School, University of Reading.
    48. Valentina Corradi & Norman Swanson, 2003. "The Block Bootstrap for Parameter Estimation Error In Recursive Estimation Schemes, With Applications to Predictive Evaluation," Departmental Working Papers 200313, Rutgers University, Department of Economics.
    49. Wagner Piazza Gaglianone & Jaqueline Terra Moura Marins, 2014. "Risk Assessment of the Brazilian FX Rate," Working Papers Series 344, Central Bank of Brazil, Research Department.
    50. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
    51. Kerkhof, Jeroen & Melenberg, Bertrand, 2004. "Backtesting for risk-based regulatory capital," Journal of Banking & Finance, Elsevier, vol. 28(8), pages 1845-1865, August.
    52. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    53. Pinto, Cristian F. & Acuña, Andres A., 2011. "Consistencia de la evaluación de desempeño de inversiones financieras: Pruebas de dominación estocástica versus índices media-varianza [Consistency in the evaluation of financial investment perform," MPRA Paper 31301, University Library of Munich, Germany.
    54. David Feldman & Xin Xu, 2018. "Equilibrium-based volatility models of the market portfolio rate of return (peacock tails or stotting gazelles)," Annals of Operations Research, Springer, vol. 262(2), pages 493-518, March.
    55. Kraft, Holger & Schmidt, Alexander, 2013. "Systemic risk in the financial sector: What can se learn from option markets?," SAFE Working Paper Series 25, Leibniz Institute for Financial Research SAFE.
    56. Hamidreza Arian & Hossein Poorvasei & Azin Sharifi & Shiva Zamani, 2020. "The Uncertain Shape of Grey Swans: Extreme Value Theory with Uncertain Threshold," Papers 2011.06693, arXiv.org.
    57. Tomáš Jeøábek, 2020. "The Efficiency of GARCH Models in Realizing Value at Risk Estimates," ACTA VSFS, University of Finance and Administration, vol. 14(1), pages 32-50.
    58. Lehar, Alfred & Scheicher, Martin & Schittenkopf, Christian, 2002. "GARCH vs. stochastic volatility: Option pricing and risk management," Journal of Banking & Finance, Elsevier, vol. 26(2-3), pages 323-345, March.
    59. Siva Kiran GUPTHA. K & Prabhakar RAO. R, 2019. "GARCH based VaR estimation: An empirical evidence from BRICS stock markets," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(4(621), W), pages 201-218, Winter.
    60. Georgios Fatouros & Georgios Makridis & Dimitrios Kotios & John Soldatos & Michael Filippakis & Dimosthenis Kyriazis, 2023. "DeepVaR: a framework for portfolio risk assessment leveraging probabilistic deep neural networks," Digital Finance, Springer, vol. 5(1), pages 29-56, March.
    61. Hong, Yongmiao & Liu, Yanhui & Wang, Shouyang, 2009. "Granger causality in risk and detection of extreme risk spillover between financial markets," Journal of Econometrics, Elsevier, vol. 150(2), pages 271-287, June.
    62. Metiu, Norbert, 2012. "Sovereign risk contagion in the Eurozone," Economics Letters, Elsevier, vol. 117(1), pages 35-38.
    63. Köksal, Bülent & Orhan, Mehmet, 2012. "Market risk of developed and developing countries during the global financial crisis," MPRA Paper 37523, University Library of Munich, Germany.
    64. Mirjana Miletić & Siniša Miletić, 2016. "Performance of VaR in Developed and CEE Countries during the Global Financial Crisis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 54-75, March.
    65. Kilic, Ekrem, 2006. "Violation duration as a better way of VaR model evaluation : evidence from Turkish market portfolio," MPRA Paper 5610, University Library of Munich, Germany.
    66. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
    67. Isengildina-Massa, Olga & Sharp, Julia L., 2013. "Interval Forecast Comparison," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150791, Agricultural and Applied Economics Association.
    68. Cerović Julija & Lipovina-Božović Milena & Vujošević Saša, 2015. "A Comparative Analysis of Value at Risk Measurement on Emerging Stock Markets: Case of Montenegro," Business Systems Research, Sciendo, vol. 6(1), pages 36-55, March.

  19. Joshua D. Angrist & Jinyong Hahn, 1999. "When to Control for Covariates? Panel-Asymptotic Results for Estimates of Treatment Effects," NBER Technical Working Papers 0241, National Bureau of Economic Research, Inc.

    Cited by:

    1. Simon Porcher, 2019. "Does Contracting for the Provision of Public Services Decrease Prices? Evidence from French Water Public Services," Working Papers hal-02145863, HAL.
    2. Joshua D. Angrist & Victor Lavy, 2002. "The Effect of High School Matriculation Awards: Evidence from Randomized Trials," NBER Working Papers 9389, National Bureau of Economic Research, Inc.
    3. Guido Imbens, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometric Society World Congress 2000 Contributed Papers 1166, Econometric Society.
    4. Jochen Kluve & Hartmut Lehmann & Christoph M. Schmidt, 2000. "Disentangling Treatment Effects of Polish Active Labour Market Policies: Evidence from Matched Samples," CERT Discussion Papers 0007, Centre for Economic Reform and Transformation, Heriot Watt University.
    5. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    6. Wooldridge, Jeffrey M. & Imbens, Guido, 2009. "Recent Developments in the Econometrics of Program Evaluation," Scholarly Articles 3043416, Harvard University Department of Economics.
    7. Mueser, Peter R. & Troske, Kenneth & Gorislavsky, Alexey, 2003. "Using State Administrative Data to Measure Program Performance," IZA Discussion Papers 786, Institute of Labor Economics (IZA).
    8. Joshua Angrist & Victor Lavy, 2003. "Achievement awards for high school matriculation: Evidence from randomized trials," Natural Field Experiments 00202, The Field Experiments Website.
    9. Kim, Jong Min & Jun, Mina & Kim, Chung K., 2018. "The Effects of Culture on Consumers' Consumption and Generation of Online Reviews," Journal of Interactive Marketing, Elsevier, vol. 43(C), pages 134-150.
    10. Foster, E. Michael & Stephens, Robert & Krivelyova, Anna & Gamfi, Phyllis, 2007. "Can system integration improve mental health outcomes for children and youth?," Children and Youth Services Review, Elsevier, vol. 29(10), pages 1301-1319, October.
    11. Augurzky, Boris & Kluve, Jochen, 2004. "Assessing the Performance of Matching Algorithms When Selection into Treatment Is Strong," IZA Discussion Papers 1301, Institute of Labor Economics (IZA).
    12. Fajnzylber, Pablo & Maloney, William F. & Rojas, Gabriel V. Montes, 2006. "Releasing constraints to growth or pushing on a string ? the impact of credit, training, business associations, and taxes on the performance of Mexican micro-firms," Policy Research Working Paper Series 3807, The World Bank.
    13. Angrist, Joshua & Lavy, Victor, 2004. "The Effect of High Stakes High School Achievement Awards: Evidence from a School-Centered Randomized Trial," IZA Discussion Papers 1146, Institute of Labor Economics (IZA).

  20. Jinyong Hahn & Petra Todd & Wilbert Van der Klaauw, 1999. "Evaluating the Effect of an Antidiscrimination Law Using a Regression-Discontinuity Design," NBER Working Papers 7131, National Bureau of Economic Research, Inc.

    Cited by:

    1. Brian A. Jacob & Lars Lefgren, 2002. "The Impact of Teacher Training on Student Achievement: Quasi-Experimental Evidence from School Reform Efforts in Chicago," NBER Working Papers 8916, National Bureau of Economic Research, Inc.
    2. Fort, Margherita, 2005. "Education and timing of births: evidence from a natural experiment in Italy," ISER Working Paper Series 2005-20, Institute for Social and Economic Research.
    3. Christina Korting & Carl Lieberman & Jordan Matsudaira & Zhuan Pei & Yi Shen, 2021. "Visual Inference and Graphical Representation in Regression Discontinuity Designs," Papers 2112.03096, arXiv.org, revised Jan 2023.
    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. Erich Battistin & Enrico Rettore, 2002. "Testing for programme effects in a regression discontinuity design with imperfect compliance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(1), pages 39-57, February.
    6. Zhuan Pei & David Card & David S. Lee & Andrea Weber, 2012. "Nonlinear Policy Rules and the Identification and Estimation of Causal Effects in a Generalized Regression Kink Design," Working Papers 60, Brandeis University, Department of Economics and International Business School.
    7. Brian A. Jacob & Lars Lefgren, 2002. "Remedial Education and Student Achievement: A Regression-Discontinuity Analysis," NBER Working Papers 8918, National Bureau of Economic Research, Inc.
    8. Pamela Cardozo & Fredy Gamboa & David Perez-Reyna & Mauricio Villamizar-Villegas, 2016. "Banking Limits on Foreign Holdings: Disentangling the Portfolio Balance Channel," Borradores de Economia 934, Banco de la Republica de Colombia.
    9. Burgert, Derik, 2006. "Einstellungschancen von Älteren – Wie wirkt der Schwellenwert im Kündigungsschutz?," MPRA Paper 5846, University Library of Munich, Germany.
    10. David Neumark & Wendy A. Stock, 2001. "The Effects of Race and Sex Discrimination Laws," NBER Working Papers 8215, National Bureau of Economic Research, Inc.
    11. David S. Lee & Thomas Lemieux, 2010. "Regression Discontinuity Designs in Economics," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 281-355, June.
    12. Frölich, Markus & Melly, Blaise, 2008. "Quantile Treatment Effects in the Regression Discontinuity Design," IZA Discussion Papers 3638, Institute of Labor Economics (IZA).
    13. Guido Imbens & Thomas Lemieux, 2007. "Regression Discontinuity Designs: A Guide to Practice," NBER Technical Working Papers 0337, National Bureau of Economic Research, Inc.
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    Cited by:

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    3. Walter Beckert, 2020. "A Note on Specification Testing in Some Structural Regression Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 82(3), pages 686-695, June.
    4. MacDonald, Ronald & Vieira, Flávio & Damasceno, Aderbal, 2010. "The Role of Institutions in Cross-Section Income and Panel Data Growth Models: A Deeper Investigation on the Weakness and Proliferation of Instruments," SIRE Discussion Papers 2010-50, Scottish Institute for Research in Economics (SIRE).
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    7. Ricardo Martin & Alex Segura-Ubiergo, 2005. "Fiscal Discipline and Social Spending in IMF-supported Programs," Public Economics 0504012, University Library of Munich, Germany.
    8. Tansel, Aysit & Keskin, Halil Ibrahim, 2017. "Education Effects on Days Hospitalized and Days Out of Work by Gender: Evidence from Turkey," MPRA Paper 83227, University Library of Munich, Germany.
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    113. Miluka, Juna & Carletto, Calogero & Davis, Benjamin & Zezza, Alberto, 2007. "The vanishing farms ? the impact of international migration on Albanian family farming," Policy Research Working Paper Series 4367, The World Bank.
    114. Marine Carrasco & Mohamed Doukali, 2022. "Testing overidentifying restrictions with many instruments and heteroscedasticity using regularised jackknife IV [Specification testing in models with many instruments]," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 71-97.
    115. Peter C. Reiss, 2011. "Structural Workshop Paper --Descriptive, Structural, and Experimental Empirical Methods in Marketing Research," Marketing Science, INFORMS, vol. 30(6), pages 950-964, November.
    116. Galvao, Antonio F. & Montes-Rojas, Gabriel & Song, Suyong, 2017. "Endogeneity bias modeling using observables," Economics Letters, Elsevier, vol. 152(C), pages 41-45.
    117. Jan Víšek, 2009. "Consistency of the instrumental weighted variables," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(3), pages 543-578, September.
    118. Martin Emil Jakobsen & Jonas Peters, 2022. "Distributional robustness of K-class estimators and the PULSE [The colonial origins of comparative development: An empirical investigation]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 404-432.
    119. Bhagat, Sanjai & Bolton, Brian & Lu, Jun, 2015. "Size, leverage, and risk-taking of financial institutions," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 520-537.
    120. Bhagat, Sanjai & Bolton, Brian, 2008. "Corporate governance and firm performance," Journal of Corporate Finance, Elsevier, vol. 14(3), pages 257-273, June.
    121. Yoonseok Lee & Ryo Okui, 2009. "A Specification Test for Instrumental Variables Regression with Many Instruments," Cowles Foundation Discussion Papers 1741, Cowles Foundation for Research in Economics, Yale University.
    122. Lloyd Blanchard & Bo Zhao & John Yinger, 2005. "Do Credit Market Barriers Exist for Minority and Women Entrepreneurs?," Center for Policy Research Working Papers 74, Center for Policy Research, Maxwell School, Syracuse University.
    123. Breznau, Nate, 2017. "Simultaneous Feedback Models with Macro-Comparative Cross-Sectional Data," OSF Preprints v4sxb, Center for Open Science.
    124. Patrik Guggenberger, 2006. "Finite-Sample Evidence Suggesting a Heavy Tail Problem of the Generalized Empirical Likelihood Estimator, accepted for publication, Econometric Reviews," UCLA Economics Online Papers 371, UCLA Department of Economics.
    125. Mikusheva, Anna, 2013. "Survey on statistical inferences in weakly-identified instrumental variable models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 29(1), pages 117-131.
    126. Canay, Ivan A., 2010. "Simultaneous selection and weighting of moments in GMM using a trapezoidal kernel," Journal of Econometrics, Elsevier, vol. 156(2), pages 284-303, June.
    127. Brian Bolton, 2014. "Audit committee performance: ownership vs.independence – Did SOX get it wrong?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 54(1), pages 83-112, March.
    128. Cameron McIntosh, 2014. "The presence of an error term does not preclude causal inference in regression: a comment on Krause (2012)," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(1), pages 243-250, January.
    129. Jondeau, Eric & Le Bihan, Hervé, 2008. "Examining bias in estimators of linear rational expectations models under misspecification," Journal of Econometrics, Elsevier, vol. 143(2), pages 375-395, April.
    130. Christian Durán, 2004. "Evaluación microeconométrica de las políticas públicas de empleo: aspectos metodológicos," Hacienda Pública Española / Review of Public Economics, IEF, vol. 170(3), pages 107-133, september.
    131. Emek Basker, 2007. "When Good Instruments Go Bad," Working Papers 0706, Department of Economics, University of Missouri.
    132. Pradeep Chintagunta & Tülin Erdem & Peter E. Rossi & Michel Wedel, 2006. "Structural Modeling in Marketing: Review and Assessment," Marketing Science, INFORMS, vol. 25(6), pages 604-616, 11-12.
    133. Krishna Chaitanya Vadlamannati & Arusha Cooray, 2015. "Do transparency initiatives work? Assessing the impact of the Special Data Dissemination Standard (SDDS) on data transparency," CAMA Working Papers 2015-24, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    134. Dawood Mamoon & S. Mansoob Murshed, 2017. "When Education Explains Strong Institutions: Trade Policy also Matters," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(3), pages 1179-1210, April.
    135. Hausman, Jerry, 2001. "Microeconometrics," Journal of Econometrics, Elsevier, vol. 100(1), pages 33-35, January.
    136. Fishback, Price V. & Horrace, William C. & Kantor, Shawn, 2006. "The impact of New Deal expenditures on mobility during the Great Depression," Explorations in Economic History, Elsevier, vol. 43(2), pages 179-222, April.
    137. Sean F. Reardon & Fatih Unlu & Pei Zhu & Howard S. Bloom, 2014. "Bias and Bias Correction in Multisite Instrumental Variables Analysis of Heterogeneous Mediator Effects," Journal of Educational and Behavioral Statistics, , vol. 39(1), pages 53-86, February.
    138. Hahn, Jinyong & Ham, John C. & Moon, Hyungsik Roger, 2011. "The Hausman test and weak instruments," Journal of Econometrics, Elsevier, vol. 160(2), pages 289-299, February.
    139. Jenni L Bettman & Mitch Kosev & Stephen J Sault, 2011. "Exploring the asset growth effect in the Australian equity market," Australian Journal of Management, Australian School of Business, vol. 36(2), pages 200-216, August.
    140. Peter Ebbes, 2007. "A non-technical guide to instrumental variables and regressor-error dependencies (in Russian)," Quantile, Quantile, issue 2, pages 3-20, March.
    141. Garry Phillips & Emma Iglesias, 2004. "The estimation of simultaneous equation models under conditional heteroscedasticity," Econometric Society 2004 Latin American Meetings 91, Econometric Society.
    142. Shaobo Jin & Fan Yang-Wallentin & Kenneth A. Bollen, 2021. "A unified model-implied instrumental variable approach for structural equation modeling with mixed variables," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 564-594, June.
    143. Yakup Asarkaya & Serkan Özcan, 2007. "Determinants of Capital Structure in Financial Institutions: The Case of Turkey," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, vol. 1(1), pages 91-109.
    144. Jinyong Hahn & Atsushi Inoue, 2002. "A Monte Carlo Comparison Of Various Asymptotic Approximations To The Distribution Of Instrumental Variables Estimators," Econometric Reviews, Taylor & Francis Journals, vol. 21(3), pages 309-336.
    145. Garry Phillips & Emma Iglesias, 2004. "Simultaneous Equations and Weak Instruments under Conditionally Heteroscedastic Disturbances," Econometric Society 2004 Far Eastern Meetings 567, Econometric Society.
    146. Justus Ochieng & Beatrice Knerr & George Owuor & Emily Ouma, 2016. "Commercialisation of Food Crops and Farm Productivity: Evidence from Smallholders in Central Africa," Agrekon, Taylor & Francis Journals, vol. 55(4), pages 458-482, October.
    147. Arusha Cooray & Nabamita Dutta & Sushanta Mallick, 2016. "Does female human capital formation matter for the income effect of remittances? Evidence from developing countries," Oxford Development Studies, Taylor & Francis Journals, vol. 44(4), pages 458-478, October.
    148. Divine Ikenwilo & Anthony Scott, 2007. "The effects of pay and job satisfaction on the labour supply of hospital consultants," Health Economics, John Wiley & Sons, Ltd., vol. 16(12), pages 1303-1318, December.
    149. Chang, Jinyuan & Guo, Bin & Yao, Qiwei, 2015. "High dimensional stochastic regression with latent factors, endogeneity and nonlinearity," Journal of Econometrics, Elsevier, vol. 189(2), pages 297-312.
    150. Zhenhong Huang & Chen Wang & Jianfeng Yao, 2023. "Assessing the strength of many instruments with the first-stage F and Cragg-Donald statistics," Papers 2302.14423, arXiv.org.
    151. Jinyong Hahn & Jerry Hausman, 2003. "Weak Instruments: Diagnosis and Cures in Empirical Econometrics," American Economic Review, American Economic Association, vol. 93(2), pages 118-125, May.

  22. Peter Christoffersen & Jinyong Hahn & Atsushi Inoue, 1999. "Testing, Comparing, and Combining Value at Risk Measures," Center for Financial Institutions Working Papers 99-44, Wharton School Center for Financial Institutions, University of Pennsylvania.

    Cited by:

    1. Parente, Paulo M.D.C. & Smith, Richard J., 2011. "Gel Methods For Nonsmooth Moment Indicators," Econometric Theory, Cambridge University Press, vol. 27(1), pages 74-113, February.
    2. Chen, Xiaohong & Hong, Han & Shum, Matthew, 2007. "Nonparametric likelihood ratio model selection tests between parametric likelihood and moment condition models," Journal of Econometrics, Elsevier, vol. 141(1), pages 109-140, November.
    3. Victor Chernozhukov & Iván Fernández-Val, 2011. "Inference for Extremal Conditional Quantile Models, with an Application to Market and Birthweight Risks," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(2), pages 559-589.
    4. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
    5. Shcherba, Alexandr, 2011. "Comparison of VaR estimation methods for different forecasting samples for Russian stocks," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 24(4), pages 58-70.
    6. Dany Rogers Silva & Karem Cristina de Sousa Ribeiro & Hsia Hua Sheng, 2011. "Trade credit profitability measurement: application in a wholesalerdistributor case," Brazilian Business Review, Fucape Business School, vol. 8(2), pages 22-41, April.
    7. Mauro Bernardi & Leopoldo Catania & Lea Petrella, 2014. "Are news important to predict large losses?," Papers 1410.6898, arXiv.org, revised Oct 2014.
    8. Kilic, Ekrem, 2006. "Violation duration as a better way of VaR model evaluation : evidence from Turkish market portfolio," MPRA Paper 5610, University Library of Munich, Germany.

  23. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1998. "Real-Time Multivariate Density Forecast Evaluation and Calibration: Monitoring the Risk of High-Frequency Returns on Foreign Exchange," New York University, Leonard N. Stern School Finance Department Working Paper Seires 98-079, New York University, Leonard N. Stern School of Business-.

    Cited by:

    1. Lopez, Jose A. & Saidenberg, Marc R., 2000. "Evaluating credit risk models," Journal of Banking & Finance, Elsevier, vol. 24(1-2), pages 151-165, January.
    2. Stefan Jaschke & Gerhard Stahl & Richard Stehle, 2007. "Value-at-risk forecasts under scrutiny—the German experience," Quantitative Finance, Taylor & Francis Journals, vol. 7(6), pages 621-636.

  24. Moshe Buchinsky & Jinyong Hahn, 1995. "Quantile Regression Model with Unknown Censoring Point," Cowles Foundation Discussion Papers 1096, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Fernández-Val, Iván & van Vuuren, Aico & Vella, Francis & Peracchi, Franco, 2022. "Selection and the Distribution of Female Hourly Wages in the U.S," IZA Discussion Papers 15028, Institute of Labor Economics (IZA).
    2. Bedassa Tadesse & Elias K. Shukralla, 2013. "The impact of foreign direct investment on horizontal export diversification: empirical evidence," Applied Economics, Taylor & Francis Journals, vol. 45(2), pages 141-159, January.
    3. Golan, Amos & Judge, George & Perloff, Jeffrey, 1997. "Estimation and inference with censored and ordered multinomial response data," Journal of Econometrics, Elsevier, vol. 79(1), pages 23-51, July.
    4. Iván Fernández‐Val & Aico van Vuuren & Francis Vella & Franco Peracchi, 2023. "Selection and the distribution of female real hourly wages in the United States," Quantitative Economics, Econometric Society, vol. 14(2), pages 571-607, May.
    5. Roger White & Bedassa Tadesse, 2011. "International Migration and Economic Integration," Books, Edward Elgar Publishing, number 14318.

  25. Jinyong Hahn & Andrew D. Foster, "undated". "A Consistent Semiparametric Estimator of the Consumer Surplus Distribution," Home Pages _077, University of Pennsylvania.

    Cited by:

    1. Hahn, Jinyong, 2001. "Consistent estimation of the random structural coefficient distribution from the linear simultaneous equations system," Economics Letters, Elsevier, vol. 73(2), pages 227-231, November.
    2. Sebastiaan Maes & Raghav Malhotra, 2023. "Robust Hicksian Welfare Analysis under Individual Heterogeneity," Papers 2303.01231, arXiv.org, revised Nov 2023.
    3. Maes, Sebastiaan & Malhotra, Raghav, 2024. "Robust Hicksian Welfare Analysis under Individual Heterogeneity," CRETA Online Discussion Paper Series 84, Centre for Research in Economic Theory and its Applications CRETA.
    4. McAleer, Michael & Medeiros, Marcelo C. & Slottje, Daniel, 2008. "A neural network demand system with heteroskedastic errors," Journal of Econometrics, Elsevier, vol. 147(2), pages 359-371, December.
    5. Gao, Z. & Pesaran, M. H., 2022. "Identification and Estimation of Categorical Random Coeficient Models," Cambridge Working Papers in Economics 2228, Faculty of Economics, University of Cambridge.
    6. Donald J. Brown & Rosa L. Matzkin, 1998. "Estimation of Nonparametric Functions in Simultaneous Equations Models, with an Application to Consumer Demand," Cowles Foundation Discussion Papers 1175, Cowles Foundation for Research in Economics, Yale University.

Articles

  1. Hahn, Jinyong & Hausman, Jerry & Kim, Jeonghwan, 2021. "A small sigma approach to certain problems in errors-in-variables models," Economics Letters, Elsevier, vol. 208(C).

    Cited by:

    1. Andrei Zeleneev & Kirill Evdokimov, 2023. "Simple estimation of semiparametric models with measurement errors," CeMMAP working papers 10/23, Institute for Fiscal Studies.
    2. Kirill S. Evdokimov & Andrei Zeleneev, 2023. "Simple Estimation of Semiparametric Models with Measurement Errors," Papers 2306.14311, arXiv.org, revised Mar 2024.
    3. Kirill Evdokimov & Andrei Zeleneev, 2024. "Simple estimation of semiparametric models with measurement errors," CeMMAP working papers 05/24, Institute for Fiscal Studies.

  2. Jinyong Hahn & Zhipeng Liao, 2021. "Bootstrap Standard Error Estimates and Inference," Econometrica, Econometric Society, vol. 89(4), pages 1963-1977, July.

    Cited by:

    1. Jiang, Liang & Phillips, Peter C.B. & Tao, Yubo & Zhang, Yichong, 2023. "Regression-adjusted estimation of quantile treatment effects under covariate-adaptive randomizations," Journal of Econometrics, Elsevier, vol. 234(2), pages 758-776.
    2. Koen Jochmans, 2023. "Bootstrap inference for fixed-effect models," French Stata Users' Group Meetings 2023 21, Stata Users Group.
    3. Wenjie Wang & Yichong Zhang, 2021. "Wild Bootstrap for Instrumental Variables Regressions with Weak and Few Clusters," Papers 2108.13707, arXiv.org, revised Jan 2024.
    4. Lu, Xun & Su, Liangjun, 2023. "Uniform inference in linear panel data models with two-dimensional heterogeneity," Journal of Econometrics, Elsevier, vol. 235(2), pages 694-719.
    5. Alexander Mayer & Dominik Wied, 2021. "Estimation and Inference in Factor Copula Models with Exogenous Covariates," Papers 2107.03366, arXiv.org, revised Dec 2022.
    6. Carlos Lamarche & Thomas Parker, 2022. "Wild Bootstrap Inference For Penalized Quantile Regression For Longitudinal Data," Working Papers 22003 Classification-C15,, University of Waterloo, Department of Economics.

  3. Jinyong Hahn & Jerry Hausman, 2021. "Problems with the Control Variable Approach in Achieving Unbiased Estimates in Nonlinear Models in the Presence of Many Instruments," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 39-58, December.

    Cited by:

    1. Yong Bao & Aman Ullah, 2021. "The Special Issue in Honor of Anirudh Lal Nagar: An Introduction," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 1-8, December.

  4. Hahn, Jinyong & Hausman, Jerry & Lustig, Josh, 2020. "Specification test on mixed logit models," Journal of Econometrics, Elsevier, vol. 219(1), pages 19-37.
    See citations under working paper version above.
  5. Hahn, Jinyong & Liao, Zhipeng & Ridder, Geert, 2018. "Nonparametric Two-Step Sieve M Estimation And Inference," Econometric Theory, Cambridge University Press, vol. 34(6), pages 1281-1324, December.

    Cited by:

    1. Bournakis, Ioannis & Tsionas, Mike G., 2023. "A Non-Parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax," MPRA Paper 118100, University Library of Munich, Germany.
    2. Malikov, Emir & Zhao, Shunan, 2022. "On the Estimation of Cross-Firm Productivity Spillovers with an Application to FDI," 2022 Allied Social Sciences Association (ASSA) Annual Meeting (Virtual), January 7-9, 2022 316529, Agricultural and Applied Economics Association.
    3. Jackson Bunting, 2022. "Continuous permanent unobserved heterogeneity in dynamic discrete choice models," Papers 2202.03960, arXiv.org, revised Feb 2024.
    4. Louise Laage, 2020. "A Correlated Random Coefficient Panel Model with Time-Varying Endogeneity," Papers 2003.09367, arXiv.org, revised Nov 2022.
    5. Minji Bang & Wayne Gao & Andrew Postlewaite & Holger Sieg, 2021. "Using Monotonicity Restrictions to Identify Models with Partially Latent Covariates," NBER Working Papers 28436, National Bureau of Economic Research, Inc.
    6. Ganesh Karapakula, 2023. "Stable Probability Weighting: Large-Sample and Finite-Sample Estimation and Inference Methods for Heterogeneous Causal Effects of Multivalued Treatments Under Limited Overlap," Papers 2301.05703, arXiv.org, revised Jan 2023.
    7. Elia Lapenta, 2022. "A Bootstrap Specification Test for Semiparametric Models with Generated Regressors," Papers 2212.11112, arXiv.org, revised Oct 2023.
    8. Ying-Ying Lee, 2018. "Partial Mean Processes with Generated Regressors: Continuous Treatment Effects and Nonseparable Models," Papers 1811.00157, arXiv.org.
    9. Botosaru, Irene, 2020. "Nonparametric analysis of a duration model with stochastic unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 217(1), pages 112-139.
    10. Costanza Naguib & Patrick Gagliardini, 2023. "A Semi-nonparametric Copula Model for Earnings Mobility," Diskussionsschriften dp2302, Universitaet Bern, Departement Volkswirtschaft.
    11. Sungwon Lee, 2020. "Nonparametric Identification and Estimation of Panel Quantile Models with Sample Selection," Working Papers 2012, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).

  6. Graham, Bryan S. & Hahn, Jinyong & Poirier, Alexandre & Powell, James L., 2018. "A quantile correlated random coefficients panel data model," Journal of Econometrics, Elsevier, vol. 206(2), pages 305-335.
    See citations under working paper version above.
  7. Hahn, Jinyong & Ridder, Geert, 2017. "Instrumental variable estimation of nonlinear models with nonclassical measurement error using control variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 238-250.

    Cited by:

    1. Hahn, Jinyong & Ridder, Geert, 2019. "Three-stage semi-parametric inference: Control variables and differentiability," Journal of Econometrics, Elsevier, vol. 211(1), pages 262-293.
    2. Diaz-Serrano, Luis & Nilsson, William, 2017. "The Reliability of Students' Earnings Expectations," IZA Discussion Papers 10700, Institute of Labor Economics (IZA).

  8. Jinyong Hahn & Ruoyao Shi, 2017. "Synthetic Control and Inference," Econometrics, MDPI, vol. 5(4), pages 1-12, November.
    See citations under working paper version above.
  9. Jinyong Hahn & Hyungsik Roger Moon & Connan Snider, 2017. "LM Test of Neglected Correlated Random Effects and Its Application," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(3), pages 359-370, July.

    Cited by:

    1. Xiao, Ruli, 2018. "Identification and estimation of incomplete information games with multiple equilibria," Journal of Econometrics, Elsevier, vol. 203(2), pages 328-343.

  10. Manuel Arellano & Jinyong Hahn, 2016. "A likelihood-Based Approximate Solution to the Incidental Parameter Problem in Dynamic Nonlinear Models with Multiple Effects," Global Economic Review, Taylor & Francis Journals, vol. 45(3), pages 251-274, July.
    See citations under working paper version above.
  11. Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn & Zhipeng Liao, 2014. "Asymptotic Efficiency of Semiparametric Two-step GMM," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(3), pages 919-943.
    See citations under working paper version above.
  12. Victor Chernozhukov & Iván Fernández‐Val & Jinyong Hahn & Whitney Newey, 2013. "Average and Quantile Effects in Nonseparable Panel Models," Econometrica, Econometric Society, vol. 81(2), pages 535-580, March.
    See citations under working paper version above.
  13. Jinyong Hahn & Geert Ridder, 2013. "Asymptotic Variance of Semiparametric Estimators With Generated Regressors," Econometrica, Econometric Society, vol. 81(1), pages 315-340, January.
    See citations under working paper version above.
  14. Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn, 2012. "A Practical Asymptotic Variance Estimator for Two-Step Semiparametric Estimators," The Review of Economics and Statistics, MIT Press, vol. 94(2), pages 481-498, May.
    See citations under working paper version above.
  15. Hahn, Jinyong & Kuersteiner, Guido, 2011. "Bias Reduction For Dynamic Nonlinear Panel Models With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 27(6), pages 1152-1191, December.

    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. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2022. "Discretizing Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 90(2), pages 625-643, March.
    3. Vivian Norambuena, 2015. "Sovereign Debt Default: Are Countries Trapped by Their Own Default History?," Working Papers wp416, University of Chile, Department of Economics.
    4. Ivan Fernandez-Val & Martin Weidner, 2018. "Fixed effect estimation of large T panel data models," CeMMAP working papers CWP22/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile and probability curves without crossing," CeMMAP working papers CWP10/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Liangjun Su & Sainan Jin & Yonghui Zhang, 2014. "Specification Test for Panel Data Models with Interactive Fixed Effects," Working Papers 08-2014, Singapore Management University, School of Economics.
    7. Belkhir, Mohamed & Naceur, Sami Ben & Candelon, Bertrand & Wijnandts, Jean-Charles, 2022. "Macroprudential policies, economic growth and banking crises," Emerging Markets Review, Elsevier, vol. 53(C).
    8. Dzemski, Andreas, 2017. "An empirical model of dyadic link formation in a network with unobserved heterogeneity," Working Papers in Economics 698, University of Gothenburg, Department of Economics, revised Apr 2018.
    9. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    10. Vira Semenova & Matt Goldman & Victor Chernozhukov & Matt Taddy, 2023. "Inference on heterogeneous treatment effects in high‐dimensional dynamic panels under weak dependence," Quantitative Economics, Econometric Society, vol. 14(2), pages 471-510, May.
    11. Lee, Yoonseok & Phillips, Peter C.B., 2015. "Model selection in the presence of incidental parameters," Journal of Econometrics, Elsevier, vol. 188(2), pages 474-489.
    12. DHAENE, Geert & JOCHMANS, Koen, 2010. "Split-panel jackknife estimation of fixed-effect models," LIDAM Discussion Papers CORE 2010003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Gonçalves, Sílvia & Kaffo, Maximilien, 2015. "Bootstrap inference for linear dynamic panel data models with individual fixed effects," Journal of Econometrics, Elsevier, vol. 186(2), pages 407-426.
    14. Giuseppe Cavaliere & S'ilvia Gonc{c}alves & Morten {O}rregaard Nielsen & Edoardo Zanelli, 2022. "Bootstrap inference in the presence of bias," Papers 2208.02028, arXiv.org, revised Nov 2023.
    15. Hyungsik Roger Moon & Martin Weidner, 2013. "Dynamic linear panel regression models with interactive fixed effects," CeMMAP working papers CWP63/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Carro, Jesús M. & Traferri, Alejandra, 2011. "State dependence and heterogeneity in health using a bias corrected fixed effects estimator," UC3M Working papers. Economics we1118, Universidad Carlos III de Madrid. Departamento de Economía.
    17. Laura Hospido, 2007. "Modelling Heterogeneity and Dynamics in the Volatility of Individual Wages," Working Papers wp2007_0717, CEMFI.
    18. Sun, Yixiao & Kim, Min Seong, 2009. "k-step Bootstrap Bias Correction for Fixed Effects Estimators in Nonlinear Panel Models," University of California at San Diego, Economics Working Paper Series qt9gn6n5mr, Department of Economics, UC San Diego.
    19. Manuel Arellano & Stéphane Bonhomme, 2007. "Robust priors in nonlinear panel data models," CeMMAP working papers CWP07/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    20. Pesaran, Hashem & Chudik, Alexander, 2013. "Common Correlated Effects Estimation of Heterogeneous Dynamic Panel Data Models with Weakly Exogenous Regressors," Cambridge Working Papers in Economics 1317, Faculty of Economics, University of Cambridge.
    21. Mayer, Alexander, 2022. "On the local power of some tests of strict exogeneity in linear fixed effects models," Econometrics and Statistics, Elsevier, vol. 24(C), pages 49-74.
    22. Jess Benhabib & Alejandro Corvalen & Mark M. Spiegel, 2011. "Reestablishing the income-democracy nexus," Working Paper Series 2011-09, Federal Reserve Bank of San Francisco.
    23. Su, Liangjun & Ju, Gaosheng, 2018. "Identifying latent grouped patterns in panel data models with interactive fixed effects," Journal of Econometrics, Elsevier, vol. 206(2), pages 554-573.
    24. Manuel Arellano & Stéphane Bonhomme & Micole De Vera & Laura Hospido & Siqi Wei, 2021. "Income Risk Inequality: Evidence from Spanish Administrative Records," Working Papers 2136, Banco de España.
    25. Hyungsik Roger Moon & Matthew Shum & Martin Weidner, 2012. "Estimation of random coefficients logit demand models with interactive fixed effects," CeMMAP working papers CWP08/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    26. Andersen, Torben G. & Fusari, Nicola & Todorov, Viktor & Varneskov, Rasmus T., 2019. "Unified inference for nonlinear factor models from panels with fixed and large time span," Journal of Econometrics, Elsevier, vol. 212(1), pages 4-25.
    27. Lucchetti, Riccardo & Pigini, Claudia, 2017. "DPB: Dynamic Panel Binary Data Models in gretl," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i08).
    28. Geert Dhaene & Koen Jochmans, 2016. "Likelihood Inference in an Autoregression with Fixed Effects," Post-Print hal-03391995, HAL.
    29. Wang, Fa, 2017. "Maximum likelihood estimation and inference for high dimensional nonlinear factor models with application to factor-augmented regressions," MPRA Paper 93484, University Library of Munich, Germany, revised 19 May 2019.
    30. Mingyang Li & Linlin Niu & Andrew Pua, 2020. "Market Pricing of Fundamentals at the Shanghai Stock Exchange: Evidence from a Dividend Discount Model with Adaptive Expectations," Working Papers 2020-12-30, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    31. Ji-Liang Shiu & Yingyao Hu, 2010. "Identification and Estimation of Nonlinear Dynamic Panel Data Models with Unobserved Covariates," Economics Working Paper Archive 557, The Johns Hopkins University,Department of Economics.
    32. Stefan Hochguertel & Henry Ohlsson, 2011. "Wealth mobility and dynamics over entire individual working life cycles," BCL working papers 56, Central Bank of Luxembourg.
    33. Schumann, Martin & Severini, Thomas A. & Tripathi, Gautam, 2023. "The role of score and information bias in panel data likelihoods," Journal of Econometrics, Elsevier, vol. 235(2), pages 1215-1238.
    34. Francesco Bartolucci & Valentina Nigro & Claudia Pigini, 2018. "Testing for state dependence in binary panel data with individual covariates by a modified quadratic exponential model," Econometric Reviews, Taylor & Francis Journals, vol. 37(1), pages 61-88, January.
    35. Ivan Fernandez-Val & Wayne Yuan Gao & Yuan Liao & Francis Vella, 2022. "Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes," Papers 2202.04154, arXiv.org, revised Jan 2023.
    36. Liangjun Su & Zhentao Shi & Peter C.B. Phillips, 2014. "Identifying Latent Structures in Panel Data," Cowles Foundation Discussion Papers 1965, Cowles Foundation for Research in Economics, Yale University.
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    2. Stefan Schmid & Felix Roedder, 2022. "Much ado about diversity? The perpetuation of old elites on corporate boards," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(8), pages 3263-3285, December.
    3. Wang, Yun & Zhang, Yonghui & Zhou, Qiankun, 2016. "A Stein-like estimator for linear panel data models," Economics Letters, Elsevier, vol. 141(C), pages 156-161.

  18. Patrick Bajari & Jinyong Hahn & Han Hong & Geert Ridder, 2011. "A Note On Semiparametric Estimation Of Finite Mixtures Of Discrete Choice Models With Application To Game Theoretic Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(3), pages 807-824, August.

    Cited by:

    1. Arthur Lewbel & Xun Tang, 2012. "Identification and Estimation of Games with Incomplete Information Using Excluded Regressors," Boston College Working Papers in Economics 808, Boston College Department of Economics, revised 05 Mar 2013.
    2. Stéphane Bonhomme & Koen Jochmans & Jean-Marc Robin, 2017. "Nonparametric estimation of non-exchangeable latent-variable models," SciencePo Working papers Main hal-03264006, HAL.
    3. Xiao, Ruli, 2018. "Identification and estimation of incomplete information games with multiple equilibria," Journal of Econometrics, Elsevier, vol. 203(2), pages 328-343.
    4. Paul L. E. Grieco, 2014. "Discrete games with flexible information structures: an application to local grocery markets," RAND Journal of Economics, RAND Corporation, vol. 45(2), pages 303-340, June.
    5. Lorenzo Magnolfi & Camilla Roncoroni, 2023. "Estimation of Discrete Games with Weak Assumptions on Information," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(4), pages 2006-2041.
    6. Ruli Xiao, 2015. "Identification and Estimation of Incomplete Information Games with Multiple Equilibria," CAEPR Working Papers 2015-007, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    7. Shuyang Sheng, 2020. "A Structural Econometric Analysis of Network Formation Games Through Subnetworks," Econometrica, Econometric Society, vol. 88(5), pages 1829-1858, September.
    8. Bryan S. Graham & Jinyong Hahn & Alexandre Poirier & James L. Powell, 2015. "Quantile Regression with Panel Data," NBER Working Papers 21034, National Bureau of Economic Research, Inc.
    9. Áureo de Paula, 2013. "Econometric Analysis of Games with Multiple Equilibria," Annual Review of Economics, Annual Reviews, vol. 5(1), pages 107-131, May.
    10. Xiaotian Zhu & David R. Hunter, 2019. "Clustering via finite nonparametric ICA mixture models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(1), pages 65-87, March.
    11. Kline, Brendan, 2015. "Identification of complete information games," Journal of Econometrics, Elsevier, vol. 189(1), pages 117-131.
    12. Jun, Sung Jae & Pinkse, Joris, 2020. "Counterfactual prediction in complete information games: Point prediction under partial identification," Journal of Econometrics, Elsevier, vol. 216(2), pages 394-429.
    13. Marc HENRY & Ismael MOURIFIÉ, 2013. "Nonparametric Sharp Bounds For Payoffs In 2 × 2 Games," Working Papers tecipa-500, University of Toronto, Department of Economics.
    14. Marc Henry & Romuald Méango & Maurice Queyranne, 2012. "Combinatorial Bootstrap Inference IN in Prtially Identified Incomplete Structural Models," CIRJE F-Series CIRJE-F-837, CIRJE, Faculty of Economics, University of Tokyo.

  19. Hahn, Jinyong & Ham, John C. & Moon, Hyungsik Roger, 2011. "The Hausman test and weak instruments," Journal of Econometrics, Elsevier, vol. 160(2), pages 289-299, February.

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    1. Loban, Lidia & Sarto, José Luis & Vicente, Luis, 2021. "Determinants of non-compliant equity funds with EU portfolio concentration limits," Journal of Multinational Financial Management, Elsevier, vol. 62(C).
    2. Doko Tchatoka, Firmin, 2012. "On the validity of Durbin-Wu-Hausman tests for assessing partial exogeneity hypotheses with possibly weak instruments," Working Papers 15061, University of Tasmania, Tasmanian School of Business and Economics, revised 06 Jul 2012.
    3. Tetsuya Kaji, 2019. "Theory of Weak Identification in Semiparametric Models," Papers 1908.10478, arXiv.org, revised Aug 2020.
    4. Ruprecht, Benedikt & Entrop, Oliver & Kick, Thomas & Wilkens, Marco, 2013. "Market Timing, Maturity Mismatch, and Risk Management: Evidence from the Banking Industry," VfS Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79733, Verein für Socialpolitik / German Economic Association.
    5. Alekh Gour & Shikha Aggarwal & Subodha Kumar, 2022. "Lending ears to unheard voices: An empirical analysis of user‐generated content on social media," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2457-2476, June.
    6. James Hansen, 2011. "Does Equity Mispricing Influence Household and Firm Decisions?," RBA Research Discussion Papers rdp2011-06, Reserve Bank of Australia.
    7. Yongming Zhu & Xiaoyu Zhou & Junjie Li & Fan Wang, 2022. "Technological Innovation, Fiscal Decentralization, Green Development Efficiency: Based on Spatial Effect and Moderating Effect," Sustainability, MDPI, vol. 14(7), pages 1-16, April.
    8. Or Levkovich & Jan Rouwendal & Jos van Ommeren, 2017. "The impact of highways on population redistribution: The role of land development restrictions," Tinbergen Institute Discussion Papers 17-109/VIII, Tinbergen Institute.
    9. Seri, Paolo & Zanfei, Antonello, 2013. "The co-evolution of ICT, skills and organization in public administrations: Evidence from new European country-level data," Structural Change and Economic Dynamics, Elsevier, vol. 27(C), pages 160-176.
    10. Ephraim Kwashie Thompson & Changki Kim, 2020. "Post-M&A Performance and Failure: Implications of Time until Deal Completion," Sustainability, MDPI, vol. 12(7), pages 1-31, April.
    11. Kinclová Lenka, 2015. "Legitimacy of the “Humanitarian Military Intervention”: An Empirical Assessment," Peace Economics, Peace Science, and Public Policy, De Gruyter, vol. 21(1), pages 111-152, January.
    12. Doko Tchatoka, Firmin, 2012. "Testing for partial exogeneity with weak identification," Working Papers 14565, University of Tasmania, Tasmanian School of Business and Economics, revised 31 May 2012.
    13. Woutersen, Tiemen & Hausman, Jerry A., 2019. "Increasing the power of specification tests," Journal of Econometrics, Elsevier, vol. 211(1), pages 166-175.
    14. Murray Michael P., 2017. "Linear Model IV Estimation When Instruments Are Many or Weak," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    15. Bertille Antoine & Eric Renault, 2017. "On the relevance of weaker instruments," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 928-945, October.
    16. Goetzke, Frank & Vance, Colin, 2021. "An increasing gasoline price elasticity in the United States?," Energy Economics, Elsevier, vol. 95(C).
    17. Escobal, Javier A. & Cavero, Denice, 2012. "Transaction Costs, Institutional Arrangements and Inequality Outcomes: Potato Marketing by Small Producers in Rural Peru," World Development, Elsevier, vol. 40(2), pages 329-341.
    18. Inoue, Atsushi & Rossi, Barbara, 2011. "Testing for weak identification in possibly nonlinear models," Journal of Econometrics, Elsevier, vol. 161(2), pages 246-261, April.
    19. Daria Ciriaci & Sandro Montresor & Daniela Palma, 2013. "Do KIBS make manufacturing more innovative? An empirical investigation for four European countries," JRC Working Papers on Corporate R&D and Innovation 2013-04, Joint Research Centre.
    20. Laura Di Giorgio & Massimo Filippini & Giuliano Masiero, 2014. "The relationship between costs and quality in nonprofit nursing homes," IdEP Economic Papers 1402, USI Università della Svizzera italiana.
    21. Christian Danne, 2015. "Regional Integration and the Rule of Law," FIW Working Paper series 157, FIW.
    22. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
    23. Kiviet, Jan F. & Pleus, Milan, 2017. "The performance of tests on endogeneity of subsets of explanatory variables scanned by simulation," Econometrics and Statistics, Elsevier, vol. 2(C), pages 1-21.
    24. Liping Zhu & Rui Shi & Lincheng Mi & Pu Liu & Guofeng Wang, 2022. "Spatial Distribution and Convergence of Agricultural Green Total Factor Productivity in China," IJERPH, MDPI, vol. 19(14), pages 1-16, July.
    25. L. Di Giorgio & M. Filippini & G. Masiero, 2016. "Is higher nursing home quality more costly?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(8), pages 1011-1026, November.
    26. Qusai Mohammad Qasim Alabed & Fathin Faizah Said & Zulkefly Abdul Karim & Mohd Azlan Shah Zaidi & Mohammed Daher Alshammary, 2021. "Energy–Growth Nexus in the MENA Region: A Dynamic Panel Threshold Estimation," Sustainability, MDPI, vol. 13(22), pages 1-18, November.
    27. Jonathan Chapman, 2019. "The contribution of infrastructure investment to Britain's urban mortality decline, 1861–1900," Economic History Review, Economic History Society, vol. 72(1), pages 233-259, February.
    28. Reda Cherif & Fuad Hasanov & Lichen Wang, 2018. "Sharp Instrument: A Stab at Identifying the Causes of Economic Growth," IMF Working Papers 2018/117, International Monetary Fund.
    29. Samuel Bazzi & Michael A. Clemens, 2013. "Blunt Instruments: Avoiding Common Pitfalls in Identifying the Causes of Economic Growth," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(2), pages 152-186, April.
    30. Deng, Xiangzheng & Gibson, John, 2021. "Trade-Offs between Ecosystem Services Provided By Natural Capital and the Predominant Land Use and Land Cover Changes in China," 2021 Conference, August 17-31, 2021, Virtual 315187, International Association of Agricultural Economists.
    31. Li, Yan & Lyons, Bruce, 2012. "Market structure, regulation and the speed of mobile network penetration," International Journal of Industrial Organization, Elsevier, vol. 30(6), pages 697-707.
    32. Tuğba KAYHAN & Temur KAYHAN & Engin YARBAŞI, 2019. "Profit management in the case of financial distress and global volatile market behaviour: Evidence from Borsa Istanbul Stock Exchange," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(620), A), pages 179-192, Autumn.

  20. Jinyong Hahn & Geert Ridder, 2011. "Conditional Moment Restrictions and Triangular Simultaneous Equations," The Review of Economics and Statistics, MIT Press, vol. 93(2), pages 683-689, May.

    Cited by:

    1. Santiago Pereda Fernández, 2019. "Identification and estimation of triangular models with a binary treatment," Temi di discussione (Economic working papers) 1210, Bank of Italy, Economic Research and International Relations Area.
    2. Kasy, Maximilian, "undated". "Instrumental variables with unrestricted heterogeneity and continuous treatment - DON'T CITE! SEE ERRATUM BELOW," Working Paper 33257, Harvard University OpenScholar.
    3. Lee, Jinhyun, 2013. "A Consistent Nonparametric Bootstrap Test of Exogeneity," SIRE Discussion Papers 2013-95, Scottish Institute for Research in Economics (SIRE).
    4. Halbert White & Karim Chalak, 2013. "Identification and Identification Failure for Treatment Effects Using Structural Systems," Econometric Reviews, Taylor & Francis Journals, vol. 32(3), pages 273-317, November.
    5. Pengzhou Wu & Kenji Fukumizu, 2021. "Towards Principled Causal Effect Estimation by Deep Identifiable Models," Papers 2109.15062, arXiv.org, revised Nov 2021.
    6. Hahn, Jinyong & Ridder, Geert, 2017. "Instrumental variable estimation of nonlinear models with nonclassical measurement error using control variables," Journal of Econometrics, Elsevier, vol. 200(2), pages 238-250.
    7. Alyssa Carlson, 2021. "Relaxing Conditional Independence in an Endogenous Binary Response Model," Working Papers 2113, Department of Economics, University of Missouri.
    8. Schennach, Susanne & White, Halbert & Chalak, Karim, 2012. "Local indirect least squares and average marginal effects in nonseparable structural systems," Journal of Econometrics, Elsevier, vol. 166(2), pages 282-302.
    9. Hahn, Jinyong & Ridder, Geert, 2019. "Three-stage semi-parametric inference: Control variables and differentiability," Journal of Econometrics, Elsevier, vol. 211(1), pages 262-293.
    10. Bora Kim, 2020. "Analysis of Randomized Experiments with Network Interference and Noncompliance," Papers 2012.13710, arXiv.org.
    11. Lee, Jinhyun, 2013. "Sharp Bounds on Heterogeneous Individual Treatment Responses," SIRE Discussion Papers 2013-89, Scottish Institute for Research in Economics (SIRE).
    12. Maximilian Kasy, 2014. "Instrumental Variables with Unrestricted Heterogeneity and Continuous Treatment," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(4), pages 1614-1636.
    13. Lu, Xun & White, Halbert, 2014. "Testing for separability in structural equations," Journal of Econometrics, Elsevier, vol. 182(1), pages 14-26.

  21. Buchinsky, Moshe & Hahn, Jinyong & Kim, Kyoo il, 2010. "Semiparametric information bound of dynamic discrete choice models," Economics Letters, Elsevier, vol. 108(2), pages 109-112, August.

    Cited by:

    1. Christopher Dobronyi & Jiaying Gu & Kyoo il Kim, 2021. "Identification of Dynamic Panel Logit Models with Fixed Effects," Papers 2104.04590, arXiv.org, revised Apr 2021.
    2. Kitazawa, Yoshitsugu, 2022. "Transformations and moment conditions for dynamic fixed effects logit models," Journal of Econometrics, Elsevier, vol. 229(2), pages 350-362.
    3. Yoshitsugu Kitazawa, 2013. "Exploration of dynamic fixed effects logit models from a traditional angle," Discussion Papers 60, Kyushu Sangyo University, Faculty of Economics.

  22. Hahn, Jinyong & Moon, Hyungsik Roger, 2010. "Panel Data Models With Finite Number Of Multiple Equilibria," Econometric Theory, Cambridge University Press, vol. 26(3), pages 863-881, June.

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    1. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2022. "Discretizing Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 90(2), pages 625-643, March.
    2. Xiaorong Yang & Jia Chen & Degui Li & Runze Li, 2023. "Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure," Papers 2303.13218, arXiv.org.
    3. Stéphane Bonhomme & Koen Jochmans & Jean-Marc Robin, 2017. "Nonparametric estimation of non-exchangeable latent-variable models," SciencePo Working papers Main hal-03264006, HAL.
    4. Ivan Fernandez-Val & Martin Weidner, 2018. "Fixed effect estimation of large T panel data models," CeMMAP working papers CWP22/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Liu, Yanbo & Phillips, Peter C. B. & Yu, Jun, 2022. "A Panel Clustering Approach to Analyzing Bubble Behavior," Economics and Statistics Working Papers 1-2022, Singapore Management University, School of Economics.
    6. Leng, Xuan & Chen, Heng & Wang, Wendun, 2023. "Multi-dimensional latent group structures with heterogeneous distributions," Journal of Econometrics, Elsevier, vol. 233(1), pages 1-21.
    7. Mammen, Enno & Wilke, Ralf A. & Zapp, Kristina Maria, 2022. "Estimation of group structures in panel models with individual fixed effects," ZEW Discussion Papers 22-023, ZEW - Leibniz Centre for European Economic Research.
    8. Victor Aguirregabiria & Pedro Mira, 2013. "Identification of Games of Incomplete Information with Multiple Equilibria and Common Unobserved Heterogeneity," Working Papers tecipa-474, University of Toronto, Department of Economics.
    9. Stéphane Bonhomme & Thibaut Lamadon & Elena Manresa, 2017. "Discretizing unobserved heterogeneity," IFS Working Papers W17/03, Institute for Fiscal Studies.
    10. Stéphane Bonhomme, 2021. "Selection on Welfare Gains: Experimental Evidence from Electricity Plan Choice," Working Papers 2021-15, Becker Friedman Institute for Research In Economics.
    11. Ivan Fernandez-Val & Martin Weidner, 2017. "Fixed effect estimation of large T panel data models," CeMMAP working papers 42/17, Institute for Fiscal Studies.
    12. Dong Hwan Oh & Andrew J. Patton, 2021. "Dynamic Factor Copula Models with Estimated Cluster Assignments," Finance and Economics Discussion Series 2021-029r1, Board of Governors of the Federal Reserve System (U.S.), revised 06 May 2022.
    13. Pigini, Claudia & Pionati, Alessandro & Valentini, Francesco, 2023. "Specification testing with grouped fixed effects," MPRA Paper 117821, University Library of Munich, Germany.
    14. Mehrabani, Ali, 2023. "Estimation and identification of latent group structures in panel data," Journal of Econometrics, Elsevier, vol. 235(2), pages 1464-1482.
    15. Dzemski, Andreas & Okui, Ryo, 2018. "Confidence Set for Group Membership," Working Papers in Economics 727, University of Gothenburg, Department of Economics.
    16. Ryo Okui & Wendun Wang, 2018. "Heterogeneous structural breaks in panel data models," Papers 1801.04672, arXiv.org, revised Nov 2018.
    17. Dzemski, Andreas & Okui, Ryo, 2020. "Convergence rate of estimators of clustered panel models with misclassication," Working Papers in Economics 790, University of Gothenburg, Department of Economics.
    18. Áureo de Paula, 2013. "Econometric Analysis of Games with Multiple Equilibria," Annual Review of Economics, Annual Reviews, vol. 5(1), pages 107-131, May.
    19. Lumsdaine, Robin L. & Okui, Ryo & Wang, Wendun, 2023. "Estimation of panel group structure models with structural breaks in group memberships and coefficients," Journal of Econometrics, Elsevier, vol. 233(1), pages 45-65.
    20. Thomas Wiemann, 2023. "Optimal Categorical Instrumental Variables," Papers 2311.17021, arXiv.org.
    21. Boyuan Zhang, 2022. "Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models," Papers 2211.16714, arXiv.org, revised Oct 2023.
    22. Liu, Ruiqi & Shang, Zuofeng & Zhang, Yonghui & Zhou, Qiankun, 2020. "Identification and estimation in panel models with overspecified number of groups," Journal of Econometrics, Elsevier, vol. 215(2), pages 574-590.
    23. Denis Chetverikov & Elena Manresa, 2022. "Spectral and post-spectral estimators for grouped panel data models," Papers 2212.13324, arXiv.org, revised Dec 2022.
    24. Stephane Bonhomme, 2021. "Teams: Heterogeneity, Sorting, and Complementarity," Papers 2102.01802, arXiv.org.
    25. Eric Auerbach, 2019. "Identification and Estimation of a Partially Linear Regression Model using Network Data," Papers 1903.09679, arXiv.org, revised Jun 2021.
    26. Stéphane Bonhomme & Elena Manresa, 2012. "Grouped Patterns of Heterogeneity in Panel Data," Working Papers wp2012_1208, CEMFI.
    27. Su, Liangjun & Wang, Wuyi & Xu, Xingbai, 2023. "Identifying latent group structures in spatial dynamic panels," Journal of Econometrics, Elsevier, vol. 235(2), pages 1955-1980.
    28. Andreas Dzemski & Ryo Okui, 2017. "Confidence set for group membership," Papers 1801.00332, arXiv.org, revised Nov 2023.

  23. Hahn, Jinyong, 2010. "Bounds on ATE with discrete outcomes," Economics Letters, Elsevier, vol. 109(1), pages 24-27, October.

    Cited by:

    1. Chen, Xuan & Flores, Carlos A. & Flores-Lagunes, Alfonso, 2017. "Going beyond LATE: Bounding Average Treatment Effects of Job Corps Training," GLO Discussion Paper Series 93, Global Labor Organization (GLO).
    2. Kitagawa, Toru, 2021. "The identification region of the potential outcome distributions under instrument independence," Journal of Econometrics, Elsevier, vol. 225(2), pages 231-253.

  24. Hahn, Jinyong & Kuersteiner, Guido, 2010. "Stationarity and mixing properties of the dynamic Tobit model," Economics Letters, Elsevier, vol. 107(2), pages 105-111, May.

    Cited by:

    1. Daniel Ordoñez-Callamand & Juan D. Hernandez-Leal & Mauricio Villamizar-Villegas, 2017. "When Multiple Objectives Meet Multiple Instruments: Identifying Simultaneous Monetary Shocks," Borradores de Economia 997, Banco de la Republica de Colombia.
    2. DHAENE, Geert & JOCHMANS, Koen, 2010. "Split-panel jackknife estimation of fixed-effect models," LIDAM Discussion Papers CORE 2010003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Song, Shijia & Tian, Fei & Li, Handong, 2021. "An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution," Journal of Asian Economics, Elsevier, vol. 74(C).
    4. Daniele Massacci, 2017. "Tail Risk Dynamics in Stock Returns: Links to the Macroeconomy and Global Markets Connectedness," Management Science, INFORMS, vol. 63(9), pages 3072-3089, September.
    5. Michel, Jon & de Jong, Robert M., 2018. "Mixing properties of the dynamic Tobit model with mixing errors," Economics Letters, Elsevier, vol. 162(C), pages 112-115.
    6. Genya Kobayashi & Hideo Kozumi, 2012. "Bayesian analysis of quantile regression for censored dynamic panel data," Computational Statistics, Springer, vol. 27(2), pages 359-380, June.
    7. Anna Bykhovskaya & James A. Duffy, 2022. "The Local to Unity Dynamic Tobit Model," Papers 2210.02599, arXiv.org, revised Feb 2023.

  25. Hirano, Keisuke & Hahn, Jinyong, 2010. "Design of randomized experiments to measure social interaction effects," Economics Letters, Elsevier, vol. 106(1), pages 51-53, January.

    Cited by:

    1. Steven N. Durlauf & Yannis M. Ioannides, 2009. "Social Interactions," Discussion Papers Series, Department of Economics, Tufts University 0739, Department of Economics, Tufts University.
    2. Dario Tortarolo & Guillermo Cruces & Gonzalo Vazquez-Bare, 2023. "Design of partial population experiments with an application to spillovers in tax compliance," IFS Working Papers W23/17, Institute for Fiscal Studies.
    3. Sarah Baird & Aislinn Bohren & Berk Ozler & Craig McIntosh, 2014. "Designing Experiments to Measure Spillover Effects," Working Papers 2014-11, The George Washington University, Institute for International Economic Policy.
    4. Angelucci,M. & Di Maro,Vincenzo, 2015. "Program evaluation and spillover effects," Policy Research Working Paper Series 7243, The World Bank.
    5. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
    6. Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2017. "Optimal Design of Experiments in the Presence of Interference*, Second Version," PIER Working Paper Archive 16-025, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 30 Nov 2017.
    7. Braun, Martin & Verdier, Valentin, 2023. "Estimation of spillover effects with matched data or longitudinal network data," Journal of Econometrics, Elsevier, vol. 233(2), pages 689-714.
    8. Sarah Baird & Aislinn Bohren & Craig McIntosh & Berk Ozler, 2015. "Designing Experiments to Measure Spillover Effects, Second Version," PIER Working Paper Archive 15-021, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Jun 2015.
    9. Michael P. Leung, 2020. "Treatment and Spillover Effects Under Network Interference," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 368-380, May.

  26. Graham, Bryan S. & Hahn, Jinyong & Powell, James L., 2009. "The incidental parameter problem in a non-differentiable panel data model," Economics Letters, Elsevier, vol. 105(2), pages 181-182, November.

    Cited by:

    1. Kato, Kengo & F. Galvao, Antonio & Montes-Rojas, Gabriel V., 2012. "Asymptotics for panel quantile regression models with individual effects," Journal of Econometrics, Elsevier, vol. 170(1), pages 76-91.
    2. Adam Rosen, 2009. "Set identification via quantile restrictions in short panels," CeMMAP working papers CWP26/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Pedro J. Hernández, 2020. "Reassessing the link between firm size and exports," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 10(2), pages 207-223, June.
    4. Dolado, Juan J & Chen, Liang & Gonzalo, Jesus, 2018. "Quantile Factor Models," CEPR Discussion Papers 12716, C.E.P.R. Discussion Papers.
    5. Victor Chernozhukov & Iv'an Fern'andez-Val & Martin Weidner, 2018. "Network and Panel Quantile Effects Via Distribution Regression," Papers 1803.08154, arXiv.org, revised Jun 2020.
    6. Carolina Castagnetti, 2015. "The Analysis of the Gender Wage Gap in the Italian Public Sector: a Quantile Approach for Panel Data," DEM Working Papers Series 109, University of Pavia, Department of Economics and Management.
    7. Tansel, Aysit & Keskin, Halil Ibrahim & Ozdemir, Zeynel Abidin, 2020. "Public-private sector wage gap by gender in Egypt: Evidence from quantile regression on panel data, 1998–2018," World Development, Elsevier, vol. 135(C).
    8. Harding, Matthew & Lamarche, Carlos, 2013. "Penalized Quantile Regression with Semiparametric Correlated Effects: Applications with Heterogeneous Preferences," IZA Discussion Papers 7741, Institute of Labor Economics (IZA).
    9. Carolina Castagnetti & Luisa Rosti & Marina Töpfer, 2019. "The Public-Private Sector Wage Differential Across Gender in Italy: a New Quantile-Based Decomposition Approach," Economics Bulletin, AccessEcon, vol. 39(4), pages 2533-2539.
    10. Li, Tong & Oka, Tatsushi, 2015. "Set identification of the censored quantile regression model for short panels with fixed effects," Journal of Econometrics, Elsevier, vol. 188(2), pages 363-377.
    11. Hernández Martínez, Pedro Jesús, 2016. "Reassessing the link between firm size and exports," Economics Discussion Papers 2016-25, Kiel Institute for the World Economy (IfW Kiel).
    12. Galvao, Antonio F. & Kato, Kengo, 2016. "Smoothed quantile regression for panel data," Journal of Econometrics, Elsevier, vol. 193(1), pages 92-112.
    13. Castagnetti, Carolina & Giorgetti, Maria Letizia, 2019. "Understanding the gender wage-gap differential between the public and private sectors in Italy: A quantile approach," Economic Modelling, Elsevier, vol. 78(C), pages 240-261.
    14. David Powell, 2020. "Does Labor Supply Respond to Transitory Income? Evidence from the Economic Stimulus Payments of 2008," Journal of Labor Economics, University of Chicago Press, vol. 38(1), pages 1-38.
    15. David Powell, 2022. "Quantile regression with nonadditive fixed effects," Empirical Economics, Springer, vol. 63(5), pages 2675-2691, November.
    16. Harding, Matthew & Lamarche, Carlos, 2012. "Estimating and Testing a Quantile Regression Model with Interactive Effects," IZA Discussion Papers 6802, Institute of Labor Economics (IZA).
    17. Sherrilyn Billger & Carlos Lamarche, 2015. "A panel data quantile regression analysis of the immigrant earnings distribution in the United Kingdom and United States," Empirical Economics, Springer, vol. 49(2), pages 705-750, September.
    18. David Powell, 2014. "Did the Economic Stimulus Payments of 2008 Reduce Labor Supply? Evidence from Quantile Panel Data Estimation," Working Papers WR-710-3, RAND Corporation.

  27. Daniel Ackerberg & John Geweke & Jinyong Hahn, 2009. "Comments on "Convergence Properties of the Likelihood of Computed Dynamic Models"," Econometrica, Econometric Society, vol. 77(6), pages 2009-2017, November.

    Cited by:

    1. Dennis Kristensen & Bernard Salanie, 2013. "Higher-order properties of approximate estimators," CeMMAP working papers 45/13, Institute for Fiscal Studies.
    2. Yi Wen & Huabin Wu, 2011. "Dynamics of externalities: a second-order perspective," Review, Federal Reserve Bank of St. Louis, vol. 93(May), pages 187-206.
    3. Sarolta Laczo, 2010. "Estimating Dynamic Contracts: Risk Sharing in Village Economies," 2010 Meeting Papers 687, Society for Economic Dynamics.
    4. Thomas H. Jørgensen, 2017. "Life-Cycle Consumption and Children: Evidence from a Structural Estimation," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(5), pages 717-746, October.
    5. Thomas H. Jørgensen, 2014. "Life-Cycle Consumption and Children," CAM Working Papers 2014_02, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
    6. Andreas Tryphonides, 2018. "Tilting Approximate Models," Papers 1805.10869, arXiv.org, revised Mar 2024.
    7. Lee, Jinhyuk & Seo, Kyoungwon, 2016. "Revisiting the nested fixed-point algorithm in BLP random coefficients demand estimation," Economics Letters, Elsevier, vol. 149(C), pages 67-70.

  28. Guggenberger, Patrik & Hahn, Jinyong & Kim, Kyooil, 2008. "Specification testing under moment inequalities," Economics Letters, Elsevier, vol. 99(2), pages 375-378, May.

    Cited by:

    1. Federico A. Bugni & Ivan A. Canay & Xiaoxia Shi, 2013. "Specification tests for partially identified models defined by moment inequalities," CeMMAP working papers CWP01/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Arvanitis, Stelios & Scaillet, Olivier & Topaloglou, Nikolas, 2020. "Spanning tests for Markowitz stochastic dominance," Journal of Econometrics, Elsevier, vol. 217(2), pages 291-311.
    3. Donald W.K. Andrews & Xiaoxia Shi, 2010. "Inference Based on Conditional Moment Inequalities," Cowles Foundation Discussion Papers 1761R2, Cowles Foundation for Research in Economics, Yale University, revised May 2012.
    4. Jorg Stoye & Yuichi Kitamura, 2017. "Nonparametric analysis of random utility models," CeMMAP working papers 56/17, Institute for Fiscal Studies.
    5. Le-Yu Chen & Jerzy Szroeter, 2009. "Hypothesis testing of multiple inequalities: the method of constraint chaining," CeMMAP working papers CWP13/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Jun, Sung Jae & Pinkse, Joris, 2009. "Semiparametric tests of conditional moment restrictions under weak or partial identification," Journal of Econometrics, Elsevier, vol. 152(1), pages 3-18, September.
    7. Kaido, Hiroaki, 2016. "A dual approach to inference for partially identified econometric models," Journal of Econometrics, Elsevier, vol. 192(1), pages 269-290.
    8. Donald W.K. Andrews & Panle Jia, 2008. "Inference for Parameters Defined by Moment Inequalities: A Recommended Moment Selection Procedure," Cowles Foundation Discussion Papers 1676, Cowles Foundation for Research in Economics, Yale University.
    9. David M. Kaplan & Longhao Zhuo, 2018. "Frequentist size of Bayesian inequality tests," Working Papers 1802, Department of Economics, University of Missouri, revised 14 Jul 2019.
    10. Rosen, Adam M., 2008. "Confidence sets for partially identified parameters that satisfy a finite number of moment inequalities," Journal of Econometrics, Elsevier, vol. 146(1), pages 107-117, September.
    11. Francesca Molinari, 2020. "Microeconometrics with Partial Identi?cation," CeMMAP working papers CWP15/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    12. Stefan Boes, 2009. "Bounds on Counterfactual Distributions Under Semi-Monotonicity Constraints," SOI - Working Papers 0920, Socioeconomic Institute - University of Zurich.
    13. Hsieh, Yu-Wei & Shi, Xiaoxia & Shum, Matthew, 2022. "Inference on estimators defined by mathematical programming," Journal of Econometrics, Elsevier, vol. 226(2), pages 248-268.
    14. Francesca Molinari, 2019. "Econometrics with Partial Identification," CeMMAP working papers CWP25/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Martin Huber & Giovanni Mellace, 2015. "Testing Instrument Validity for LATE Identification Based on Inequality Moment Constraints," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 398-411, May.
    16. Canay, Ivan A., 2010. "EL inference for partially identified models: Large deviations optimality and bootstrap validity," Journal of Econometrics, Elsevier, vol. 156(2), pages 408-425, June.

  29. Hahn, Jinyong & Hausman, Jerry & Kuersteiner, Guido, 2007. "Long difference instrumental variables estimation for dynamic panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 574-617, October.

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    1. Capolupo, Rosa, 2009. "The New Growth Theories and Their Empirics after Twenty Years," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-72.
    2. Elsas, Ralf & Florysiak, David, 2008. "Empirical Capital Structure Research: New Ideas, Recent Evidence, and Methodological Issues," Discussion Papers in Business Administration 4743, University of Munich, Munich School of Management.
    3. Kim, Tae-Nyun & Kim, Kihun, 2018. "External cost of leverage adjustment: Evidence from defined benefit pension plans," Journal of Economics and Business, Elsevier, vol. 96(C), pages 1-14.
    4. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2014. "What Do We Learn from the Weather? The New Climate-Economy Literature," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 740-798, September.
    5. In Choi & Sanghyun Jung, 2020. "Cross-sectional quasi maximum likelihood and bias-corrected pooled least squares estimators for short dynamic panels," Working Papers 2007, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    6. Musa, Umar & Jun, Wen, 2020. "Does inflation targeting cause financial instability?: An empirical test of paradox of credibility hypothesis," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    7. Ulubasoglu, Mehmet Ali & Yaraşır-Tülümce, Sevinç, 2019. "Pork and Turkey: Distributive Politics in the Allocation of Public Investments into Turkish Electoral Districts 1987–2004," MPRA Paper 96842, University Library of Munich, Germany.
    8. Acemoglu, Daron & Johnson, Simon & Robinson, James A. & Yared, Pierre, 2009. "Reevaluating the modernization hypothesis," Journal of Monetary Economics, Elsevier, vol. 56(8), pages 1043-1058, November.
    9. Hovakimian, Armen & Li, Guangzhong, 2011. "In search of conclusive evidence: How to test for adjustment to target capital structure," Journal of Corporate Finance, Elsevier, vol. 17(1), pages 33-44, February.
    10. Zhou, Qing & Faff, Robert & Alpert, Karen, 2014. "Bias correction in the estimation of dynamic panel models in corporate finance," Journal of Corporate Finance, Elsevier, vol. 25(C), pages 494-513.
    11. Serrasqueiro, Zélia & Nunes, Paulo Maçãs, 2010. "Non-linear relationships between growth opportunities and debt: Evidence from quoted Portuguese companies," Journal of Business Research, Elsevier, vol. 63(8), pages 870-878, August.
    12. Hu, Juncheng, 2021. "Do facilitation payments affect earnings management? Evidence from China," Journal of Corporate Finance, Elsevier, vol. 68(C).
    13. Surenderrao Komera & P. J. Jijo Lukose, 2016. "Heterogeneity and Asymmetry in Speed of Leverage Adjustment: The Indian Experience," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-26, September.
    14. Davis, Matt & Vedder, Andrea & Stone, Joe, 2015. "Local Tax Limits, Student Achievement, and School-Finance Equalization," MPRA Paper 63704, University Library of Munich, Germany.
    15. Juodis, Artūras & Sarafidis, Vasilis, 2022. "An incidental parameters free inference approach for panels with common shocks," Journal of Econometrics, Elsevier, vol. 229(1), pages 19-54.
    16. Devdatta Ray & Mikael Linden, 2020. "Health expenditure, longevity, and child mortality: dynamic panel data approach with global data," International Journal of Health Economics and Management, Springer, vol. 20(1), pages 99-119, March.
    17. Huaccha, Gissell, 2023. "Regional persistence of the energy efficiency gap: Evidence from England and Wales," Energy Economics, Elsevier, vol. 127(PA).
    18. Yongfu Huang & Jingjing He & Finn Tarp, 2012. "Is the Clean Development Mechanism Promoting Sustainable Development?," WIDER Working Paper Series wp-2012-072, World Institute for Development Economic Research (UNU-WIDER).
    19. Giorgio Canarella & Stephen M. Miller, 2019. "Determinants of Optimal Capital Structure and Speed of Adjustment: Evidence from the U.S. ICT Sector," Working papers 2019-06, University of Connecticut, Department of Economics.
    20. Shu Wen Ng & Edward C. Norton & David K. Guilkey & Barry M. Popkin, 2010. "Estimation of a Dynamic Model of Weight," NBER Working Papers 15864, National Bureau of Economic Research, Inc.
    21. Thomas J. Kniesner & W. Kip Viscusi & Christopher Woock & James P. Ziliak, 2010. "The Value of a Statistical Life: Evidence from Panel Data," Center for Policy Research Working Papers 122, Center for Policy Research, Maxwell School, Syracuse University.
    22. Daniel L. Millimet & Ian K. McDonough, 2017. "Dynamic Panel Data Models With Irregular Spacing: With an Application to Early Childhood Development," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 725-743, June.
    23. Samatas, Andreas & Makrominas, Michalis & Moro, Andrea, 2019. "Financial intermediation, capital composition and income stagnation: The case of Europe," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 273-289.
    24. Sedova, Barbora & Kalkuhl, Matthias, 2020. "Who are the climate migrants and where do they go? Evidence from rural India," World Development, Elsevier, vol. 129(C).
    25. Kryzanowski, Lawrence & Mohebshahedin, Mahmood, 2016. "Board governance, monetary interest, and closed-end fund performance," Journal of Corporate Finance, Elsevier, vol. 38(C), pages 196-217.
    26. Sasaki, Yuya & Xin, Yi, 2017. "Unequal spacing in dynamic panel data: Identification and estimation," Journal of Econometrics, Elsevier, vol. 196(2), pages 320-330.
    27. Flannery, Mark J. & Hankins, Kristine Watson, 2013. "Estimating dynamic panel models in corporate finance," Journal of Corporate Finance, Elsevier, vol. 19(C), pages 1-19.
    28. Dörffel, Christoph & Freytag, Andreas, 2023. "The poverty effect of democratization," World Development, Elsevier, vol. 165(C).
    29. Cave, Joshua & Chaudhuri, Kausik & Kumbhakar, Subal C., 2023. "Dynamic firm performance and estimator choice: A comparison of dynamic panel data estimators," European Journal of Operational Research, Elsevier, vol. 307(1), pages 447-467.
    30. Tue Gørgens & Christopher L. Skeels & Allan H. Würtz, 2009. "Efficient Estimation of Non-Linear Dynamic Panel Data Models with Application to Smooth Transition Models," CREATES Research Papers 2009-51, Department of Economics and Business Economics, Aarhus University.
    31. İbrahim Yarba & Z. Nuray Güner, 2020. "Leverage dynamics: Do financial development and government leverage matter? Evidence from a major developing economy," Empirical Economics, Springer, vol. 59(5), pages 2473-2507, November.
    32. Jan Kiviet & Milan Pleus & Rutger Poldermans, 2017. "Accuracy and Efficiency of Various GMM Inference Techniques in Dynamic Micro Panel Data Models," Econometrics, MDPI, vol. 5(1), pages 1-54, March.
    33. Maurice J.G. Bun & Sarafidis, V., 2013. "Dynamic Panel Data Models," UvA-Econometrics Working Papers 13-01, Universiteit van Amsterdam, Dept. of Econometrics.
    34. Badi H. Baltagi, 2013. "Dynamic panel data models," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 10, pages 229-248, Edward Elgar Publishing.
    35. Ottorino Morresi & Alessia Naccarato, 2016. "Are Family Firms Different in Choosing and Adjusting Their Capital Structure? An Empirical Analysis through the Lens of Agency Theory," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 8(7), pages 216-216, July.
    36. Christoph Doerffel & Peter Draper & Andreas Freytag & Sebastian Schuhmann, 2021. "Drivers of Inclusive Development: An Empirical Investigation," Jena Economics Research Papers 2021-015, Friedrich-Schiller-University Jena.
    37. Navarro, Lucas, 2009. "Employment dynamics and crises in Latin America," Revista CEPAL, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL), December.
    38. Han, Chirok & Phillips, Peter C. B. & Sul, Donggyu, 2014. "X-Differencing And Dynamic Panel Model Estimation," Econometric Theory, Cambridge University Press, vol. 30(1), pages 201-251, February.
    39. Li, Xiao-Ming & Qiu, Mei, 2021. "The joint effects of economic policy uncertainty and firm characteristics on capital structure: Evidence from US firms," Journal of International Money and Finance, Elsevier, vol. 110(C).
    40. Mountford, Andrew & Wadsworth, Jonathan, 2023. "‘Good jobs’, training and skilled immigration," LSE Research Online Documents on Economics 118784, London School of Economics and Political Science, LSE Library.
    41. Cseres-Gergely, Zsombor & Kvedaras, Virmantas, 2020. "China's WTO accession and income inequality in European regions: External pressure and internal adjustments," Working Papers 2020-01, Joint Research Centre, European Commission.
    42. Maurice J. G. Bun & Frank Kleibergen, 2021. "Identification robust inference for moments based analysis of linear dynamic panel data models," Papers 2105.08346, arXiv.org.
    43. Dang, Viet Anh & Kim, Minjoo & Shin, Yongcheol, 2012. "Asymmetric capital structure adjustments: New evidence from dynamic panel threshold models," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 465-482.
    44. In Choi, 2016. "Cross-sectional maximum likelihood and bias-corrected pooled least squares estimators for dynamic panels with short T," Working Papers 1610, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    45. Bao, Yong & Yu, Xuewen, 2023. "Indirect inference estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1027-1053.
    46. Apergis, Nicholas & Voliotis, Dimitrios, 2015. "Spillover effects between lit and dark stock markets: Evidence from a panel of London Stock Exchange transactions," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 101-106.
    47. Cheng Hsiao & Qiankun Zhou, 2016. "Asymptotic distribution of quasi-maximum likelihood estimation of dynamic panels using long difference transformation when both N and T are large," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(4), pages 675-683, November.
    48. Morais, Flávio & Serrasqueiro, Zélia & Ramalho, Joaquim J.S., 2022. "Capital structure speed of adjustment heterogeneity across zero leverage and leveraged European firms," Research in International Business and Finance, Elsevier, vol. 62(C).
    49. Hsiao, Cheng & Zhou, Qiankun, 2015. "Statistical inference for panel dynamic simultaneous equations models," Journal of Econometrics, Elsevier, vol. 189(2), pages 383-396.
    50. Masato Nishiwaki & Hyoeg Ug Kwon, 2013. "Are Losers Picked? An Empirical Analysis of Capacity Divestment and Production Reallocation in the Japanese Cement Industry," Journal of Industrial Economics, Wiley Blackwell, vol. 61(2), pages 430-467, June.
    51. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Liu, Guangqiang & Ibrahim, Mansor, 2021. "Ethical investing and capital structure," Emerging Markets Review, Elsevier, vol. 47(C).
    52. Jerry A. Hausman & Maxim L. Pinkovskiy, 2017. "Estimating dynamic panel models: backing out the Nickell Bias," Staff Reports 824, Federal Reserve Bank of New York.
    53. Wolfgang Drobetz & Dirk C. Schilling & Henning Schröder, 2015. "Heterogeneity in the Speed of Capital Structure Adjustment across Countries and over the Business Cycle," European Financial Management, European Financial Management Association, vol. 21(5), pages 936-973, November.
    54. Giorgio Canarella & Stephen M. Miller, 2019. "Firm Size, Corporate Debt, R&D Activity, and Agency Costs: Exploring Dynamic and Non-Linear Effects," Working papers 2019-05, University of Connecticut, Department of Economics.
    55. Narayan, Paresh Kumar & Nasiri, Maryam Akbari, 2020. "Understanding corporate debt from the oil market perspective," Energy Economics, Elsevier, vol. 92(C).
    56. Hayakawa, Kazuhiko & Nagata, Shuichi, 2016. "On the behaviour of the GMM estimator in persistent dynamic panel data models with unrestricted initial conditions," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 265-303.
    57. Doucouliagos, Chris & Hennessy, Jack & Mallick, Debdulal, 2019. "Health Aid, Governance and Infant Mortality," IZA Discussion Papers 12166, Institute of Labor Economics (IZA).
    58. Okui, Ryo, 2008. "Panel AR(1) estimators under misspecification," Economics Letters, Elsevier, vol. 101(3), pages 210-213, December.
    59. Jan F. Kiviet & Milan Pleus & Rutger Poldermans, 2014. "Accuracy and efficiency of various GMM inference techniques in dynamic micro panel data models," UvA-Econometrics Working Papers 14-09, Universiteit van Amsterdam, Dept. of Econometrics.
    60. Dang, Viet Anh & Kim, Minjoo & Shin, Yongcheol, 2015. "In search of robust methods for dynamic panel data models in empirical corporate finance," Journal of Banking & Finance, Elsevier, vol. 53(C), pages 84-98.
    61. Maria Elena Bontempi & Roberto Golinelli, 2012. "The effect of neglecting the slope parameters’ heterogeneity on dynamic models of corporate capital structure," Quantitative Finance, Taylor & Francis Journals, vol. 12(11), pages 1733-1751, November.
    62. Barbora Sedova & Matthias Kalkuhl & Robert Mendelsohn, 2020. "Distributional Impacts of Weather and Climate in Rural India," Economics of Disasters and Climate Change, Springer, vol. 4(1), pages 5-44, April.
    63. Chen, Weihao & Cizek, Pavel, 2023. "Bias-Corrected Instrumental Variable Estimation in Linear Dynamic Panel Data Models," Other publications TiSEM 9bf2c16c-522f-4223-8037-c, Tilburg University, School of Economics and Management.
    64. Filippo Ippolito & Alessandro Villa, 2022. "Levered Returns and Capital Structure Imbalances," Working Paper Series WP 2022-42, Federal Reserve Bank of Chicago.
    65. Mohammad Reza Farzanegan & Mehdi Feizi & Hassan F. Gholipour, 2021. "Drought and Property Prices: Empirical Evidence from Provinces of Iran," Economics of Disasters and Climate Change, Springer, vol. 5(2), pages 203-221, July.
    66. Fritsch, Markus, 2019. "On GMM estimation of linear dynamic panel data models," Passauer Diskussionspapiere, Betriebswirtschaftliche Reihe B-36-19, University of Passau, Faculty of Business and Economics.
    67. Jingjing He & Yongfu Huang & Finn Tarp, 2014. "Has the Clean Development Mechanism assisted sustainable development?," Natural Resources Forum, Blackwell Publishing, vol. 38(4), pages 248-260, November.
    68. Natalia Szomko, 2017. "The Importance of Estimation Method Choice for the Analysis of the Determinants of Capital Structure– An Example of Poland," World Journal of Applied Economics, WERI-World Economic Research Institute, vol. 3(1), pages 3-20, June.
    69. Gonzalo Rubio & Francisco Sogorb, 2011. "The Adjustment To Target Leverage Of Spanish Public Firms: Macroeconomic Conditions And Distance From Target," Revista de Economia Aplicada, Universidad de Zaragoza, Departamento de Estructura Economica y Economia Publica, vol. 19(3), pages 35-63, Winter.
    70. Jerry Hausman & Maxim L. Pinkovskiy, 2017. "Estimating dynamic panel models: backing out the Nickell Bias," CeMMAP working papers CWP53/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    71. Hoang, Khanh & Nguyen, Cuong & Zhang, Hailiang, 2021. "How does economic policy uncertainty affect corporate diversification?," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 254-269.

  30. Hahn, Jinyong & Moon, Hyungsik Roger, 2006. "Reducing Bias Of Mle In A Dynamic Panel Model," Econometric Theory, Cambridge University Press, vol. 22(3), pages 499-512, June.
    See citations under working paper version above.
  31. Jinyong Hahn & Jerry Hausman, 2005. "Estimation with Valid and Invalid Instruments," Annals of Economics and Statistics, GENES, issue 79-80, pages 25-57.

    Cited by:

    1. Hahn, Jinyong & Hausman, Jerry & Kim, Jeonghwan, 2021. "A small sigma approach to certain problems in errors-in-variables models," Economics Letters, Elsevier, vol. 208(C).
    2. Laffers, Lukas, 2013. "Identification in Models with Discrete Variables," Discussion Paper Series in Economics 1/2013, Norwegian School of Economics, Department of Economics.
    3. Firmin Doko Tchatoka, 2014. "Specification Tests with Weak and Invalid Instruments," School of Economics and Public Policy Working Papers 2014-05, University of Adelaide, School of Economics and Public Policy.
    4. He, Qichun, 2011. "Home-bias Politics, Financial Deregulation and Economic Growth: A Causal Relationship," MPRA Paper 34482, University Library of Munich, Germany.
    5. Hugo J. Faria & Hugo M. Montesinos-Yufa, 2017. "Is the Effect of Income on Democracy Heterogeneous?," Working Papers 2017-05, University of Miami, Department of Economics.
    6. Robert P. Inman, 2008. "Federalism's Values and the Value of Federalism," NBER Working Papers 13735, National Bureau of Economic Research, Inc.
    7. Marcellino, Massimiliano & Kapetanios, George & Khalaf, Lynda, 2015. "Factor based identification-robust inference in IV regressions," CEPR Discussion Papers 10390, C.E.P.R. Discussion Papers.
    8. Qichun He, 2011. "Does FDI Promote Human Capital Accumulation? The Role of Gradual Financial Liberalization," CEMA Working Papers 455, China Economics and Management Academy, Central University of Finance and Economics.
    9. van der Klaauw, Bas, 2014. "From Micro Data to Causality: Forty Years of Empirical Labor Economics," IZA Discussion Papers 8047, Institute of Labor Economics (IZA).
    10. Timothy B. Armstrong & Michal Kolesár, 2020. "Sensitivity Analysis using Approximate Moment Condition Models," Working Papers 2020-28, Princeton University. Economics Department..
    11. St'ephane Bonhomme & Martin Weidner, 2018. "Minimizing Sensitivity to Model Misspecification," Papers 1807.02161, arXiv.org, revised Oct 2021.
    12. Michael P. Murray, 2006. "Avoiding Invalid Instruments and Coping with Weak Instruments," Journal of Economic Perspectives, American Economic Association, vol. 20(4), pages 111-132, Fall.
    13. Murray Michael P., 2017. "Linear Model IV Estimation When Instruments Are Many or Weak," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    14. Michal Kolesár & Raj Chetty & John N. Friedman & Edward L. Glaeser & Guido W. Imbens, 2011. "Identification and Inference with Many Invalid Instruments," NBER Working Papers 17519, National Bureau of Economic Research, Inc.
    15. Stéphane Bonhomme & Martin Weidner, 2020. "Minimizing Sensitivity to Model Misspecification," CeMMAP working papers CWP37/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    16. Zi-Yi Guo, 2017. "Health Insurance and the Demand for Medical Care: a Case Study from China," Asian Journal of Economics and Empirical Research, Asian Online Journal Publishing Group, vol. 4(1), pages 8-13.
    17. Byunghoon Kang, 2018. "Higher Order Approximation of IV Estimators with Invalid Instruments," Working Papers 257105320, Lancaster University Management School, Economics Department.
    18. Jan F. KIVIET & Jerzy NIEMCZYK, 2013. "On the limiting and empirical distributions of IV estimators when some of the instruments are actually endogenous," Economic Growth Centre Working Paper Series 1311, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    19. Marc Frenette, 2011. "How does the stork delegate work? Childbearing and the gender division of paid and unpaid labour," Journal of Population Economics, Springer;European Society for Population Economics, vol. 24(3), pages 895-910, July.
    20. Lopez, Alberto, 2008. "Determinants of R&D cooperation: Evidence from Spanish manufacturing firms," International Journal of Industrial Organization, Elsevier, vol. 26(1), pages 113-136, January.
    21. Seojeong Lee, 2015. "A Consistent Variance Estimator for 2SLS When Instruments Identify Different LATEs," Discussion Papers 2015-01, School of Economics, The University of New South Wales.
    22. Barbara Ermini & Raffaella Santolini, 2017. "Urban sprawl and property tax of a city’s core and suburbs: evidence from Italy," Regional Studies, Taylor & Francis Journals, vol. 51(9), pages 1374-1386, September.
    23. Guo, Zijian & Kang, Hyunseung & Cai, T. Tony & Small, Dylan S., 2018. "Testing endogeneity with high dimensional covariates," Journal of Econometrics, Elsevier, vol. 207(1), pages 175-187.
    24. Rui Wang, 2023. "Point Identification of LATE with Two Imperfect Instruments," Papers 2303.13795, arXiv.org.
    25. Seojeong Lee, 2013. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Method of Moments Estimators," Discussion Papers 2013-09, School of Economics, The University of New South Wales.
    26. Cheng-Few Lee & Woan-lih Liang & Fu-Lai Lin & Yating Yang, 2016. "Applications of simultaneous equations in finance research: methods and empirical results," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 943-971, November.
    27. Martin Emil Jakobsen & Jonas Peters, 2022. "Distributional robustness of K-class estimators and the PULSE [The colonial origins of comparative development: An empirical investigation]," The Econometrics Journal, Royal Economic Society, vol. 25(2), pages 404-432.
    28. Vipul Bhatt & N. Kishor, 2013. "Bank lending channel in India: evidence from state-level analysis," Empirical Economics, Springer, vol. 45(3), pages 1307-1331, December.
    29. Shaobo Jin & Fan Yang-Wallentin & Kenneth A. Bollen, 2021. "A unified model-implied instrumental variable approach for structural equation modeling with mixed variables," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 564-594, June.
    30. Tonmoy Choudhury & Muhammad Kamran & Hadrian Geri Djajadikerta & Tapan Sarker, 2023. "Can Banks Sustain the Growth in Renewable Energy Supply? An International Evidence," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 35(1), pages 20-50, February.

  32. Patrik Guggenberger & Jinyong Hahn, 2005. "Finite Sample Properties of the Two-Step Empirical Likelihood Estimator," Econometric Reviews, Taylor & Francis Journals, vol. 24(3), pages 247-263.

    Cited by:

    1. Seojeong Lee, 2014. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for GEL Estimators," Discussion Papers 2014-02, School of Economics, The University of New South Wales.
    2. Fan, Yanqin & Gentry, Matthew & Li, Tong, 2011. "A new class of asymptotically efficient estimators for moment condition models," Journal of Econometrics, Elsevier, vol. 162(2), pages 268-277, June.
    3. Aaron Chalfin & Justin McCrary, 2013. "The Effect of Police on Crime: New Evidence from U.S. Cities, 1960-2010," NBER Working Papers 18815, National Bureau of Economic Research, Inc.
    4. Pierre Chaussé, 2011. "Generalized empirical likelihood for a continuum of moment conditions," Working Papers 1104, University of Waterloo, Department of Economics, revised Oct 2011.
    5. Stefan Boes, 2010. "Count Data Models with Correlated Unobserved Heterogeneity," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(3), pages 382-402, September.
    6. Patrik Guggenberger, 2006. "Finite-Sample Evidence Suggesting a Heavy Tail Problem of the Generalized Empirical Likelihood Estimator, accepted for publication, Econometric Reviews," UCLA Economics Online Papers 371, UCLA Department of Economics.
    7. Alain Guay & Florian Pelgrin, 2016. "Using Implied Probabilities to Improve the Estimation of Unconditional Moment Restrictions for Weakly Dependent Data," Econometric Reviews, Taylor & Francis Journals, vol. 35(3), pages 344-372, March.
    8. Seojeong Lee, 2018. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Empirical Likelihood Estimators," Papers 1806.00953, arXiv.org, revised Jun 2018.
    9. Rachida Ouysse, 2014. "On the performance of block-bootstrap continuously updated GMM for a class of non-linear conditional moment models," Computational Statistics, Springer, vol. 29(1), pages 233-261, February.
    10. Alain Guay & Florian Pelgrin, 2007. "Using Implied Probabilities to Improve Estimation with Unconditional Moment Restrictions," Cahiers de recherche 0747, CIRPEE.

  33. Graham, Bryan S. & Hahn, Jinyong, 2005. "Identification and estimation of the linear-in-means model of social interactions," Economics Letters, Elsevier, vol. 88(1), pages 1-6, July.

    Cited by:

    1. Carrión-Flores, Carmen & Irwin, Elena G., 2010. "Identifying spatial interactions in the presence of spatial error autocorrelation: An application to land use spillovers," Resource and Energy Economics, Elsevier, vol. 32(2), pages 135-153, April.
    2. Brock,W.A. & Durlauf,S.N., 2004. "Identification of binary choice models with social interactions," Working papers 2, Wisconsin Madison - Social Systems.
    3. Simon K.C. Cheung, 2017. "A Localized Model for Residential Property Valuation: Nearest Neighbor with Attribute Differences," International Real Estate Review, Global Social Science Institute, vol. 20(2), pages 221-250.
    4. Goette, Lorenz & Bruhin, Adrian & Haenni, Simon & Jiang, Lingqing, 2015. "Spillovers of Prosocial Motivation: Evidence from an Intervention Study on Blood Donors," CEPR Discussion Papers 10345, C.E.P.R. Discussion Papers.
    5. Brock,W.A. & Durlauf,S.N., 2003. "Multinomial choice with social interactions," Working papers 1, Wisconsin Madison - Social Systems.
    6. Giacomo De Giorgi & Anders Frederiksen & Luigi Pistaferri, 2016. "Consumption Network Effects," NBER Working Papers 22357, National Bureau of Economic Research, Inc.
    7. Bryan S. Graham, 2016. "Identifying and Estimating Neighborhood Effects," NBER Working Papers 22575, National Bureau of Economic Research, Inc.
    8. Natallia Gray & Gabriel Picone, 2018. "Evidence of Large-Scale Social Interactions in Mammography in the United States," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 46(4), pages 441-457, December.
    9. Giovanni Abbiati & Jonathan Pratschke, 2021. "‘Like with Like’ or ‘Do Like’? Modelling Peer Effects in The Classroom," CSEF Working Papers 603, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    10. Bramoullé, Yann & Djebbari, Habiba & Fortin, Bernard, 2009. "Identification of peer effects through social networks," Journal of Econometrics, Elsevier, vol. 150(1), pages 41-55, May.
    11. Bet Caeyers, 2014. "Peer effects in development programme awareness of vulnerable groups in rural Tanzania," CSAE Working Paper Series 2014-11, Centre for the Study of African Economies, University of Oxford.
    12. Arthur Lewbel & Xi Qu & Xun Tang, 2023. "Social Networks with Unobserved Links," Journal of Political Economy, University of Chicago Press, vol. 131(4), pages 898-946.
    13. Grodner, Andrew & Kniesner, Thomas J. & Bishop, John A., 2011. "Social Interactions in the Labor Market," Foundations and Trends(R) in Microeconomics, now publishers, vol. 6(4), pages 265-366, September.
    14. Apouey, B. & Picone, G., 2014. "Social Interactions and Malaria Preventive Behaviors in Sub-Saharan Africa," Health, Econometrics and Data Group (HEDG) Working Papers 14/06, HEDG, c/o Department of Economics, University of York.
    15. ÖZGÜR, Onur & BISIN, Alberto, 2011. "Dynamic linear economies with social interactions," Cahiers de recherche 2011-03, Universite de Montreal, Departement de sciences economiques.
    16. Davezies, Laurent & D'Haultfoeuille, Xavier & Fougère, Denis, 2006. "Identification of Peer Effects Using Group Size Variation," IZA Discussion Papers 2324, Institute of Labor Economics (IZA).
    17. Luisa Corrado & Roberta Distante & Majlinda Joxhe, 2019. "Body mass index and social interactions from adolescence to adulthood," Spatial Economic Analysis, Taylor & Francis Journals, vol. 14(4), pages 425-445, October.
    18. Giacomo DeGiorgi, "undated". "Be As Careful Of The Company You Keep As Of The Books You Read. Peer Effects In Education And On The Labor Market," Discussion Papers 07-054, Stanford Institute for Economic Policy Research.
    19. Ariel H. Fambeu, 2019. "Peer Effect and Environmental Responsibility of Enterprises in a Sub-Saharan African Country," Economics Bulletin, AccessEcon, vol. 39(2), pages 1084-1094.
    20. Steven N. Durlauf & Hisatoshi Tanaka, 2008. "Understanding Regression Versus Variance Tests For Social Interactions," Economic Inquiry, Western Economic Association International, vol. 46(1), pages 25-28, January.
    21. Patacchini, Eleonora & Bisin, Alberto, 2019. "Dynamic Social Interactions and Health Risk Behavior," CEPR Discussion Papers 13918, C.E.P.R. Discussion Papers.
    22. Canning, David & Günther, Isabel & Linnemayr, Sebastian & Bloom, David, 2013. "Fertility choice, mortality expectations, and interdependent preferences—An empirical analysis," European Economic Review, Elsevier, vol. 63(C), pages 273-289.
    23. Giorgio Topa & Elizabeth Setren & Meta Brown, 2011. "Do Referrals Lead to Better Matches? Evidence from a Firm's Employee," 2011 Meeting Papers 711, Society for Economic Dynamics.
    24. John Knight & Ramani Gunatilaka, 2017. "Is Happiness Infectious?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 64(1), pages 1-24, February.
    25. Jason Fletcher, 2013. "Social Interactions And College Enrollment: Evidence From The National Education Longitudinal Study," Contemporary Economic Policy, Western Economic Association International, vol. 31(4), pages 762-778, October.
    26. Georges Dieudonné Mbondo & Novice Patrick Bakehe & Ariel Herbert Fambeu, 2022. "Is informality contagious? An analysis of the effects of social conformism on the formalization of small business," Economics Bulletin, AccessEcon, vol. 42(2), pages 317-329.
    27. Lin, Zhongjian & Tang, Xun & Yu, Ning Neil, 2021. "Uncovering heterogeneous social effects in binary choices," Journal of Econometrics, Elsevier, vol. 222(2), pages 959-973.
    28. Andrew Grodner & Thomas Kniesner, 2005. "Labor Supply with Social Interactions: Econometric Estimates and Their Tax Policy Implications," Center for Policy Research Working Papers 69, Center for Policy Research, Maxwell School, Syracuse University.
    29. Bet Caeyers, 2014. "Exclusion bias in empirical social interaction models: causes, consequences and solutions," CSAE Working Paper Series 2014-05, Centre for the Study of African Economies, University of Oxford.
    30. Jesse A. Matheson, 2015. "Prices and social behaviour: Evidence from adult smoking in Canadian Aboriginal communities," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 48(5), pages 1661-1693, December.
    31. Fang, Hang & Chen, Qianheng & Delgado, Michael S. & He, Qinying, 2023. "Peer correlations in income: Evidence from a Guanxi network in rural China," Economics Letters, Elsevier, vol. 222(C).
    32. Vaughan Daniel, 2013. "Nurture vs. Nurture: Endogenous Parental and Peer Effects and the Transmission of Culture," Working Papers 2013-04, Banco de México.
    33. Simone Celant, 2013. "The analysis of students’ academic achievement: the evaluation of peer effects through relational links," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(2), pages 615-631, February.
    34. David Puelz & Guillaume Basse & Avi Feller & Panos Toulis, 2022. "A graph‐theoretic approach to randomization tests of causal effects under general interference," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(1), pages 174-204, February.
    35. Hesselius, Patrik & Johansson, Per & Vikström, Johan, 2008. "Monitoring and norms in sickness insurance: empirical evidence from a natural experiment," Working Paper Series 2008:8, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    36. Zacharias Ziegelhöfer, 2012. "Down with diarrhea: Using fuzzy Regression Discontinuity Design to link communal water supply with health," IHEID Working Papers 05-2012, Economics Section, The Graduate Institute of International Studies, revised 26 Mar 2012.
    37. Ciliberto, Federico & Miller, Amalia & Skyt Nielsen, Helena & Simonsen, Marianne, 2013. "Playing the Fertility Game at Work: An Equilibrium Model of Peer Effects," MPRA Paper 45914, University Library of Munich, Germany.
    38. José-Alberto Guerra & Myra Mohnen, 2017. "Multinomial choice with social interactions: occupations in Victorian London," Documentos CEDE 15667, Universidad de los Andes, Facultad de Economía, CEDE.
    39. Yang, Muzhe & Huang, Rui, 2010. "Exposure to Obesity and Weight Gain among Adolescents," Research Reports 149944, University of Connecticut, Food Marketing Policy Center.
    40. Chi Feng & Yang Nathan, 2011. "Twitter Adoption in Congress," Review of Network Economics, De Gruyter, vol. 10(1), pages 1-46, March.
    41. Alberto Bisin & Andrea Moro & Giorgio Topa, 2011. "The empirical content of models with multiple equilibria in economies with social interactions," Staff Reports 504, Federal Reserve Bank of New York.
    42. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jan 2022.
    43. Blume,L.E. & Durlauf,S.N., 2005. "Identifying social interactions : a review," Working papers 12, Wisconsin Madison - Social Systems.
    44. Tommy K. Y. Cheung & Simon K. C. Cheung, 2020. "Spatial dependence model with feature difference," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 615-627, July.
    45. Auld, M. Christopher, 2011. "Effect of large-scale social interactions on body weight," Journal of Health Economics, Elsevier, vol. 30(2), pages 303-316, March.
    46. Giacomo De Giorgi & Michele Pellizzari & Silvia Redaelli, 2010. "Identification of Social Interactions through Partially Overlapping Peer Groups," American Economic Journal: Applied Economics, American Economic Association, vol. 2(2), pages 241-275, April.
    47. Eric Auerbach, 2019. "Identification and Estimation of a Partially Linear Regression Model using Network Data," Papers 1903.09679, arXiv.org, revised Jun 2021.
    48. Bansal, Sangeeta & Khanna, Madhu & Sydlowski, Joseph, 2021. "Incentives for corporate social responsibility in India: Mandate, peer pressure and crowding-out effects," Journal of Environmental Economics and Management, Elsevier, vol. 105(C).
    49. Hirano, Keisuke & Hahn, Jinyong, 2010. "Design of randomized experiments to measure social interaction effects," Economics Letters, Elsevier, vol. 106(1), pages 51-53, January.
    50. Cheung, Tommy King-Yin & Wong, Wai-hung & Zhang, Anming & Wu, Yangming, 2020. "Spatial panel model for examining airport relationships within multi-airport regions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 148-163.
    51. Brock,W.A. & Durlauf,S.N., 2005. "Social interactions and macroeconomics," Working papers 5, Wisconsin Madison - Social Systems.
    52. De Giorgi, Giacomo & Pellizzari, Michele & Redaelli, Silvia, 2007. "Be as Careful of the Books You Read as of the Company You Keep: Evidence on Peer Effects in Educational Choices," IZA Discussion Papers 2833, Institute of Labor Economics (IZA).
    53. David E. Bloom & David Canning & Isabel Günther & Sebastian Linnemayr, 2008. "Social Interactions and Fertility in Developing Countries," PGDA Working Papers 3408, Program on the Global Demography of Aging.
    54. Lea Eilers & Alfredo R. Paloyo & Peggy Bechara, 2022. "The effect of peer employment and neighborhood characteristics on individual employment," Empirical Economics, Springer, vol. 62(4), pages 1885-1908, April.
    55. Entorf, Horst & Tatsi, Eirini, 2009. "Migrants at School: Educational Inequality and Social Interaction in the UK and Germany," IZA Discussion Papers 4175, Institute of Labor Economics (IZA).

  34. Hahn, Jinyong & Meinecke, Juergen, 2005. "Time-Invariant Regressor In Nonlinear Panel Model With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 21(2), pages 455-469, April.

    Cited by:

    1. Olatunji Abdul Shobande, 2021. "Decomposing the Persistent and Transitory Effect of Information and Communication Technology on Environmental Impacts Assessment in Africa: Evidence from Mundlak Specification," Sustainability, MDPI, vol. 13(9), pages 1-12, April.
    2. Denis Chetverikov & Bradley Larsen & Christopher Palmer, 2016. "IV Quantile Regression for Group‐Level Treatments, With an Application to the Distributional Effects of Trade," Econometrica, Econometric Society, vol. 84, pages 809-833, March.
    3. Okafor, Luke & Yan, Eric, 2022. "Covid-19 vaccines, rules, deaths, and tourism recovery," Annals of Tourism Research, Elsevier, vol. 95(C).

  35. Hahn, Jinyong & Kuersteiner, Guido & Cho, Myeong Hyeon, 2004. "Asymptotic distribution of misspecified random effects estimator for a dynamic panel model with fixed effects when both n and T are large," Economics Letters, Elsevier, vol. 84(1), pages 117-125, July.

    Cited by:

    1. Manuel Arellano & Stéphane Bonhomme, 2007. "Robust priors in nonlinear panel data models," CeMMAP working papers CWP07/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Maurice J.G. Bun & Martin A. Carree & Artūras Juodis, 2017. "On Maximum Likelihood Estimation of Dynamic Panel Data Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 79(4), pages 463-494, August.
    3. Rodrigo Alfaro, 2008. "Estimation of a Dynamic Panel Data: The Case Of Corporate Investment in Chile," Working Papers Central Bank of Chile 467, Central Bank of Chile.

  36. Jinyong Hahn & Whitney Newey, 2004. "Jackknife and Analytical Bias Reduction for Nonlinear Panel Models," Econometrica, Econometric Society, vol. 72(4), pages 1295-1319, July.
    See citations under working paper version above.
  37. Hahn, Jinyong, 2004. "Does Jeffrey's prior alleviate the incidental parameter problem?," Economics Letters, Elsevier, vol. 82(1), pages 135-138, January.

    Cited by:

    1. Manuel Arellano & Stéphane Bonhomme, 2007. "Robust priors in nonlinear panel data models," CeMMAP working papers CWP07/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  38. Joshua Angrist & Jinyong Hahn, 2004. "When to Control for Covariates? Panel Asymptotics for Estimates of Treatment Effects," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 58-72, February.

    Cited by:

    1. Dettmann, E. & Becker, C. & Schmeißer, C., 2011. "Distance functions for matching in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1942-1960, May.
    2. Bryan S. Graham & Keisuke Hirano, 2011. "Robustness to Parametric Assumptions in Missing Data Models," American Economic Review, American Economic Association, vol. 101(3), pages 538-543, May.
    3. Antonio Musolesi & Hervé Cardot, 2017. "Modeling temporal treatment effects with zero inflated semi-parametric regression models: the case of local development policies in France," Working Papers 2017036, University of Ferrara, Department of Economics.
    4. Kristin Forbes & Marcel Fratzscher & Roland Straub, 2014. "Capital-flow Management Measures: What Are They Good For?," NBER Chapters, in: NBER International Seminar on Macroeconomics 2014, pages 76-97, National Bureau of Economic Research, Inc.
    5. Dettmann, Eva & Günther, Jutta, 2009. "Subsidized Vocational Training: Stepping Stone or Trap? An Evaluation Study for East Germany," IWH Discussion Papers 21/2009, Halle Institute for Economic Research (IWH).
    6. Arthur Grimes & Cleo Ren & Philip Stevens, 2009. "The Need for Speed: Impacts of Internet Connectivity on Firm Productivity," Working Papers 09_15, Motu Economic and Public Policy Research.
    7. Wooldridge, Jeffrey M. & Imbens, Guido, 2009. "Recent Developments in the Econometrics of Program Evaluation," Scholarly Articles 3043416, Harvard University Department of Economics.
    8. Cattaneo, Matias D & Jansson, Michael & Newey, Whitney K, 2018. "Inference in Linear Regression Models with Many Covariates and Heteroscedasticity," Department of Economics, Working Paper Series qt6rp7p9gs, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    9. Riccardo D'Adamo, 2018. "Cluster-Robust Standard Errors for Linear Regression Models with Many Controls," Papers 1806.07314, arXiv.org, revised Apr 2019.
    10. Richard Blundell & Lorraine Dearden & Barbara Sianesi, 2005. "Evaluating the effect of education on earnings: models, methods and results from the National Child Development Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(3), pages 473-512, July.
    11. Joshua Angrist, 2022. "Empirical Strategies in Economics: Illuminating the Path from Cause to Effect," NBER Working Papers 29726, National Bureau of Economic Research, Inc.
    12. Rothe, Christoph, 2016. "The Value of Knowing the Propensity Score for Estimating Average Treatment Effects," IZA Discussion Papers 9989, Institute of Labor Economics (IZA).
    13. Atila Abdulkadiroğlu & Joshua D. Angrist & Yusuke Narita & Parag A. Pathak, 2017. "Research Design Meets Market Design: Using Centralized Assignment for Impact Evaluation," Econometrica, Econometric Society, vol. 85, pages 1373-1432, September.
    14. Atzeni, Gianfranco E. & Carboni, Oliviero A., 2008. "The effects of grant policy on technology investment in Italy," Journal of Policy Modeling, Elsevier, vol. 30(3), pages 381-399.
    15. Nalan Basturk & Cem Cakmakli & S. Pinar Ceyhan & Herman K. van Dijk, 2014. "On the Rise of Bayesian Econometrics after Cowles Foundation Monographs 10, 14," Tinbergen Institute Discussion Papers 14-085/III, Tinbergen Institute, revised 04 Sep 2014.
    16. Emmanuel Orkoh & Phillip Frederick Blaauw & Carike Claassen, 2020. "Relative Effects of Income and Consumption Poverty on Time Poverty in Ghana," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(2), pages 465-499, January.
    17. Eva Dettmann & Jutta Günther, 2013. "Subsidized Vocational Training: Stepping Stone or Trap? Assessing Empirical Effects Using Matching Techniques," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 149(IV), pages 405-443, December.
    18. Ogrokhina, Olena & Rodriguez, Cesar M., 2018. "The role of inflation targeting in international debt denomination in developing countries," Journal of International Economics, Elsevier, vol. 114(C), pages 116-129.
    19. Blundell, Richard & Dearden, Lorraine & Sianesi, Barbara, 2004. "Evaluating the impact of education on earnings in the UK: models, methods and results from the NCDS," LSE Research Online Documents on Economics 19451, London School of Economics and Political Science, LSE Library.
    20. Fratzscher, Marcel & Forbes, Kristin & Straub, Roland, 2014. "Capital Controls and Macroprudential Measures: What Are They Good For?," CEPR Discussion Papers 9798, C.E.P.R. Discussion Papers.
    21. Martin Huber & Michael Lechner & Conny Wunsch, 2010. "How to control for many covariates? Reliable estimators based on the propensity score," University of St. Gallen Department of Economics working paper series 2010 2010-30, Department of Economics, University of St. Gallen.
    22. E. Han Kim & Yao Lu, 2018. "Executive Suite Independence: Is It Related to Board Independence?," Management Science, INFORMS, vol. 64(3), pages 1015-1033, March.
    23. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    24. Radhika Pandey & Gurnain Pasricha & Ila Patnaik & Ajay Shah, 2015. "Motivations for Capital Controls and Their Effectiveness," Staff Working Papers 15-5, Bank of Canada.
    25. Marcus Eliason & Donald Storrie, 2006. "Lasting or Latent Scars? Swedish Evidence on the Long-Term Effects of Job Displacement," Journal of Labor Economics, University of Chicago Press, vol. 24(4), pages 831-856, October.
    26. Roberto Gabriele & Marco Zamarian & Enrico Zaninotto, 2006. "Assessing the economic impact of public industrial policies: an empirical investigation on subsidies," ROCK Working Papers 039, Department of Computer and Management Sciences, University of Trento, Italy, revised 12 Jun 2008.
    27. Keisuke Hirano & Jack R. Porter, 2016. "Panel Asymptotics and Statistical Decision Theory," The Japanese Economic Review, Springer, vol. 67(1), pages 33-49, March.
    28. Ravallion, Martin, 2008. "Evaluating Anti-Poverty Programs," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 59, pages 3787-3846, Elsevier.
    29. Dettmann, Eva & Becker, Claudia & Schmeißer, Christian, 2010. "Is there a Superior Distance Function for Matching in Small Samples?," IWH Discussion Papers 3/2010, Halle Institute for Economic Research (IWH).
    30. Jian Sun & Nengliang Yao & Shoujun Lyu, 2021. "The association between Urban and Rural Resident Basic Medical Insurance and depressive symptoms among Chinese middle‐aged and older adults: Evidence from the China Health and Retirement Longitudinal ," International Journal of Health Planning and Management, Wiley Blackwell, vol. 36(5), September.
    31. Justine Burns & Malcolm Kewsell & Rebecca Thornton, 2009. "Evaluating the Impact of Health Programmes," SALDRU Working Papers 40, Southern Africa Labour and Development Research Unit, University of Cape Town.
    32. Augurzky, Boris & Kluve, Jochen, 2004. "Assessing the Performance of Matching Algorithms When Selection into Treatment Is Strong," IZA Discussion Papers 1301, Institute of Labor Economics (IZA).
    33. Jason K. Luellen & William R. Shadish & M. H. Clark, 2005. "Propensity Scores," Evaluation Review, , vol. 29(6), pages 530-558, December.
    34. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
    35. Gianfranco E. Atzeni & OA Carboni, 2006. "Regional Disparity in ICT Adoption: an Empirical Evaluation of The Effects of Subsidies in Italy," Working Paper CRENoS 200608, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    36. Anirban Basu & Daniel Polsky & Willard G. Manning, 2008. "Use of Propensity Scores in Non-Linear Response Models: The Case for Health Care Expenditures," NBER Working Papers 14086, National Bureau of Economic Research, Inc.
    37. Angrist, Joshua & Lavy, Victor, 2004. "The Effect of High Stakes High School Achievement Awards: Evidence from a School-Centered Randomized Trial," IZA Discussion Papers 1146, Institute of Labor Economics (IZA).
    38. Miguel Minutti‐Meza, 2013. "Does Auditor Industry Specialization Improve Audit Quality?," Journal of Accounting Research, Wiley Blackwell, vol. 51(4), pages 779-817, September.
    39. Jochmans, K., 2019. "Heteroskedasticity-Robust Inference in Linear Regression Models," Cambridge Working Papers in Economics 1957, Faculty of Economics, University of Cambridge.
    40. Brumback, Babette A., 2009. "A note on using the estimated versus the known propensity score to estimate the average treatment effect," Statistics & Probability Letters, Elsevier, vol. 79(4), pages 537-542, February.
    41. Adel Ben Khalifa, 2018. "Government Supports and Technology Adoption: Evidence from Tunisia," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 43(4), pages 41-70, December.

  39. Jinyong Hahn, 2004. "Functional Restriction and Efficiency in Causal Inference," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 73-76, February.

    Cited by:

    1. Persson, Emma & Häggström, Jenny & Waernbaum, Ingeborg & de Luna, Xavier, 2017. "Data-driven algorithms for dimension reduction in causal inference," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 280-292.
    2. Toru Kitagawa & Chris Muris, 2015. "Model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP46/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Halbert White & Karim Chalak, 2010. "Testing a Conditional Form of Exogeneity," Boston College Working Papers in Economics 733, Boston College Department of Economics.
    4. Fan, Yanqin & Guerre, Emmanuel & Zhu, Dongming, 2017. "Partial identification of functionals of the joint distribution of “potential outcomes”," Journal of Econometrics, Elsevier, vol. 197(1), pages 42-59.
    5. Pingel, Ronnie & Waernbaum, Ingeborg, 2015. "Correlation and efficiency of propensity score-based estimators for average causal effects," Working Paper Series 2015:3, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    6. Stijn Vansteelandt, 2012. "Discussions," Biometrics, The International Biometric Society, vol. 68(3), pages 675-678, September.
    7. F Richard Guo & Emilija Perković & Andrea Rotnitzky, 2023. "Variable elimination, graph reduction and the efficient g-formula," Biometrika, Biometrika Trust, vol. 110(3), pages 739-761.
    8. Ruoqi Yu, 2021. "Evaluating and improving a matched comparison of antidepressants and bone density," Biometrics, The International Biometric Society, vol. 77(4), pages 1276-1288, December.
    9. Edward H. Kennedy & Sivaraman Balakrishnan, 2018. "Discussion of “Data†driven confounder selection via Markov and Bayesian networks†by Jenny Häggström," Biometrics, The International Biometric Society, vol. 74(2), pages 399-402, June.
    10. Häggström, Jenny & Persson, Emma & Waernbaum, Ingeborg & de Luna, Xavier, 2015. "CovSel: An R Package for Covariate Selection When Estimating Average Causal Effects," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(i01).
    11. Toru Kitagawa & Chris Muris, 2013. "Covariate selection and model averaging in semiparametric estimation of treatment effects," CeMMAP working papers 61/13, Institute for Fiscal Studies.
    12. Halbert White & Karim Chalak, 2013. "Identification and Identification Failure for Treatment Effects Using Structural Systems," Econometric Reviews, Taylor & Francis Journals, vol. 32(3), pages 273-317, November.
    13. Xun Lu, 2015. "A Covariate Selection Criterion for Estimation of Treatment Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(4), pages 506-522, October.
    14. Lu, Xun & White, Halbert, 2014. "Robustness checks and robustness tests in applied economics," Journal of Econometrics, Elsevier, vol. 178(P1), pages 194-206.
    15. Leonard Henckel & Emilija Perković & Marloes H. Maathuis, 2022. "Graphical criteria for efficient total effect estimation via adjustment in causal linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 579-599, April.
    16. Chi Wang & Giovanni Parmigiani & Francesca Dominici, 2012. "Rejoinder: Bayesian Effect Estimation Accounting for Adjustment Uncertainty," Biometrics, The International Biometric Society, vol. 68(3), pages 680-686, September.
    17. David Cheng & Abhishek Chakrabortty & Ashwin N. Ananthakrishnan & Tianxi Cai, 2020. "Estimating average treatment effects with a double‐index propensity score," Biometrics, The International Biometric Society, vol. 76(3), pages 767-777, September.
    18. Farrell, Max H., 2015. "Robust inference on average treatment effects with possibly more covariates than observations," Journal of Econometrics, Elsevier, vol. 189(1), pages 1-23.
    19. Matthew Cefalu & Francesca Dominici & Nils Arvold & Giovanni Parmigiani, 2017. "Model averaged double robust estimation," Biometrics, The International Biometric Society, vol. 73(2), pages 410-421, June.
    20. Lee, Ying-Ying, 2018. "Efficient propensity score regression estimators of multivalued treatment effects for the treated," Journal of Econometrics, Elsevier, vol. 204(2), pages 207-222.
    21. Dingke Tang & Dehan Kong & Wenliang Pan & Linbo Wang, 2023. "Ultra‐high dimensional variable selection for doubly robust causal inference," Biometrics, The International Biometric Society, vol. 79(2), pages 903-914, June.
    22. Bryan Keller, 2020. "Variable Selection for Causal Effect Estimation: Nonparametric Conditional Independence Testing With Random Forests," Journal of Educational and Behavioral Statistics, , vol. 45(2), pages 119-142, April.

  40. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2004. "Estimation with weak instruments: Accuracy of higher-order bias and MSE approximations," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 272-306, June.

    Cited by:

    1. Ken Yamada, 2010. "Intertemporal Substitution in the Time Allocation of Married Women," Working Papers 27-2010, Singapore Management University, School of Economics.
    2. Ćorić, Bruno & Pugh, Geoff, 2013. "Foreign direct investment and output growth volatility: A worldwide analysis," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 260-271.
    3. Meng, Ginger & Hu, Gang & Bai, Jushan, 2007. "Olive: a simple method for estimating betas when factors are measured with error," MPRA Paper 33183, University Library of Munich, Germany.
    4. Anikó Bíró, 2013. "Subjective mortality hazard shocks and the adjustment of consumption expenditures," Journal of Population Economics, Springer;European Society for Population Economics, vol. 26(4), pages 1379-1408, October.
    5. McCord, Gordon C. & Conley, Dalton & Sachs, Jeffrey D., 2017. "Malaria ecology, child mortality & fertility," Economics & Human Biology, Elsevier, vol. 24(C), pages 1-17.
    6. Roberto Ricciuti & Antonio Savoia & Kunal Sen, 2016. "How do political institutions affect fiscal capacity? Explaining taxation in developing economies," Global Development Institute Working Paper Series esid-059-16, GDI, The University of Manchester.
    7. Woo, Jaejoon, 2011. "Growth, income distribution, and fiscal policy volatility," Journal of Development Economics, Elsevier, vol. 96(2), pages 289-313, November.
    8. Hausman, Jerry & Stock, James H. & Yogo, Motohiro, 2005. "Asymptotic properties of the Hahn-Hausman test for weak-instruments," Economics Letters, Elsevier, vol. 89(3), pages 333-342, December.
    9. Frölich, Markus & Lechner, Michael, 2004. "Regional Treatment Intensity as an Instrument for the Evaluation of Labour Market Policies," IZA Discussion Papers 1095, Institute of Labor Economics (IZA).
    10. Isaiah Andrews & Timothy B. Armstrong, 2015. "Unbiased Instrumental Variables Estimation under Known First-Stage Sign," Cowles Foundation Discussion Papers 1984R, Cowles Foundation for Research in Economics, Yale University, revised Mar 2015.
    11. Russell Davidson & James MacKinnon, 2006. "Moments Of Iv And Jive Estimators," Departmental Working Papers 2006-22, McGill University, Department of Economics.
    12. John Chao & Jerry Hausman & Whitney Newey & Norman Swanson & Tiemen Woutersen, 2013. "An Expository Note on the Existence of Moments of Fuller and HFUL Estimators," Departmental Working Papers 201311, Rutgers University, Department of Economics.
    13. Daniel Czarnowske & Amrei Stammann, 2020. "Inference in Unbalanced Panel Data Models with Interactive Fixed Effects," Papers 2004.03414, arXiv.org.
    14. Adrián Rial & Rafael Fernández, 2023. "Does tertiarisation slow down productivity growth? A Kaldorian–Baumolian analysis across 10 developed economies," Metroeconomica, Wiley Blackwell, vol. 74(1), pages 188-222, February.
    15. Sheila M. Olmstead & Hilary Sigman, 2014. "Damming the Commons: An Empirical Analysis of International Cooperation and Conflict in Dam Location," NBER Working Papers 20389, National Bureau of Economic Research, Inc.
    16. Rodrigo Alfaro, 2008. "Higher Order Properties of the Symmetricallr Normalized Instrumental Variable Estimator," Working Papers Central Bank of Chile 500, Central Bank of Chile.
    17. Alexandre Dmitriev, 2013. "Institutions and growth: evidence from estimation methods robust to weak instruments," Applied Economics, Taylor & Francis Journals, vol. 45(13), pages 1625-1635, May.
    18. James G. MacKinnon & Russell Davidson, 2006. "The case against JIVE," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 827-833.
    19. Tae Ho Eom & William Duncombe & Phuong Nguyen-Hoang & John Yinger, 2014. "The Unintended Consequences of Property Tax Relief: New York’s STAR Program," Education Finance and Policy, MIT Press, vol. 9(4), pages 446-480, October.
    20. Frölich, Markus & Lechner, Michael, 2006. "Exploiting Regional Treatment Intensity for the Evaluation of Labour Market Policies," IZA Discussion Papers 2144, Institute of Labor Economics (IZA).
    21. Jerry Hausman & Whitney K. Newey & Tiemen M. Woutersen & John Chao & Norman Swanson, 2007. "Instrumental variable estimation with heteroskedasticity and many instruments," CeMMAP working papers CWP22/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    22. Jeremy Edwards & Sheilagh Ogilvie, 2022. "Did the Black Death cause economic development by ‘inventing’ fertility restriction? [Land use and management in the upland demesne of the De Lacy estate of Blackburnshire c. 1300]," Oxford Economic Papers, Oxford University Press, vol. 74(4), pages 1228-1246.
    23. Hanushek, Eric A. & Wößmann, Ludger, 2012. "Do better schools lead to more growth? Cognitive skills, economic outcomes, and causation," Munich Reprints in Economics 20400, University of Munich, Department of Economics.
    24. Marcelo J. Moreira & Jack R. Porter & Gustavo A. Suarez, 2004. "Bootstrap and Higher-Order Expansion Validity When Instruments May Be Weak," Harvard Institute of Economic Research Working Papers 2048, Harvard - Institute of Economic Research.
    25. Ashim Kumar Kar, 2012. "Does capital and financing structure have any relevance to the performance of microfinance institutions?," International Review of Applied Economics, Taylor & Francis Journals, vol. 26(3), pages 329-348, March.
    26. Kodila-Tedika, Oasis & Khalifa, Sherif, 2020. "Leaders’ Foreign Travel and Foreign Investment Inflows," MPRA Paper 98625, University Library of Munich, Germany.
    27. Conley, Timothy G. & Hansen, Christian B. & McCulloch, Robert E. & Rossi, Peter E., 2008. "A semi-parametric Bayesian approach to the instrumental variable problem," Journal of Econometrics, Elsevier, vol. 144(1), pages 276-305, May.
    28. Bekker, Paul A. & Crudu, Federico, 2015. "Jackknife instrumental variable estimation with heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 332-342.
    29. Mari Rege & Kjetil Telle & Mark Votruba, 2007. "Social Interaction Effects in Disability Pension Participation. Evidence from Plant Downsizing," Discussion Papers 496, Statistics Norway, Research Department.
    30. Iglesias, Emma M. & Phillips, Garry D.A., 2011. "Almost Unbiased Estimation in Simultaneous Equations Models with Strong and / or Weak Instruments," Cardiff Economics Working Papers E2011/19, Cardiff University, Cardiff Business School, Economics Section.
    31. Hanushek, Eric A. & Wößmann, Ludger, 2012. "Schooling, educational achievement, and the Latin American growth puzzle," Munich Reprints in Economics 20399, University of Munich, Department of Economics.
    32. Asma Boussetta, 2022. "Microfinance, Poverty and Education," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 64(1), pages 86-108, March.
    33. Arcand, Jean-Louis & Ai, Chunrong & Ethier, Francois, 2007. "Moral hazard and Marshallian inefficiency: Evidence from Tunisia," Journal of Development Economics, Elsevier, vol. 83(2), pages 411-445, July.
    34. Donald W.K. Andrews & James H. Stock, 2005. "Inference with Weak Instruments," NBER Technical Working Papers 0313, National Bureau of Economic Research, Inc.
    35. Cosmin Ilut & Peter Benczur, 2010. "Evidence for Relational Contracts in Sovereign Bank Lending," 2010 Meeting Papers 91, Society for Economic Dynamics.
    36. Nadir ALTINOK & Abdurrahman AYDEMIR, 2017. "Does one size fit all? The impact of cognitive skills on economic growth," Working Paper fe6bac64-da74-4fe1-b551-7, Agence française de développement.
    37. Tomasz Wisniewski & Geoffrey Lightfoot & Simon Lilley, 2012. "Speculating on presidential success: exploring the link between the price–earnings ratio and approval ratings," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 106-122, January.
    38. A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012. "Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain," Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
    39. Zhen Cui & Yalan Feng, 2017. "Wealthy Hand-to-Mouth Households in China," Asian Economic Journal, East Asian Economic Association, vol. 31(3), pages 275-297, September.
    40. Marjan Petreski, 2010. "An Overhaul of a Doctrine: Has Inflation Targeting Opened a New Era in Developing-country Peggers?," FIW Working Paper series 057, FIW.
    41. Jakob Brochner Madsen & MD. Rabiul Islam & Hristos Doucouliagos, 2016. "Inequality, Financial Development and Economic Growth in the OECD, 1870-2011," Monash Economics Working Papers 18-16, Monash University, Department of Economics.
    42. Hausman, Jerry & Lewis, Randall & Menzel, Konrad & Newey, Whitney, 2011. "Properties of the CUE estimator and a modification with moments," Journal of Econometrics, Elsevier, vol. 165(1), pages 45-57.
    43. P. Dorian Owen & Stephen Knowles, 2008. "Which Institutions are Good for Your Health? The Deep Determinants of Comparative Cross-country Health Status," Working Papers 0811, University of Otago, Department of Economics, revised Dec 2008.
    44. Roberto Ricciuti & Antonio Savoia & Kunal Sen, 2019. "What determines administrative capacity in developing countries?," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 26(5), pages 972-998, October.
    45. Néstor Gandelman & Ana Balsa & Nicolás González, 2012. "Peer Effects in Risk Aversion," Development Research Working Paper Series 11/2012, Institute for Advanced Development Studies.
    46. Awaworyi Churchill, Sefa & Smyth, Russell, 2021. "Energy poverty and health: Panel data evidence from Australia," Energy Economics, Elsevier, vol. 97(C).
    47. Korpi, Tomas & Tåhlin, Michael, 2009. "Educational mismatch, wages, and wage growth: Overeducation in Sweden, 1974-2000," Labour Economics, Elsevier, vol. 16(2), pages 183-193, April.
    48. Korpi, Tomas & Tåhlin, Michael, 2007. "Educational mismatch, wages, and wage growth: Overeducation in Sweden, 1974-2000," Working Paper Series 10/2007, Stockholm University, Swedish Institute for Social Research.
    49. Katsushi S. Imai & Raghav Gaiha & Constanza Di Nucci, 2014. "Agricultural Employment, Wages and Poverty in Developing Countries," Global Development Institute Working Paper Series 20914, GDI, The University of Manchester.
    50. Aleksandra Rutkowska & Magdalena Szyszko, 2022. "New DTW Windows Type for Forward- and Backward-Lookingness Examination. Application for Inflation Expectation," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 701-718, February.
    51. Ephraim Kwashie Thompson & Changki Kim, 2020. "Post-M&A Performance and Failure: Implications of Time until Deal Completion," Sustainability, MDPI, vol. 12(7), pages 1-31, April.
    52. Yong Bao & Aman Ullah, 2021. "Analytical Finite Sample Econometrics: From A. L. Nagar to Now," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 17-37, December.
    53. Natalia Khorunzhina, 2019. "Intratemporal nonseparability between housing and nondurable consumption: evidence from reinvestment in housing stock," CESifo Working Paper Series 7663, CESifo.
    54. Simon Wiederhold, 2012. "The Role of Public Procurement in Innovation: Theory and Empirical Evidence," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 43.
    55. Nguyen-Hoang, Phuong & Yeung, Ryan, 2010. "What is paratransit worth?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(10), pages 841-853, December.
    56. Attanasio, O. & Levell, P. & Low, H. & Sanchez-Marcos, V., 2017. "Aggregating Elasticities: Intensive and Extensive Margins of Female Labour Supply," Cambridge Working Papers in Economics 1711, Faculty of Economics, University of Cambridge.
    57. Bonleu, A. & Cette, G. & Horny, G., 2011. "Capital Utilisation and Retirement," Working papers 343, Banque de France.
    58. Lei Bill Wang, 2023. "Estimating overidentified linear models with heteroskedasticity and outliers," Papers 2305.17615, arXiv.org, revised Apr 2024.
    59. Martin Emil Jakobsen & Jonas Peters, 2020. "Distributional robustness of K-class estimators and the PULSE," Papers 2005.03353, arXiv.org, revised Mar 2022.
    60. Kwak, Sungil, 2011. "The Impact of Taxes on Charitable Giving: Empirical Evidence from the Korean Labor and Income Panel Study," MPRA Paper 36845, University Library of Munich, Germany.
    61. Peter Claeys & Luis Costa, 2012. "“A Note on the Relationship Between the Cyclicality of Markups and Fiscal Policy”," AQR Working Papers 201208, University of Barcelona, Regional Quantitative Analysis Group, revised Sep 2012.
    62. Matsushita, Yukitoshi & Otsu, Taisuke, 2023. "Second-order refinements for t-ratios with many instruments," Journal of Econometrics, Elsevier, vol. 232(2), pages 346-366.
    63. Puertas, Rosa & Guaita-Martinez, José M. & Marti, Luisa, 2023. "Analysis of the impact of university policies on society's environmental perception," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    64. Rogelio Mercado Jr., 2017. "Are Capital Inflows Expansionary or Contractionary in the Philippines?," Working Papers wp27, South East Asian Central Banks (SEACEN) Research and Training Centre.
    65. Johannes Rincke & Christian Traxler, 2009. "Deterrence through Word of Mouth," CESifo Working Paper Series 2549, CESifo.
    66. Zongwu Cai & Ying Fang & Henong Li, 2012. "Weak Instrumental Variables Models for Longitudinal Data," Econometric Reviews, Taylor & Francis Journals, vol. 31(4), pages 361-389.
    67. John Chao & Norman R. Swanson, 2003. "Alternative Approximations of the Bias and MSE of the IV Estimator under Weak Identification with an Application to Bias Correction," Cowles Foundation Discussion Papers 1418, Cowles Foundation for Research in Economics, Yale University.
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    69. Syed Mansoob Murshed & Muhammad Badiuzzaman & Mohammad Habibullah Pulok, 2017. "Fiscal capacity and social protection expenditure in developing nations," WIDER Working Paper Series wp-2017-60, World Institute for Development Economic Research (UNU-WIDER).
    70. José María Durán-Cabré & Alejandro Esteller-Moré & Luca Salvadori, 2012. "Empirical evidence on horizontal competition in tax enforcement," Working Papers 2012/5, Institut d'Economia de Barcelona (IEB).
    71. Matsushita, Yukitoshi & Otsu, Taisuke, 2022. "A jackknife Lagrange multiplier test with many weak instruments," LSE Research Online Documents on Economics 116392, London School of Economics and Political Science, LSE Library.
    72. Ferede, Ergete & Dahlby, Bev, 2012. "The Impact of Tax Cuts on Economic Growth: Evidence From the Canadian Provinces," National Tax Journal, National Tax Association;National Tax Journal, vol. 65(3), pages 563-594, September.
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    74. Michael P. Murray, 2006. "Avoiding Invalid Instruments and Coping with Weak Instruments," Journal of Economic Perspectives, American Economic Association, vol. 20(4), pages 111-132, Fall.
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    76. Murray Michael P., 2017. "Linear Model IV Estimation When Instruments Are Many or Weak," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
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    78. Xuexin WANG, 2021. "Instrumental variable estimation via a continuum of instruments with an application to estimating the elasticity of intertemporal substitution in consumption," Working Papers 2021-11-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
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    241. Westerlund, Joakim & Norkute, Milda, 2014. "A Factor Analytical Method to Interactive Effects Dynamic Panel Models with or without Unit Root," Working Papers 2014:12, Lund University, Department of Economics.
    242. Kazuhiko Hayakawa, 2007. "Consistent OLS estimation of AR(1) dynamic panel data models with short time series," Applied Economics Letters, Taylor & Francis Journals, vol. 14(15), pages 1141-1145.
    243. Kazuhiko Hayakawa, 2008. "On the Effect of Nonstationary Initial Conditions in Dynamic Panel Data Models," Hi-Stat Discussion Paper Series d07-245, Institute of Economic Research, Hitotsubashi University.
    244. Giles John & Murtazashvili Irina, 2013. "A Control Function Approach to Estimating Dynamic Probit Models with Endogenous Regressors," Journal of Econometric Methods, De Gruyter, vol. 2(1), pages 69-87, July.
    245. Golodniuk, Inna, 2006. "Evidence on the bank-lending channel in Ukraine," Research in International Business and Finance, Elsevier, vol. 20(2), pages 180-199, June.
    246. Juanjuan Zhuo & Masao Kumamoto, 2020. "Stock market reactions to COVID-19 and containment policies: A panel VAR approach," Economics Bulletin, AccessEcon, vol. 40(4), pages 3296-3305.
    247. Kruiniger, Hugo, 2008. "Maximum likelihood estimation and inference methods for the covariance stationary panel AR(1)/unit root model," Journal of Econometrics, Elsevier, vol. 144(2), pages 447-464, June.
    248. Carbajal-De-Nova, Carolina & Venegas-Martínez, Francisco, 2019. "Synthetic Estimation of Dynamic Panel Models When Either N or T or Both Are Not Large: Bias Decomposition in Systematic and Random Components," MPRA Paper 94405, University Library of Munich, Germany.
    249. Stéphane Bonhomme & Kevin Dano & Bryan S. Graham, 2023. "Identification in a binary choice panel data model with a predetermined covariate," CeMMAP working papers 17/23, Institute for Fiscal Studies.
    250. Andreas Dzemski & Ryo Okui, 2017. "Confidence set for group membership," Papers 1801.00332, arXiv.org, revised Nov 2023.
    251. Geert Dhaene & Martin Weidner, 2023. "Approximate Functional Differencing," Papers 2301.13736, arXiv.org, revised May 2023.
    252. Jeong, Hanbat & Lee, Lung-fei, 2020. "Spatial dynamic models with intertemporal optimization: Specification and estimation," Journal of Econometrics, Elsevier, vol. 218(1), pages 82-104.
    253. Breitung, Jörg & Kripfganz, Sebastian & Hayakawa, Kazuhiko, 2022. "Bias-corrected method of moments estimators for dynamic panel data models," Econometrics and Statistics, Elsevier, vol. 24(C), pages 116-132.
    254. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
    255. Juodis, Artūras & Poldermans, Rutger W., 2021. "Backward mean transformation in unit root panel data models," Economics Letters, Elsevier, vol. 201(C).

  43. Hahn, Jinyong, 2002. "Optimal Inference With Many Instruments," Econometric Theory, Cambridge University Press, vol. 18(1), pages 140-168, February.

    Cited by:

    1. Frölich, Markus & Lechner, Michael, 2004. "Regional Treatment Intensity as an Instrument for the Evaluation of Labour Market Policies," IZA Discussion Papers 1095, Institute of Labor Economics (IZA).
    2. Chao & Swanson & Hausman & Newey & Woutersen, 2010. "Asymptotic Distribution of JIVE in a Heteroskedastic IV Regression with Many Instruments," Economics Working Paper Archive 567, The Johns Hopkins University,Department of Economics.
    3. Anderson, T.W. & Kunitomo, Naoto & Matsushita, Yukitoshi, 2010. "On the asymptotic optimality of the LIML estimator with possibly many instruments," Journal of Econometrics, Elsevier, vol. 157(2), pages 191-204, August.
    4. Bekker, Paul A. & Crudu, Federico, 2015. "Jackknife instrumental variable estimation with heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 332-342.
    5. Donald W.K. Andrews & James H. Stock, 2005. "Inference with Weak Instruments," NBER Technical Working Papers 0313, National Bureau of Economic Research, Inc.
    6. Stanislav Anatolyev, 2005. "Optimal Instruments in Time Series: A Survey," Working Papers w0069, Center for Economic and Financial Research (CEFIR).
    7. A. Belloni & D. Chen & V. Chernozhukov & C. Hansen, 2012. "Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain," Econometrica, Econometric Society, vol. 80(6), pages 2369-2429, November.
    8. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2008. "A Shrinkage Instrumental Variable Estimator for Large Datasets," Working Papers 626, Queen Mary University of London, School of Economics and Finance.
    9. Kuanhao Jiang & Rajarshi Mukherjee & Subhabrata Sen & Pragya Sur, 2022. "A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-Fit Covariance and Beyond," Papers 2205.10198, arXiv.org, revised Oct 2022.
    10. Shi, Zhentao, 2016. "Econometric estimation with high-dimensional moment equalities," Journal of Econometrics, Elsevier, vol. 195(1), pages 104-119.
    11. Shane M. Sherlund, 2004. "Quasi Empirical Likelihood Estimation of Moment Condition Models," Econometric Society 2004 North American Summer Meetings 507, Econometric Society.
    12. Kolesár, Michal, 2018. "Minimum distance approach to inference with many instruments," Journal of Econometrics, Elsevier, vol. 204(1), pages 86-100.
    13. Michal Kolesár & Raj Chetty & John N. Friedman & Edward L. Glaeser & Guido W. Imbens, 2011. "Identification and Inference with Many Invalid Instruments," NBER Working Papers 17519, National Bureau of Economic Research, Inc.
    14. Xuexin WANG, 2021. "Instrumental variable estimation via a continuum of instruments with an application to estimating the elasticity of intertemporal substitution in consumption," Working Papers 2021-11-06, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    15. Cattaneo, Matias D. & Crump, Richard K. & Jansson, Michael, 2012. "Optimal inference for instrumental variables regression with non-Gaussian errors," Journal of Econometrics, Elsevier, vol. 167(1), pages 1-15.
    16. Kapetanios, George & Marcellino, Massimiliano, 2010. "Cross-sectional averaging and instrumental variable estimation with many weak instruments," Economics Letters, Elsevier, vol. 108(1), pages 36-39, July.
    17. Tae-Hyoung Tommy Gim, 2016. "Testing the Reciprocal Relationship between Attitudes and Land Use in Relation to Trip Frequencies," International Regional Science Review, , vol. 39(2), pages 203-227, April.
    18. Sølvsten, Mikkel, 2020. "Robust estimation with many instruments," Journal of Econometrics, Elsevier, vol. 214(2), pages 495-512.
    19. Bekker, Paul A. & Crudu, Federico, 2012. "Symmetric Jackknife Instrumental Variable Estimation," MPRA Paper 37853, University Library of Munich, Germany.
    20. Norman R. Swanson & John C. Chao, 2004. "Estimation and Testing Using Jackknife IV in Heteroskedastic Regressions with Many Weak Instruments," Econometric Society 2004 Far Eastern Meetings 668, Econometric Society.
    21. Haruo Iwakura, 2014. "Deriving the Information Bounds for Nonlinear Panel Data Models with Fixed Effects," KIER Working Papers 886, Kyoto University, Institute of Economic Research.
    22. Kazuhiko Hayakawa, 2006. "Efficient GMM Estimation of Dynamic Panel Data Models Where Large Heterogeneity May Be Present," Hi-Stat Discussion Paper Series d05-130, Institute of Economic Research, Hitotsubashi University.
    23. Wayne Yuan Gao & Rui Wang, 2023. "IV Regressions without Exclusion Restrictions," Papers 2304.00626, arXiv.org, revised Jul 2023.

  44. Hahn, Jinyong & Hausman, Jerry, 2002. "Notes on bias in estimators for simultaneous equation models," Economics Letters, Elsevier, vol. 75(2), pages 237-241, April.

    Cited by:

    1. Ćorić, Bruno & Pugh, Geoff, 2013. "Foreign direct investment and output growth volatility: A worldwide analysis," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 260-271.
    2. Jean-Marie Dufour, 2003. "Identification, Weak Instruments and Statistical Inference in Econometrics," CIRANO Working Papers 2003s-49, CIRANO.
    3. Maurice Bun & Frank Windmeijer, 2010. "A comparison of bias approximations for the 2SLS estimator," CeMMAP working papers CWP07/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Kruiniger, Hugo, 2009. "Gmm Estimation And Inference In Dynamic Panel Data Models With Persistent Data," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1348-1391, October.
    5. Léandre BASSOLE & Jean-Louis ARCAND, 2006. "Does Community Driven Development Work? Evidence from Senegal," Working Papers 200606, CERDI.
    6. Economou, Athina & Theodossiou, Ioannis, 2010. "Poor and Sick: Estimating the relationship between Household Income and Health," SIRE Discussion Papers 2010-121, Scottish Institute for Research in Economics (SIRE).
    7. Maurice J.G. Bun & Frank Windmeijer, 2009. "The Weak Instrument Problem of the System GMM Estimator in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 09-086/4, Tinbergen Institute.
    8. Iglesias, Emma M. & Phillips, Garry D.A., 2011. "Almost Unbiased Estimation in Simultaneous Equations Models with Strong and / or Weak Instruments," Cardiff Economics Working Papers E2011/19, Cardiff University, Cardiff Business School, Economics Section.
    9. Arcand, Jean-Louis & Ai, Chunrong & Ethier, Francois, 2007. "Moral hazard and Marshallian inefficiency: Evidence from Tunisia," Journal of Development Economics, Elsevier, vol. 83(2), pages 411-445, July.
    10. Abonazel, Mohamed R., 2016. "Bias Correction Methods for Dynamic Panel Data Models with Fixed Effects," MPRA Paper 72587, University Library of Munich, Germany.
    11. James Lomas & Stephen Martin & Karl Claxton, 2018. "Estimating the marginal productivity of the English National Health Service from 2003/04 to 2012/13," Working Papers 158cherp, Centre for Health Economics, University of York.
    12. Takaaki Masaki, 2016. "The impact of intergovernmental transfers on local revenue generation in Africa: Evidence from Tanzania," WIDER Working Paper Series wp-2016-113, World Institute for Development Economic Research (UNU-WIDER).
    13. Maite Blázquez & Elena Cottini & Ainhoa Herrarte, 2014. "The socioeconomic gradient in health: how important is material deprivation?," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(2), pages 239-264, June.
    14. Hiroko Okudaira, 2009. "The Economic Costs of Court Decisions Concerning Dismissals in Japan: Identification by Judge Transfers," ISER Discussion Paper 0733r, Institute of Social and Economic Research, Osaka University, revised Sep 2015.
    15. Christopher Khawand, 2015. "Air Quality, Mortality, and Perinatal Health: Causal Evidence from Wildfires," 2015 Papers pkh318, Job Market Papers.
    16. Phillips, Garry David Alan & Wang, Dandan, 2019. "Bias assessment and reduction for the 2SLS estimator in general dynamic simultaneous equations models," DES - Working Papers. Statistics and Econometrics. WS 28322, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Nicola Matteucci & Raffaella Santolini & Silvio Di Fabio, 2023. "ICT diffusion in public administrations and business dynamics: Evidence from Italian municipalities," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 94(4), pages 1233-1271, December.
    18. Arcand, Jean-Louis & d'Hombres, Beatrice, 2006. "Testing for Separation in Agricultural Household Models and Unobservable Household-Specific Effects," MPRA Paper 1863, University Library of Munich, Germany.
    19. John Chao & Norman R. Swanson, 2003. "Alternative Approximations of the Bias and MSE of the IV Estimator under Weak Identification with an Application to Bias Correction," Cowles Foundation Discussion Papers 1418, Cowles Foundation for Research in Economics, Yale University.
    20. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/generalized method of moments estimation and testing," Stata Journal, StataCorp LP, vol. 7(4), pages 465-506, December.
    21. Jean-Louis Arcand & Jean-Pierre Tranchant, 2012. "Institutions, Mobilization and Rebellion in Post-Colonial Societies," HiCN Working Papers 133, Households in Conflict Network.
    22. Jean-Louis Arcand & Marcel Dagenais, 2011. "Errors in Variables and the Empirics of Economic Growth," Working Papers halshs-00564683, HAL.
    23. Domadenik, Polona & Prašnikar, Janez & Svejnar, Jan, 2007. "How to Increase R&D in Transition Economies? Evidence from Slovenia," IZA Discussion Papers 2801, Institute of Labor Economics (IZA).
    24. Namhyun Kim & Winfried Pohlmeier, 2016. "A Note on the Regularized Approach to Biased 2SLS Estimation with Weak Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(6), pages 915-924, December.
    25. Daniel A. Ackerberg & Paul J. Devereux, 2008. "Improved Jive Estimators for Overidentified Linear Models with and without Heteroskedasticity," Working Papers 200817, School of Economics, University College Dublin.
    26. McDonough, Ian K. & Millimet, Daniel L., 2016. "Missing Data, Imputation, and Endogeneity," IZA Discussion Papers 10402, Institute of Labor Economics (IZA).
    27. Theodossiou, I. & Zangelidis, A., 2009. "The social gradient in health: The effect of absolute income and subjective social status assessment on the individual's health in Europe," Economics & Human Biology, Elsevier, vol. 7(2), pages 229-237, July.
    28. Jones A.M & Rice N, 2009. "Econometric Evaluation of Health Policies," Health, Econometrics and Data Group (HEDG) Working Papers 09/09, HEDG, c/o Department of Economics, University of York.
    29. Romanos Priftis & Anastasia Theofilakou, 2021. "Growth effects of corporate balance sheet adjustments in the EU," Empirical Economics, Springer, vol. 60(2), pages 773-801, February.
    30. Bun, Maurice J.G. & Windmeijer, Frank, 2011. "A comparison of bias approximations for the two-stage least squares (2SLS) estimator," Economics Letters, Elsevier, vol. 113(1), pages 76-79, October.
    31. Robert H. Chenhall & Frank Moers, 2007. "The Issue of Endogeneity within Theory-Based, Quantitative Management Accounting Research," European Accounting Review, Taylor & Francis Journals, vol. 16(1), pages 173-196.
    32. Shakil, Golam Saroare & Marsh, Thomas L., 2021. "One Instrument to Rule Them All?," 2021 Annual Meeting, August 1-3, Austin, Texas 314047, Agricultural and Applied Economics Association.
    33. Elizabeth Asiedu & Yi Jin & Boaz Nandwa, 2009. "Does Foreign Aid Mitigate the Adverse Effect of Expropriation Risk on Foreign Direct Investment?," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 200905, University of Kansas, Department of Economics.
    34. Dufour, Jean-Marie & Taamouti, Mohamed, 2007. "Further results on projection-based inference in IV regressions with weak, collinear or missing instruments," Journal of Econometrics, Elsevier, vol. 139(1), pages 133-153, July.
    35. Matthew C. Harding & Jerry Hausman & Christopher Palmer, 2015. "Finite sample bias corrected IV estimation for weak and many instruments," CeMMAP working papers CWP41/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    36. Arif A. Mamun, 2006. "The White Picket Fence Dream: Effects of Assets on the Choice of Family Union," Mathematica Policy Research Reports 01ccaca54ad44dc89c4f3f393, Mathematica Policy Research.
    37. Ichida, Yukinobu & Hirai, Hiroshi & Kondo, Katsunori & Kawachi, Ichiro & Takeda, Tokunori & Endo, Hideki, 2013. "Does social participation improve self-rated health in the older population? A quasi-experimental intervention study," Social Science & Medicine, Elsevier, vol. 94(C), pages 83-90.
    38. Escobar Gamboa, Octavio Romano, 2009. "IDE entrants, exportations et productivité manufacturière : les différentes performances des régions mexicaines," Economics Thesis from University Paris Dauphine, Paris Dauphine University, number 123456789/3850 edited by Guillochon, Bernard.
    39. Alfonso Flores-Lagunes, 2007. "Finite sample evidence of IV estimators under weak instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 677-694.
    40. Nam-Hyun Kim & Winfried Pohlmeier, 2015. "A Regularization Approach to Biased Two-Stage Least Squares Estimation," Working Paper series 15-22, Rimini Centre for Economic Analysis.
    41. DUFOUR, Jean-Marie & TAAMOUTI, Mohamed, 2003. "Projection-Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments," Cahiers de recherche 08-2003, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    42. P. Dorian Owen, 2017. "Evaluating Ingenious Instruments for Fundamental Determinants of Long-Run Economic Growth and Development," Econometrics, MDPI, vol. 5(3), pages 1-33, September.
    43. Marco Fugazza & Frédéric Robert-Nicoud, 2012. "The ‘Emulator Effect’ Of The Uruguay Round On United States Regionalism," UNCTAD Blue Series Papers 51, United Nations Conference on Trade and Development.
    44. Barnes Michael G & Smith Trenton G., 2009. "Tobacco Use as Response to Economic Insecurity: Evidence from the National Longitudinal Survey of Youth," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 9(1), pages 1-29, November.
    45. Ng Serena & Bai Jushan, 2009. "Selecting Instrumental Variables in a Data Rich Environment," Journal of Time Series Econometrics, De Gruyter, vol. 1(1), pages 1-34, April.
    46. Millimet, Daniel L., 2015. "Covariate measurement and endogeneity," Economics Letters, Elsevier, vol. 136(C), pages 59-63.
    47. Phillips, Garry D.A. & Liu-Evans, Gareth, 2016. "Approximating and reducing bias in 2SLS estimation of dynamic simultaneous equation models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 734-762.
    48. Nam, Hyun-Jung & Bang, Jeongseok & Ryu, Doojin, 2023. "Do financial and governmental institutions play a mediating role in the spillover effects of FDI?," Journal of Multinational Financial Management, Elsevier, vol. 69(C).
    49. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/GMM estimation and testing," Boston College Working Papers in Economics 667, Boston College Department of Economics, revised 05 Sep 2007.
    50. Garry Phillips & Emma Iglesias, 2004. "The estimation of simultaneous equation models under conditional heteroscedasticity," Econometric Society 2004 Latin American Meetings 91, Econometric Society.
    51. Octavio Escobar, 2011. "The location pattern of FDI in Mexico after NAFTA," ERSA conference papers ersa10p804, European Regional Science Association.
    52. Berkowitz, Daniel & Jackson, John E., 2006. "Entrepreneurship and the evolution of income distributions in Poland and Russia," Journal of Comparative Economics, Elsevier, vol. 34(2), pages 338-356, June.
    53. Kazuhiko Hayakawa, 2005. "Small Sample Bias Propreties of the System GMM Estimator in Dynamic Panel Data Models," Hi-Stat Discussion Paper Series d05-82, Institute of Economic Research, Hitotsubashi University.
    54. Garry Phillips & Emma Iglesias, 2004. "Simultaneous Equations and Weak Instruments under Conditionally Heteroscedastic Disturbances," Econometric Society 2004 Far Eastern Meetings 567, Econometric Society.
    55. Sawada, Yasuyuki & Ishii, Takaharu, 2012. "Do Community-Managed Schools Facilitate Social Capital Accumulation? Evidence from the COGES Project in Burkina Faso," Working Papers 42, JICA Research Institute.
    56. Battiston, Diego, 2013. "The impact of immigration on the labour market: Evidence from 20 years of cross-border migration to Argentina," MPRA Paper 52424, University Library of Munich, Germany.
    57. Okudaira, Hiroko, 2018. "The economic costs of court decisions concerning dismissals in Japan: Identification by judge transfers," International Review of Law and Economics, Elsevier, vol. 53(C), pages 60-75.
    58. Nabamita Dutta & Peter T. Leeson & Claudia R. Williamson, 2013. "The Amplification Effect: Foreign Aid's Impact on Political Institutions," Kyklos, Wiley Blackwell, vol. 66(2), pages 208-228, May.

  45. Kezdi, Gabor & Hahn, Jinyong & Solon, Gary, 2002. "Jackknife minimum distance estimation," Economics Letters, Elsevier, vol. 76(1), pages 35-45, June.

    Cited by:

    1. Horn, Dániel & Lindner, Attila, 2022. "Kézdi Gábor (1971-2021) [Gábor Kézdi (1971-2021)]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(11), pages 1245-1254.
    2. Jeffrey M. Wooldridge, 2004. "Estimating average partial effects under conditional moment independence assumptions," CeMMAP working papers CWP03/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Magnac, Thierry & Roux, Sébastien, 2007. "Dynamique des salaires dans une cohorte," IDEI Working Papers 436, Institut d'Économie Industrielle (IDEI), Toulouse.
    4. Michael Creel & Dennis Kristensen, "undated". "Indirect Likelihood Inference," Working Papers 558, Barcelona School of Economics.
    5. Whitney K. Newey & Richard Smith, 2003. "Higher order properties of GMM and generalised empirical likelihood estimators," CeMMAP working papers CWP04/03, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Zhang, Rui & Shonkwiler, J. Scott, 2017. "Bias Correction of Welfare measures in Non-Market Valuation: Comparison of the Delta Method, Jackknife and Bootstrap," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258099, Agricultural and Applied Economics Association.

  46. Jinyong Hahn & Atsushi Inoue, 2002. "A Monte Carlo Comparison Of Various Asymptotic Approximations To The Distribution Of Instrumental Variables Estimators," Econometric Reviews, Taylor & Francis Journals, vol. 21(3), pages 309-336.

    Cited by:

    1. Paul A. Bekker & Jan van der Ploeg, 2000. "Instrumental Variable Estimation Based on Grouped Data," Econometric Society World Congress 2000 Contributed Papers 1862, Econometric Society.
    2. John Chao & Norman Swanson, 2004. "Consistent Estimation with a Large Number of Weak Instruments," Departmental Working Papers 200421, Rutgers University, Department of Economics.
    3. Jerry Hausman & Whitney K. Newey & Tiemen M. Woutersen & John Chao & Norman Swanson, 2007. "Instrumental variable estimation with heteroskedasticity and many instruments," CeMMAP working papers CWP22/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Carrasco, Marine & Tchuente, Guy, 2015. "Regularized LIML for many instruments," Journal of Econometrics, Elsevier, vol. 186(2), pages 427-442.
    5. Bekker, Paul A. & Crudu, Federico, 2015. "Jackknife instrumental variable estimation with heteroskedasticity," Journal of Econometrics, Elsevier, vol. 185(2), pages 332-342.
    6. Park, Albert & Brandt, Loren & Giles, John, 2003. "Competition under credit rationing: theory and evidence from rural China," Journal of Development Economics, Elsevier, vol. 71(2), pages 463-495, August.
    7. Neil Kellard & Denise Osborn & Jerry Coakley & Alastair R. Hall & Denise R. Osborn & Nikolaos Sakkas, 2015. "Structural Break Inference Using Information Criteria in Models Estimated by Two-Stage Least Squares," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 741-762, September.
    8. Abutaliev, Albert & Anatolyev, Stanislav, 2013. "Asymptotic variance under many instruments: Numerical computations," Economics Letters, Elsevier, vol. 118(2), pages 272-274.
    9. Hall, Alastair R. & Han, Sanggohn & Boldea, Otilia, 2012. "Inference regarding multiple structural changes in linear models with endogenous regressors," Journal of Econometrics, Elsevier, vol. 170(2), pages 281-302.
    10. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    11. Christl, Michael & Köppl Turyna, Monika & Kucsera, Denes, 2015. "Employment effects of minimum wages in Europe revisited," MPRA Paper 65761, University Library of Munich, Germany.
    12. John Chao & Norman R. Swanson, 2003. "Alternative Approximations of the Bias and MSE of the IV Estimator under Weak Identification with an Application to Bias Correction," Cowles Foundation Discussion Papers 1418, Cowles Foundation for Research in Economics, Yale University.
    13. Christian Hansen & Jerry Hausman & Whitney K. Newey, 2006. "Estimation with many instrumental variables," CeMMAP working papers CWP19/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    14. Murray Michael P., 2017. "Linear Model IV Estimation When Instruments Are Many or Weak," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    15. Richard Startz & Charles Nelson & Eric Zivot, 1999. "Improved Inference for the Instrumental Variable Estimator," Working Papers 0039, University of Washington, Department of Economics.
    16. Hall, Alastair R. & Han, Sanggohn & Boldea, Otilia, 2008. "Asymptotic Distribution Theory for Break Point Estimators in Models Estimated via 2SLS," MPRA Paper 9472, University Library of Munich, Germany.
    17. Otilia Boldea & Alastair Hall & Sanggohn Han, 2010. "Uncertainty, Entrepreneurship and the Organisation of Corruption," Centre for Growth and Business Cycle Research Discussion Paper Series 134, Economics, The University of Manchester.
    18. Joura, Essam & Xiao, Qin & Ullah, Subhan, 2021. "The impact of Say-on-Pay votes on firms' strategic policies: Insights from the Anglo-Saxon economy," International Review of Financial Analysis, Elsevier, vol. 73(C).
    19. Jan F. KIVIET & Jerzy NIEMCZYK, 2013. "On the limiting and empirical distributions of IV estimators when some of the instruments are actually endogenous," Economic Growth Centre Working Paper Series 1311, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    20. Bekker, Paul A. & Crudu, Federico, 2012. "Symmetric Jackknife Instrumental Variable Estimation," MPRA Paper 37853, University Library of Munich, Germany.
    21. Kweh, Qian Long & Tebourbi, Imen & Lo, Huai-Chun & Huang, Cheng-Tsu, 2022. "CEO compensation and firm performance: Evidence from financially constrained firms," Research in International Business and Finance, Elsevier, vol. 61(C).
    22. Christl Michael & Köppl-Turyna Monika & Kucsera Dénes, 2018. "Revisiting the Employment Effects of Minimum Wages in Europe," German Economic Review, De Gruyter, vol. 19(4), pages 426-465, December.
    23. Hall, Alastair R. & Han, Sanggohn & Boldea, Otilia, 2008. "Inference regarding multiple structural changes in linear models estimated via two stage least squares," MPRA Paper 9251, University Library of Munich, Germany, revised 20 Jun 2008.
    24. Kazuhiko Hayakawa, 2006. "Efficient GMM Estimation of Dynamic Panel Data Models Where Large Heterogeneity May Be Present," Hi-Stat Discussion Paper Series d05-130, Institute of Economic Research, Hitotsubashi University.
    25. Kiviet, Jan F. & Niemczyk, Jerzy, 2007. "The asymptotic and finite sample distributions of OLS and simple IV in simultaneous equations," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3296-3318, April.

  47. Jinyong Hahn & Jerry Hausman, 2002. "A New Specification Test for the Validity of Instrumental Variables," Econometrica, Econometric Society, vol. 70(1), pages 163-189, January.
    See citations under working paper version above.
  48. Hahn, Jinyong & Kuersteiner, Guido, 2002. "Discontinuities of weak instrument limiting distributions," Economics Letters, Elsevier, vol. 75(3), pages 325-331, May.

    Cited by:

    1. Caner, Mehmet, 2014. "Near exogeneity and weak identification in generalized empirical likelihood estimators: Many moment asymptotics," Journal of Econometrics, Elsevier, vol. 182(2), pages 247-268.
    2. John Chao & Norman Swanson, 2004. "Consistent Estimation with a Large Number of Weak Instruments," Departmental Working Papers 200421, Rutgers University, Department of Economics.
    3. Maurice Bun & Frank Windmeijer, 2010. "A comparison of bias approximations for the 2SLS estimator," CeMMAP working papers CWP07/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Donna Feir & Thomas Lemieux & Vadim Marmer, 2016. "Weak Identification in Fuzzy Regression Discontinuity Designs," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(2), pages 185-196, April.
    5. Maurice J.G. Bun & Frank Windmeijer, 2009. "The Weak Instrument Problem of the System GMM Estimator in Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 09-086/4, Tinbergen Institute.
    6. Mehmet Caner, 2005. "Higher Order Expansions in GMM with Nearly Weak and Many Nearly Weak Instruments," Working Paper 209, Department of Economics, University of Pittsburgh, revised Jan 2005.
    7. David T. Frazier & Eric Renault & Lina Zhang & Xueyan Zhao, 2020. "Weak Identification in Discrete Choice Models," Papers 2011.06753, arXiv.org, revised Jan 2021.
    8. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
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    1045. Reader, Mary, 2023. "The infant health effects of starting universal child benefits in pregnancy: Evidence from England and Wales," Journal of Health Economics, Elsevier, vol. 89(C).
    1046. Erasmo Giambona & Rafael P. Ribas, 2023. "Unveiling the Price of Obscenity: Evidence From Closing Prostitution Windows in Amsterdam," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(3), pages 677-705, June.
    1047. Burgert, Derik, 2005. "The Impact of German Job Protection Legislation on Job Creation in Small Establishments - An Application of the Regression Discontinuity Design," MPRA Paper 5971, University Library of Munich, Germany.
    1048. Deborah A. Cobb‐Clark & Thomas Crossley, 2003. "Econometrics for Evaluations: An Introduction to Recent Developments," The Economic Record, The Economic Society of Australia, vol. 79(247), pages 491-511, December.
    1049. Lei, Yiyuan & Ozbay, Kaan, 2021. "A robust analysis of the impacts of the stay-at-home policy on taxi and Citi Bike usage: A case study of Manhattan," Transport Policy, Elsevier, vol. 110(C), pages 487-498.
    1050. Figlio, David & Holden, Kristian L. & Ozek, Umut, 2018. "Do students benefit from longer school days? Regression discontinuity evidence from Florida's additional hour of literacy instruction," Economics of Education Review, Elsevier, vol. 67(C), pages 171-183.
    1051. Crespo Cristian, 2020. "Beyond Manipulation: Administrative Sorting in Regression Discontinuity Designs," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 164-181, January.

  50. Hahn, Jinyong, 2001. "Consistent estimation of the random structural coefficient distribution from the linear simultaneous equations system," Economics Letters, Elsevier, vol. 73(2), pages 227-231, November.

    Cited by:

    1. Alla Koblyakova & Larisa Fleishman & Orly Furman, 2022. "Accuracy of Households’ Dwelling Valuations, Housing Demand and Mortgage Decisions: Israeli Case," The Journal of Real Estate Finance and Economics, Springer, vol. 65(1), pages 48-74, July.

  51. Hahn, Jinyong, 2001. "Comment: Binary Regressors in Nonlinear Panel-Data Models with Fixed Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 16-17, January.

    Cited by:

    1. Bryan S. Graham & James Powell, 2008. "Identification and Estimation of 'Irregular' Correlated Random Coefficient Models," NBER Working Papers 14469, National Bureau of Economic Research, Inc.
    2. Victor Chernozhukov & Ivan Fernandez-Val & Jinyong Hahn & Whitney K. Newey, 2009. "Identification and estimation of marginal effects in nonlinear panel models," CeMMAP working papers CWP05/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Damien de Walque, 2010. "Education, Information and Smoking Decisions: Evidence from Smoking Histories in the United States, 1940–2000," Journal of Human Resources, University of Wisconsin Press, vol. 45(3).
    4. Jeffrey M. Wooldridge, 2004. "On the robustness of fixed effects and related estimators in correlated random coefficient panel data models," CeMMAP working papers CWP04/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. David Autor & Mark Duggan & Jonathan Gruber, 2014. "Moral Hazard and Claims Deterrence in Private Disability Insurance," American Economic Journal: Applied Economics, American Economic Association, vol. 6(4), pages 110-141, October.
    6. Fernández-Val, Iván & Vella, Francis, 2011. "Bias corrections for two-step fixed effects panel data estimators," Journal of Econometrics, Elsevier, vol. 163(2), pages 144-162, August.
    7. Peter Hull, 2018. "Estimating Treatment Effects in Mover Designs," Papers 1804.06721, arXiv.org.
    8. Victor Aguirregabiria & Jesus M. Carro, 2021. "Identification of Average Marginal Effects in Fixed Effects Dynamic Discrete Choice Models," Papers 2107.06141, arXiv.org.
    9. Ivan Fernandez-Val, 2005. "Estimation of Structural Parameters and Marginal Effects in Binary Choice Panel Data Models with Fixed Effects," Boston University - Department of Economics - Working Papers Series WP2005-38, Boston University - Department of Economics.
    10. Gao, Yichen & Li, Cong & Liang, Zhongwen, 2015. "Binary response correlated random coefficient panel data models," Journal of Econometrics, Elsevier, vol. 188(2), pages 421-434.
    11. Fernández-Val, Iván, 2009. "Fixed effects estimation of structural parameters and marginal effects in panel probit models," Journal of Econometrics, Elsevier, vol. 150(1), pages 71-85, May.
    12. Jeffrey M. Wooldridge, 2004. "On the robustness of fixed effects and related estimators in correlated random coefficient panel data models," CeMMAP working papers 04/04, Institute for Fiscal Studies.
    13. Andrew Adrian Yu Pua, 2015. "On IV estimation of a dynamic linear probability model with fixed effects," UvA-Econometrics Working Papers 15-01, Universiteit van Amsterdam, Dept. of Econometrics.

  52. Christoffersen, Peter & Hahn, Jinyong & Inoue, Atsushi, 2001. "Testing and comparing Value-at-Risk measures," Journal of Empirical Finance, Elsevier, vol. 8(3), pages 325-342, July.
    See citations under working paper version above.
  53. Hahn, Jinyong, 2001. "The Information Bound Of A Dynamic Panel Logit Model With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 17(5), pages 913-932, October.

    Cited by:

    1. Christopher Dobronyi & Jiaying Gu & Kyoo il Kim, 2021. "Identification of Dynamic Panel Logit Models with Fixed Effects," Papers 2104.04590, arXiv.org, revised Apr 2021.
    2. Kevin Dano, 2023. "Transition Probabilities and Moment Restrictions in Dynamic Fixed Effects Logit Models," Papers 2303.00083, arXiv.org, revised Dec 2023.
    3. DHAENE, Geert & JOCHMANS, Koen, 2010. "Split-panel jackknife estimation of fixed-effect models," LIDAM Discussion Papers CORE 2010003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. D'Addio, Anna Cristina & Honoré, Bo E., 2010. "Duration Dependence and Timevarying Variables in Discrete Time Duration Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(2), December.
    5. Chris Muris & Pedro Raposo & Sotiris Vandoros, 2020. "A Dynamic Ordered Logit Model with Fixed Effects," Department of Economics Working Papers 2020-14, McMaster University.
    6. Christopher R. Dobronyi & Fu Ouyang & Thomas Tao Yang, 2023. "Revisiting Panel Data Discrete Choice Models with Lagged Dependent Variables," Papers 2301.09379, arXiv.org, revised Mar 2024.
    7. Matteo Richiardi & Ambra Poggi, 2012. "Imputing Individual Effects in Dynamic Microsimulation Models. An application of the Rank Method," Carlo Alberto Notebooks 267, Collegio Carlo Alberto.
    8. Yoshitsugu Kitazawa, 2017. "DFEL-RTN, a set of TSP programs for root-N consistent estimations of dynamic fixed effects logit models," Discussion Papers 81, Kyushu Sangyo University, Faculty of Economics.
    9. Timothy Halliday, 2006. "Identifying State Dependence in Non-Stationary Processes," Working Papers 200601, University of Hawaii at Manoa, Department of Economics.
    10. Ji-Liang Shiu & Yingyao Hu, 2010. "Identification and Estimation of Nonlinear Dynamic Panel Data Models with Unobserved Covariates," Economics Working Paper Archive 557, The Johns Hopkins University,Department of Economics.
    11. Ai, Chunrong & Gan, Li, 2010. "An alternative root-n consistent estimator for panel data binary choice models," Journal of Econometrics, Elsevier, vol. 157(1), pages 93-100, July.
    12. Timothy J. Halliday, 2006. "Testing for State Dependence with Time-Variant Transition Probabilities," Working Papers 200614, University of Hawaii at Manoa, Department of Economics.
    13. Ambra Poggi & Matteo Richiardi, 2012. "Accounting for Unobserved Heterogeneity in Discrete-time, Discrete-choice Dynamic Microsimulation Models. An application to Labor Supply and Household Formation in Italy," LABORatorio R. Revelli Working Papers Series 117, LABORatorio R. Revelli, Centre for Employment Studies.
    14. Matteo Richiardi & Ambra Poggi, 2014. "Imputing Individual Effects in Dynamic Microsimulation Models. An application to household formation and labour market participation in Italy," International Journal of Microsimulation, International Microsimulation Association, vol. 7(2), pages 3-39.
    15. Bartolucci, Francesco & Nigro, Valentina, 2012. "Pseudo conditional maximum likelihood estimation of the dynamic logit model for binary panel data," Journal of Econometrics, Elsevier, vol. 170(1), pages 102-116.
    16. Sheng-Kai Chang, 2014. "Simulation Estimation of Dynamic Panel Discrete Choice Models Using the $$t$$ t Distributions," Computational Economics, Springer;Society for Computational Economics, vol. 43(4), pages 395-409, April.
    17. Fu Ouyang & Thomas Tao Yang, 2022. "Semiparametric Estimation of Dynamic Binary Choice Panel Data Models," Papers 2202.12062, arXiv.org, revised Feb 2024.
    18. Carro, Jesus M., 2007. "Estimating dynamic panel data discrete choice models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 503-528, October.
    19. Bo E. Honor'e & Martin Weidner, 2020. "Moment Conditions for Dynamic Panel Logit Models with Fixed Effects," Papers 2005.05942, arXiv.org, revised Dec 2023.
    20. Fu Ouyang & Thomas Tao Yang, 2020. "Semiparametric Estimation of Dynamic Binary Choice Panel Data Models," ANU Working Papers in Economics and Econometrics 2020-671, Australian National University, College of Business and Economics, School of Economics.
    21. Manuel Arellano & Jinyong Hahn, 2005. "Understanding Bias in Nonlinear Panel Models: Some Recent Developments," Working Papers wp2005_0507, CEMFI.
    22. Bo E. Honoré & Martin Weidner, 2021. "Moment Conditions for Dynamic Panel Logit Models with Fixed Effects," Working Papers 2021-79, Princeton University. Economics Department..
    23. Fu Ouyang & Thomas Tao Yang, 2020. "Semiparametric Estimation of Dynamic Binary Choice Panel Data Models," Discussion Papers Series 626, School of Economics, University of Queensland, Australia.
    24. Escanciano, Juan Carlos, 2023. "Irregular identification of structural models with nonparametric unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 234(1), pages 106-127.
    25. Songnian Chen & Shakeeb Khan & Xun Tang, 2018. "Exclusion Restrictions in Dynamic Binary Choice Panel Data Models," Boston College Working Papers in Economics 947, Boston College Department of Economics.
    26. Bo E. Honoré & Martin Weidner, 2020. "Moment Conditions for Dynamic Panel Logit Models with Fixed Effects," CeMMAP working papers CWP38/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    27. Yoshitsugu Kitazawa, 2013. "Exploration of dynamic fixed effects logit models from a traditional angle," Discussion Papers 60, Kyushu Sangyo University, Faculty of Economics.
    28. Yoshitsugu Kitazawa, 2016. "Root-N consistent estimations of time dummies for the dynamic fixed effects logit models: Monte Carlo illustrations," Discussion Papers 72, Kyushu Sangyo University, Faculty of Economics.

  54. Foster, Andrew & Hahn, Jinyong, 2000. "A consistent semiparametric estimation of the consumer surplus distribution," Economics Letters, Elsevier, vol. 69(3), pages 245-251, December.
    See citations under working paper version above.
  55. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1999. "Multivariate Density Forecast Evaluation And Calibration In Financial Risk Management: High-Frequency Returns On Foreign Exchange," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 661-673, November.

    Cited by:

    1. Norman R. Swanson & Nii Ayi Armah, 2011. "Predictive Inference Under Model Misspecification with an Application to Assessing the Marginal Predictive Content of Money for Output," Departmental Working Papers 201103, Rutgers University, Department of Economics.
    2. Clements, Michael P., 2008. "Explanations of the inconsistencies in survey respondents'forecasts," The Warwick Economics Research Paper Series (TWERPS) 870, University of Warwick, Department of Economics.
    3. Charles Goodhart & Miguel Segoviano, 2009. "Banking Stability Measures," FMG Discussion Papers dp627, Financial Markets Group.
    4. Ivanova, Vesela & Puigvert Gutiérrez, Josep Maria, 2014. "Interest rate forecasts, state price densities and risk premium from Euribor options," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 210-223.
    5. Campbell, Sean D. & Diebold, Francis X., 2004. "Weather forecasting for weather derivatives," CFS Working Paper Series 2004/10, Center for Financial Studies (CFS).
    6. David Johnstone, 2007. "Economic Darwinism: Who has the Best Probabilities?," Theory and Decision, Springer, vol. 62(1), pages 47-96, February.
    7. Niguez, Trino-Manuel & Perote, Javier, 2004. "Forecasting the density of asset returns," LSE Research Online Documents on Economics 6845, London School of Economics and Political Science, LSE Library.
    8. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2000. "Exchange Rate Returns Standardized by Realized Volatility are (Nearly) Gaussian," NBER Working Papers 7488, National Bureau of Economic Research, Inc.
    9. Wolters, Maik H., 2013. "Evaluating point and density forecasts of DSGE models," Economics Working Papers 2013-03, Christian-Albrechts-University of Kiel, Department of Economics.
    10. Adamantios Ntakaris & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators," Papers 1907.09452, arXiv.org.
    11. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    12. Segoviano, Miguel A. & Goodhart, Charles, 2009. "Banking stability measures," LSE Research Online Documents on Economics 24416, London School of Economics and Political Science, LSE Library.
    13. Suzanne Emmer & Marie Kratz & Dirk Tasche, 2013. "What Is the Best Risk Measure in Practice? A Comparison of Standard Measures," Working Papers hal-00921283, HAL.
    14. Knüppel, Malte & Krüger, Fabian & Pohle, Marc-Oliver, 2022. "Score-based calibration testing for multivariate forecast distributions," Discussion Papers 50/2022, Deutsche Bundesbank.
    15. Ning, Ye & Zhang, Lingxiang, 2018. "Modeling dynamics of short-term international capital flows in China: A Markov regime switching approach," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 193-203.
    16. Pesaran, M. Hashem & Zaffaroni, Paolo, 2005. "Model Averaging and Value-at-Risk Based Evaluation of Large Multi-Asset Volatility Models for Risk Management," CEPR Discussion Papers 5279, C.E.P.R. Discussion Papers.
    17. Pascual, Lorenzo & Ruiz Ortega, Esther & Fresoli, Diego Eduardo, 2011. "Bootstrap forecast of multivariate VAR models without using the backward representation," DES - Working Papers. Statistics and Econometrics. WS ws113426, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Barbara Rossi, 2013. "Exchange rate predictability," Economics Working Papers 1369, Department of Economics and Business, Universitat Pompeu Fabra.
    19. David Bessler & Robert Ruffley, 2004. "Prequential analysis of stock market returns," Applied Economics, Taylor & Francis Journals, vol. 36(5), pages 399-412.
    20. Allayioti, Anastasia & Venditti, Fabrizio, 2024. "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series 2901, European Central Bank.
    21. Christian Bontemps & Nour Meddahi, 2012. "Testing distributional assumptions: A GMM aproach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 978-1012, September.
    22. Francis X. Diebold & Canlin Li, 2002. "Forecasting the Term Structure of Government Bond Yields," Center for Financial Institutions Working Papers 02-34, Wharton School Center for Financial Institutions, University of Pennsylvania.
    23. M. Hashem Pesaran, 2000. "Forecast Uncertainties in Macroeconometric Modelling: An Application to the UK Economy," CESifo Working Paper Series 345, CESifo.
    24. Pfajfar, D. & Zakelj, B., 2012. "Uncertainty and Disagreement in Forecasting Inflation : Evidence from the Laboratory (Revised version of EBC DP 2011-014)," Other publications TiSEM 2b92a09f-918e-4614-978d-0, Tilburg University, School of Economics and Management.
    25. Jian Wang & Jason J. Wu, 2012. "The Taylor Rule and Forecast Intervals for Exchange Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 103-144, February.
    26. Gloria Gonzalez-Rivera & Joao Henrique Mazzeu & Esther Ruiz & Helena Veiga, 2017. "A Bootstrap Approach for Generalized Autocontour Testing. Implications for VIX Forecast Densities," Working Papers 201709, University of California at Riverside, Department of Economics.
    27. Xiaohong Chen & Yanqin Fan, 2002. "Evaluating Density Forecasts via the Copula Approach," Vanderbilt University Department of Economics Working Papers 0225, Vanderbilt University Department of Economics, revised Sep 2003.
    28. Corradi, Valentina & Swanson, Norman R., 2004. "A test for the distributional comparison of simulated and historical data," Economics Letters, Elsevier, vol. 85(2), pages 185-193, November.
    29. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
    30. Refet S. Gürkaynak & Justin Wolfers, 2005. "Macroeconomic derivatives: an initial analysis of market-based macro forecasts, uncertainty, and risk," Working Paper Series 2005-26, Federal Reserve Bank of San Francisco.
    31. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
    32. Shamiri, Ahmed & Shaari, Abu Hassan & Isa, Zaidi, 2007. "Practical Volatility Modeling for Financial Market Risk Management," MPRA Paper 9790, University Library of Munich, Germany, revised 15 May 2008.
    33. Igor L. Kheifets, 2015. "Specification tests for nonlinear dynamic models," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 67-94, February.
    34. Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
    35. Corradi, Valentina & Swanson, Norman R., 2004. "Some recent developments in predictive accuracy testing with nested models and (generic) nonlinear alternatives," International Journal of Forecasting, Elsevier, vol. 20(2), pages 185-199.
    36. Francis X. Diebold, 2004. "The Nobel Memorial Prize for Robert F. Engle," Scandinavian Journal of Economics, Wiley Blackwell, vol. 106(2), pages 165-185, June.
    37. Pesaran, M. Hashem & Schleicher, Christoph & Zaffaroni, Paolo, 2009. "Model averaging in risk management with an application to futures markets," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 280-305, March.
    38. Ñíguez, Trino-Manuel & Perote, Javier, 2016. "Multivariate moments expansion density: Application of the dynamic equicorrelation model," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 216-232.
    39. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.
    40. Francisco Peñaranda, 2004. "Are Vector Autoregressions an Accurate Model for Dynamic Asset Allocation?," Working Papers wp2004_0419, CEMFI.
    41. Besma Hkiri & Juncal Cunado & Mehmet Balcilar & Rangan Gupta, 2019. "Time-Varying Relationship between Conventional and Unconventional Monetary Policies and Risk Aversion: International Evidence from Time- and Frequency-Domains," Working Papers 201965, University of Pretoria, Department of Economics.
    42. Valentina Corradi & Norman Swanson, 2004. "Predective Density and Conditional Confidence Interval Accuracy Tests," Departmental Working Papers 200423, Rutgers University, Department of Economics.
    43. Warshaw, Evan, 2019. "Extreme dependence and risk spillovers across north american equity markets," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 237-251.
    44. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
    45. Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
    46. Adamantios Ntakaris & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2020. "Mid-price prediction based on machine learning methods with technical and quantitative indicators," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-39, June.
    47. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.
    48. Shi Bo & Minheng Xiao, 2022. "Dynamic Risk Measurement by EVT based on Stochastic Volatility models via MCMC," Papers 2201.09434, arXiv.org, revised Jun 2023.
    49. Gabriela de Raaij & Burkhard Raunig, 2002. "Evaluating Density Forecasts with an Application to Stock Market Returns," Working Papers 59, Oesterreichische Nationalbank (Austrian Central Bank).
    50. Graziani, Carlo & Rosner, Robert & Adams, Jennifer M. & Machete, Reason L., 2021. "Probabilistic recalibration of forecasts," International Journal of Forecasting, Elsevier, vol. 37(1), pages 1-27.
    51. Ahoniemi, Katja & Lanne, Markku, 2007. "Joint Modeling of Call and Put Implied Volatility," MPRA Paper 6318, University Library of Munich, Germany.
    52. Kratz, Marie & Lok, Y-H & McNeil, Alexander J., 2016. "Multinomial VaR Backtests: A simple implicit approach to backtesting expected shortfall," ESSEC Working Papers WP1617, ESSEC Research Center, ESSEC Business School.
    53. Niango Ange Joseph Yapi, 2020. "Exchange rate predictive densities and currency risks: A quantile regression approach," EconomiX Working Papers 2020-16, University of Paris Nanterre, EconomiX.
    54. Ko, Stanley I.M. & Park, Sung Y., 2013. "Multivariate density forecast evaluation: A modified approach," International Journal of Forecasting, Elsevier, vol. 29(3), pages 431-441.
    55. Tsyplakov, Alexander, 2013. "Evaluation of Probabilistic Forecasts: Proper Scoring Rules and Moments," MPRA Paper 45186, University Library of Munich, Germany.
    56. Wang, Yudong & Liu, Li & Wu, Chongfeng, 2017. "Forecasting the real prices of crude oil using forecast combinations over time-varying parameter models," Energy Economics, Elsevier, vol. 66(C), pages 337-348.
    57. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    58. Brandt, Patrick T. & Freeman, John R. & Schrodt, Philip A., 2014. "Evaluating forecasts of political conflict dynamics," International Journal of Forecasting, Elsevier, vol. 30(4), pages 944-962.
    59. Gloria Gonzalez-Rivera & Yun Luo & Esther Ruiz, 2019. "Prediction Regions for Interval-valued Time Series," Working Papers 201921, University of California at Riverside, Department of Economics.
    60. Bruno Rémillard, 2017. "Goodness-of-Fit Tests for Copulas of Multivariate Time Series," Econometrics, MDPI, vol. 5(1), pages 1-23, March.
    61. González-Rivera, Gloria & Yoldas, Emre, 2012. "Autocontour-based evaluation of multivariate predictive densities," International Journal of Forecasting, Elsevier, vol. 28(2), pages 328-342.
    62. Jian Wang & Jason J. Wu, 2012. "The Taylor Rule and Forecast Intervals for Exchange Rates," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 103-144, February.
    63. Hong, Yongmiao & Li, Haitao & Zhao, Feng, 2007. "Can the random walk model be beaten in out-of-sample density forecasts? Evidence from intraday foreign exchange rates," Journal of Econometrics, Elsevier, vol. 141(2), pages 736-776, December.
    64. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
    65. Pfajfar, Damjan & Žakelj, Blaž, 2016. "Uncertainty in forecasting inflation and monetary policy design: Evidence from the laboratory," International Journal of Forecasting, Elsevier, vol. 32(3), pages 849-864.
    66. Kratz, Marie & Lok, Yen H. & McNeil, Alexander J., 2018. "Multinomial VaR backtests: A simple implicit approach to backtesting expected shortfall," Journal of Banking & Finance, Elsevier, vol. 88(C), pages 393-407.
    67. Casey, Eddie, 2021. "Are professional forecasters overconfident?," International Journal of Forecasting, Elsevier, vol. 37(2), pages 716-732.
    68. Herbst, Edward & Schorfheide, Frank, 2012. "Evaluating DSGE model forecasts of comovements," Journal of Econometrics, Elsevier, vol. 171(2), pages 152-166.
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    70. Valentina Corradi & Norman R. Swanson, 2003. "Bootstrap Conditional Distribution Tests In the Presence of Dynamic Misspecification," Departmental Working Papers 200311, Rutgers University, Department of Economics.
    71. Kyungchul Song, 2011. "Testing Predictive Ability and Power Robustification," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 288-296, October.
    72. Gloria Gonzalez-Rivera & Yingying Sun, 2014. "Generalized Autocontours: Evaluation of Multivariate Density Models," Working Papers 201431, University of California at Riverside, Department of Economics.
    73. Hansen, Bruce E., 2006. "Interval forecasts and parameter uncertainty," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 377-398.
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    75. Arnold Polanski & Evarist Stoja, 2013. "Co-dependence of Extreme Events in High Frequency FX Returns," University of East Anglia Applied and Financial Economics Working Paper Series 040, School of Economics, University of East Anglia, Norwich, UK..
    76. Matthias Pelster & Johannes Vilsmeier, 2018. "The determinants of CDS spreads: evidence from the model space," Review of Derivatives Research, Springer, vol. 21(1), pages 63-118, April.
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    1. Binder, M. & Hsaio, C. & Pesaran, M.H., 2000. "Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration," Cambridge Working Papers in Economics 0003, Faculty of Economics, University of Cambridge.
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    4. Jose Diogo Barbosa & Marcelo Moreira, 2017. "Likelihood inference and the role of initial conditions for the dynamic panel data model," CeMMAP working papers CWP04/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    5. Gareth M. Thomas & Seung C. Ahn, 2004. "Likelihood Based Inference for amic Panel Data Models," Econometric Society 2004 Far Eastern Meetings 669, Econometric Society.
    6. Yingyao Hu & Ji‐Liang Shiu, 2018. "Identification and estimation of semi‐parametric censored dynamic panel data models of short time periods," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 55-85, February.
    7. Matteo Richiardi & Ambra Poggi, 2012. "Imputing Individual Effects in Dynamic Microsimulation Models. An application of the Rank Method," Carlo Alberto Notebooks 267, Collegio Carlo Alberto.
    8. Giorgio Calzolari & Laura Magazzini, 2014. "Improving GMM efficiency in dynamic models for panel data with mean stationarity," Working Papers 12/2014, University of Verona, Department of Economics.
    9. Al-Sadoon, Majid M. & Li, Tong & Pesaran, M. Hashem, 2012. "An Exponential Class of Dynamic Binary Choice Panel Data Models with Fixed Effects," IZA Discussion Papers 7054, Institute of Labor Economics (IZA).
    10. Burak Dindaroglu, 2010. "Intra-Industry Knowledge Spillovers and Scientific Labor Mobility," Discussion Papers 10-01, University at Albany, SUNY, Department of Economics.
    11. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
    12. Michael Funke & Ralf Ruhwedel, 2002. "Export variety and export performance: Empirical evidence for the OECD countries," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 138(1), pages 97-114, March.
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    18. Matteo Richiardi & Ambra Poggi, 2014. "Imputing Individual Effects in Dynamic Microsimulation Models. An application to household formation and labour market participation in Italy," International Journal of Microsimulation, International Microsimulation Association, vol. 7(2), pages 3-39.
    19. Jeffrey M. Wooldridge, 2002. "Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity," CeMMAP working papers 18/02, Institute for Fiscal Studies.
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    30. Giorgio Calzolari & Laura Magazzini, 2013. "A powerful test of mean stationarity in dynamic models for panel data: Monte Carlo evidence," Working Papers 14/2013, University of Verona, Department of Economics.
    31. Arvid Raknerud, 2002. "Identification, Estimation and Testing in Panel Data Models with Attrition: The Role of the Missing at Random Assumption," Discussion Papers 330, Statistics Norway, Research Department.
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    34. Jerry Hausman & Maxim L. Pinkovskiy, 2017. "Estimating dynamic panel models: backing out the Nickell Bias," CeMMAP working papers 53/17, Institute for Fiscal Studies.
    35. Maria Elena Bontempi & Jan Ditzen, 2023. "GMM-lev estimation and individual heterogeneity: Monte Carlo evidence and empirical applications," Papers 2312.00399, arXiv.org, revised Dec 2023.
    36. Jerry Hausman & Maxim L. Pinkovskiy, 2017. "Estimating dynamic panel models: backing out the Nickell Bias," CeMMAP working papers CWP53/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

  57. Moshe Buchinsky & Jinyong Hahn, 1998. "An Alternative Estimator for the Censored Quantile Regression Model," Econometrica, Econometric Society, vol. 66(3), pages 653-672, May.

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    1. Chen, Songnian, 2018. "Sequential estimation of censored quantile regression models," Journal of Econometrics, Elsevier, vol. 207(1), pages 30-52.
    2. Machado, Jose A F & Santos Silva, Joao M C, 2008. "Quantiles for Fractions and Other Mixed Data," Economics Discussion Papers 3550, University of Essex, Department of Economics.
    3. Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile and probability curves without crossing," CeMMAP working papers CWP10/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Liu, Haoming & Park, Cheolsung, 2004. "The evolution of the graduation-publication process," Economics of Education Review, Elsevier, vol. 23(5), pages 519-531, October.
    5. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
    6. Joshua Angrist & Victor Chernozhukov & Ivan Fernandez-Val, 2004. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," NBER Working Papers 10428, National Bureau of Economic Research, Inc.
    7. Danúbia R. Cunha & Jose Angelo Divino & Helton Saulo, 2022. "On a log-symmetric quantile tobit model applied to female labor supply data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(16), pages 4225-4253, December.
    8. Denis Chetverikov & Jesper R.-V. Sørensen, 2021. "Analytic and Bootstrap-after-Cross-Validation Methods for Selecting Penalty Parameters of High-Dimensional M-Estimators," Discussion Papers 21-04, University of Copenhagen. Department of Economics.
    9. Lin, Wei & Cai, Zongwu & Li, Zheng & Su, Li, 2015. "Optimal smoothing in nonparametric conditional quantile derivative function estimation," Journal of Econometrics, Elsevier, vol. 188(2), pages 502-513.
    10. Marcel Fafchamps & Christine O. N. Moser, 2004. "Crime, Isolation, and Law Enforcement," WIDER Working Paper Series RP2004-05, World Institute for Development Economic Research (UNU-WIDER).
    11. Elise Coudin & Jean-Marie Dufour, 2007. "Finite-sample Distribution-free Inference in Linear Median Regression under Heteroskedasticity and Nonlinear Dependence of Unknown Form," Working Papers 2007-38, Center for Research in Economics and Statistics.
    12. Kim, Mo Se & Lee, Byung Sung & Lee, Hye Seon & Lee, Seung Ho & Lee, Junseok & Kim, Wonse, 2020. "Robust estimation of outage costs in South Korea using a machine learning technique: Bayesian Tobit quantile regression," Applied Energy, Elsevier, vol. 278(C).
    13. Manuel Arellano & Stéphane Bonhomme & Micole De Vera & Laura Hospido & Siqi Wei, 2021. "Income Risk Inequality: Evidence from Spanish Administrative Records," Working Papers 2136, Banco de España.
    14. Lu, Xuewen & Burke, M.D., 2005. "Censored multiple regression by the method of average derivatives," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 182-205, July.
    15. Ignacio Palacios-Huerta, 2001. "The Human Capital of Stockholders and the International Diversification Puzzle," Working Papers 2001-13, Brown University, Department of Economics.
    16. Gabrielle Fack & Camille Landais, 2016. "The effect of tax enforcement on tax elasticities: Evidence from charitable contributions in France," PSE-Ecole d'économie de Paris (Postprint) hal-01300122, HAL.
    17. Christophe Muller, 2006. "Optimising Anti-Poverty Transfers With Quantile Regressions," Working Papers. Serie AD 2006-07, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    18. Moshe Buchinsky & Phillip Leslie, 2010. "Educational Attainment and the Changing U.S. Wage Structure: Dynamic Implications on Young Individuals' Choices," Journal of Labor Economics, University of Chicago Press, vol. 28(3), pages 541-594, July.
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    21. John Simon & Tahlee Stone, 2017. "The Property Ladder after the Financial Crisis: The First Step is a Stretch but Those Who Make It Are Doing OK," RBA Research Discussion Papers rdp2017-05, Reserve Bank of Australia.
    22. Gabrielle Fack & Camille Landais, 2010. "Are Tax Incentives for Charitable Giving Efficient? Evidence from France," American Economic Journal: Economic Policy, American Economic Association, vol. 2(2), pages 117-141, May.
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    1. Geert Dhaene & Koen Jochmans, 2011. "Profile-score Adjustements for Nonlinearfixed-effect Models," SciencePo Working papers Main hal-01073733, HAL.
    2. Otilia Boldea & Bettina Drepper & Zhuojiong Gan, 2020. "Change point estimation in panel data with time‐varying individual effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(6), pages 712-727, September.
    3. Dahlberg, Matz & Lundin, Douglas, 2005. "Antidepressants and the Suicide Rate: Is There Really a Connection?," Working Paper Series 2005:4, Uppsala University, Department of Economics.
    4. Bo E. Honoré & Chris Muris & Martin Weidner, 2021. "Dynamic Ordered Panel Logit Models," Working Papers 2021-14, Princeton University. Economics Department..
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    7. Laurent Davezies & Xavier D'Haultfoeuille & Martin Mugnier, 2020. "Fixed Effects Binary Choice Models with Three or More Periods," Papers 2009.08108, arXiv.org, revised Sep 2022.
    8. Laurent Davezies & Xavier D'Haultfoeuille & Louise Laage, 2021. "Identification and Estimation of Average Marginal Effects in Fixed Effects Logit Models," Papers 2105.00879, arXiv.org, revised Oct 2022.
    9. Nicholas Brown & Jeffrey Wooldridge, 2023. "More Efficient Estimation of Multiplicative Panel Data Models in the Presence of Serial Correlation," Working Paper 1497, Economics Department, Queen's University.
    10. Martins, Igor, 2019. "An Act for the Abolition of the Slave Trade: The Effects of an Import Ban on Cape Colony Slaveholders," African Economic History Working Paper 43/2019, African Economic History Network.
    11. Wooldridge, Jeffrey M., 1999. "Distribution-free estimation of some nonlinear panel data models," Journal of Econometrics, Elsevier, vol. 90(1), pages 77-97, May.
    12. Lindvall, Lars, 2003. "Does Public Spending on Youths Affect Crime Rates?," Working Paper Series 2004:3, Uppsala University, Department of Economics.

  60. Hahn, Jinyong, 1997. "Bayesian Bootstrap of the Quantile Regression Estimator: A Large Sample Study," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 38(4), pages 795-808, November.

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    1. Alexandre Belloni & Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2016. "Program evaluation and causal inference with high-dimensional data," CeMMAP working papers 13/16, Institute for Fiscal Studies.
    2. Joshua Angrist & Victor Chernozhukov & Ivan Fernandez-Val, 2004. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," NBER Working Papers 10428, National Bureau of Economic Research, Inc.
    3. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2012. "Inference on counterfactual distributions," CeMMAP working papers 05/12, Institute for Fiscal Studies.
    4. David M. Kaplan & Lonnie Hofmann, 2019. "High-order coverage of smoothed Bayesian bootstrap intervals for population quantiles," Working Papers 1914, Department of Economics, University of Missouri, revised 19 Sep 2020.
    5. Kaplan, David M. & Zhuo, Longhao, 2021. "Frequentist properties of Bayesian inequality tests," Journal of Econometrics, Elsevier, vol. 221(1), pages 312-336.
    6. Giuseppe Ragusa, 2007. "Bayesian Likelihoods for Moment Condition Models," Working Papers 060714, University of California-Irvine, Department of Economics.
    7. Victor Chernozhukov & Ivan Fernandez-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers 57/13, Institute for Fiscal Studies.
    8. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    9. 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.
    10. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Ivan Fernandez-Val, 2016. "Conditional quantile processes based on series or many regressors," CeMMAP working papers 46/16, Institute for Fiscal Studies.
    11. Ying-Ying Lee, 2015. "Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification," Econometrics, MDPI, vol. 4(1), pages 1-14, December.
    12. David M. Kaplan & Longhao Zhuo, 2018. "Frequentist size of Bayesian inequality tests," Working Papers 1802, Department of Economics, University of Missouri, revised 14 Jul 2019.
    13. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
    14. Victor Chernozhukov & Iv'an Fern'andez-Val & Blaise Melly, 2019. "Fast Algorithms for the Quantile Regression Process," Papers 1909.05782, arXiv.org, revised Apr 2020.
    15. Kilian, Lutz & Inoue, Atsushi & Guerron-Quintana, Pablo A., 2009. "Frequentist Inference in Weakly Identified DSGE Models," CEPR Discussion Papers 7447, C.E.P.R. Discussion Papers.

  61. Hahn, Jinyong, 1997. "Efficient estimation of panel data models with sequential moment restrictions," Journal of Econometrics, Elsevier, vol. 79(1), pages 1-21, July.

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    1. Koenker, Roger & Machado, Jose A. F., 1999. "GMM inference when the number of moment conditions is large," Journal of Econometrics, Elsevier, vol. 93(2), pages 327-344, December.
    2. Inkmann, Joachim, 2000. "Misspecified heteroskedasticity in the panel probit model: A small sample comparison of GMM and SML estimators," Journal of Econometrics, Elsevier, vol. 97(2), pages 227-259, August.
    3. Inkmann, Joachim, 2000. "Finite Sample Properties of One-step, Two-step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation," CoFE Discussion Papers 00/03, University of Konstanz, Center of Finance and Econometrics (CoFE).
    4. Stanislav Anatolyev, 2005. "Optimal Instruments in Time Series: A Survey," Working Papers w0069, Center for Economic and Financial Research (CEFIR).
    5. Mustafa Salamh & Liqun Wang, 2021. "Second-Order Least Squares Method for Dynamic Panel Data Models with Application," JRFM, MDPI, vol. 14(9), pages 1-19, September.
    6. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
    7. Christian Gourieroux & Peter C. B. Phillips & Jun Yu, 2006. "Indirect Inference for Dynamic Panel Models," Cowles Foundation Discussion Papers 1550, Cowles Foundation for Research in Economics, Yale University.
    8. Chunrong Ai & Xiaohong Chen, 2009. "Semiparametric efficiency bound for models of sequential moment restrictions containing unknown functions," CeMMAP working papers CWP28/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Tue Gørgens & Christopher L. Skeels & Allan H. Würtz, 2009. "Efficient Estimation of Non-Linear Dynamic Panel Data Models with Application to Smooth Transition Models," CREATES Research Papers 2009-51, Department of Economics and Business Economics, Aarhus University.
    10. Wang, Xuexin, 2015. "A Note on Consistent Conditional Moment Tests," MPRA Paper 69005, University Library of Munich, Germany.
    11. Manuel Arellano, 2003. "Modelling Optimal Instrumental Variables for Dynamic Panel Data Models," Working Papers wp2003_0310, CEMFI.
    12. Zhenlin Yang, 2014. "Initial-Condition Free Estimation of Fixed Effects Dynamic Panel Data Models," Working Papers 16-2014, Singapore Management University, School of Economics.
    13. Bao, Yong & Yu, Xuewen, 2023. "Indirect inference estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1027-1053.
    14. Ahn, Seung Chan & Hoon Lee, Young & Schmidt, Peter, 2001. "GMM estimation of linear panel data models with time-varying individual effects," Journal of Econometrics, Elsevier, vol. 101(2), pages 219-255, April.
    15. Donald, Stephen G. & Imbens, Guido W. & Newey, Whitney K., 2003. "Empirical likelihood estimation and consistent tests with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 117(1), pages 55-93, November.
    16. Jinyong Hahn & Jerry Hausman & Guido Kuersteiner, 2005. "Bias Corrected Instrumental Variables Estimation for Dynamic Panel Models with Fixed E¤ects," Boston University - Department of Economics - Working Papers Series WP2005-024, Boston University - Department of Economics.
    17. Chamberlain, Gary, 2022. "Feedback in panel data models," Journal of Econometrics, Elsevier, vol. 226(1), pages 4-20.
    18. Peter Phillips & Hyungsik Moon, 2000. "Nonstationary panel data analysis: an overview of some recent developments," Econometric Reviews, Taylor & Francis Journals, vol. 19(3), pages 263-286.
    19. Hahn, Jinyong & Hausman, Jerry & Kuersteiner, Guido, 2007. "Long difference instrumental variables estimation for dynamic panel models with fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 574-617, October.
    20. Byeong U. Park & Robin C Sickles & Léopold Simar, 2002. "Semi parametric efficient estimation of dynamic panel data models," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 C6-1, International Conferences on Panel Data.
    21. Komunjer, Ivana & Vuong, Quang, 2010. "Efficient estimation in dynamic conditional quantile models," Journal of Econometrics, Elsevier, vol. 157(2), pages 272-285, August.
    22. Michael Creel, 2009. "A Data Mining Approach to Indirect Inference," UFAE and IAE Working Papers 788.09, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC), revised 25 Oct 2009.
    23. Chen, Weihao & Cizek, Pavel, 2023. "Bias-Corrected Instrumental Variable Estimation in Linear Dynamic Panel Data Models," Other publications TiSEM 9bf2c16c-522f-4223-8037-c, Tilburg University, School of Economics and Management.
    24. Zongwu Cai & Linna Chen & Ying Fang, 2015. "Semiparametric Estimation of Partially Varying-Coefficient Dynamic Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 695-719, December.
    25. Yong Bao, 2021. "Indirect Inference Estimation of a First-Order Dynamic Panel Data Model," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 79-98, December.
    26. Prokhorov, Artem & Schmidt, Peter, 2009. "GMM redundancy results for general missing data problems," Journal of Econometrics, Elsevier, vol. 151(1), pages 47-55, July.
    27. Hahn, Jinyong, 1999. "How informative is the initial condition in the dynamic panel model with fixed effects?," Journal of Econometrics, Elsevier, vol. 93(2), pages 309-326, December.

  62. Hahn, Jinyong, 1996. "A Note on Bootstrapping Generalized Method of Moments Estimators," Econometric Theory, Cambridge University Press, vol. 12(1), pages 187-197, March.

    Cited by:

    1. Seojeong Lee, 2014. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for GEL Estimators," Discussion Papers 2014-02, School of Economics, The University of New South Wales.
    2. Inoue, Atsushi & Shintani, Mototsugu, 2006. "Bootstrapping GMM estimators for time series," Journal of Econometrics, Elsevier, vol. 133(2), pages 531-555, August.
    3. Goncalves, Silvia & White, Halbert, 2004. "Maximum likelihood and the bootstrap for nonlinear dynamic models," Journal of Econometrics, Elsevier, vol. 119(1), pages 199-219, March.
    4. Jason Allen & Allan Gregory & Katsumi Shimotsu, 2008. "Empirical Likelihood Block Bootstrapping," Staff Working Papers 08-18, Bank of Canada.
    5. Inkmann, Joachim, 2000. "Finite Sample Properties of One-step, Two-step and Bootstrap Empirical Likelihood Approaches to Efficient GMM Estimation," CoFE Discussion Papers 00/03, University of Konstanz, Center of Finance and Econometrics (CoFE).
    6. David Powell, 2013. "A New Framework for Estimation of Quantile Treatment Effects Nonseparable Disturbance in the Presence of Covariates," Working Papers WR-824-1, RAND Corporation.
    7. Erich Battistin & Michele De Nadai & Daniela Vuri, 2014. "Counting Rotten Apples: Student Achievement and Score Manipulation in Italian Elementary Schools," CEIS Research Paper 329, Tor Vergata University, CEIS, revised 08 Sep 2014.
    8. Torgovitsky, Alexander, 2017. "Minimum distance from independence estimation of nonseparable instrumental variables models," Journal of Econometrics, Elsevier, vol. 199(1), pages 35-48.
    9. Sawada, Yasuyuki & Shoji, Masahiro & Sugawara, Shinya & Shinkai, Naoko, 2010. "The Role of Infrastructure in Mitigating Poverty Dynamics:The Case of an Irrigation Project in Sri Lanka," Working Papers 4, JICA Research Institute.
    10. Matias D. Cattaneo & Michael Jansson, 2014. "Bootstrapping Kernel-Based Semiparametric Estimators," CREATES Research Papers 2014-25, Department of Economics and Business Economics, Aarhus University.
    11. Dovonon, Prosper & Gonçalves, Sílvia, 2017. "Bootstrapping the GMM overidentification test under first-order underidentification," Journal of Econometrics, Elsevier, vol. 201(1), pages 43-71.
    12. Wenjie Wang & Qingfeng Liu, 2015. "Bootstrap-based Selection for Instrumental Variables Model," Economics Bulletin, AccessEcon, vol. 35(3), pages 1886-1896.
    13. Konstantinidi, Antri & Kourtellos, Andros & Sun, Yiguo, 2023. "Social threshold regression," Journal of Econometrics, Elsevier, vol. 235(2), pages 2057-2081.
    14. Joshua Angrist & Ivan Fernandez-Val, 2010. "ExtrapoLATE-ing: External Validity and Overidentification in the LATE Framework," NBER Working Papers 16566, National Bureau of Economic Research, Inc.
    15. Honoré, Bo E. & Hu, Luojia, 2018. "Easy bootstrap-like estimation of asymptotic variances," Economics Letters, Elsevier, vol. 171(C), pages 46-50.
    16. Laurent Davezies & Xavier D'Haultfoeuille & Yannick Guyonvarch, 2018. "Asymptotic results under multiway clustering," Papers 1807.07925, arXiv.org, revised Aug 2018.
    17. Joaquim Ramalho, 2003. "Small Sample Bias of Alternative Estimation Methods for Moment Condition Models: Monte Carlo Evidence for Covariance Structures and Instrumental Variables," Economics Working Papers 9_2003, University of Évora, Department of Economics (Portugal).
    18. Seojeong Lee, 2013. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Method of Moments Estimators," Discussion Papers 2013-09, School of Economics, The University of New South Wales.
    19. Francesco Bravo & Federico Crudu, 2012. "Efficient bootstrap with weakly dependent processes," Discussion Papers 12/08, Department of Economics, University of York.
    20. Mihai Giurcanu & Brett Presnell, 2018. "Bootstrap inference for misspecified moment condition models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(3), pages 605-630, June.
    21. Ishihara, Takuya, 2020. "Identification and estimation of time-varying nonseparable panel data models without stayers," Journal of Econometrics, Elsevier, vol. 215(1), pages 184-208.
    22. Firmin Doko Tchatoka & Robert Garrard & Virginie Masson, 2017. "Testing for Stochastic Dominance in Social Networks," School of Economics and Public Policy Working Papers 2017-02, University of Adelaide, School of Economics and Public Policy.
    23. Jinyong Hahn & Jerry Hausman & Josh Lustig, 2017. "Specification test on mixed logit models," CeMMAP working papers 58/17, Institute for Fiscal Studies.
    24. Jean-Jacques Forneron & Serena Ng, 2020. "Inference by Stochastic Optimization: A Free-Lunch Bootstrap," Papers 2004.09627, arXiv.org, revised Sep 2020.
    25. Seojeong Lee, 2018. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Empirical Likelihood Estimators," Papers 1806.00953, arXiv.org, revised Jun 2018.
    26. Paulo M.D.C. Parente & Richard J. Smith, 2018. "Generalised Empirical Likelihood Kernel Block Bootstrapping," Working Papers REM 2018/55, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.

  63. Hahn, Jinyong, 1995. "Bootstrapping Quantile Regression Estimators," Econometric Theory, Cambridge University Press, vol. 11(1), pages 105-121, February.

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    1. Joel L. Horowitz, 1996. "Bootstrap Methods for Median Regression Models," Econometrics 9608004, University Library of Munich, Germany.
    2. Lüdemann, Elke & Wilke, Ralf A. & Zhang, Xuan, 2004. "Censored Quantile Regressions and the Length of Unemployment Periods in West Germany," ZEW Discussion Papers 04-57, ZEW - Leibniz Centre for European Economic Research.
    3. Roger Koenker, 2000. "Inference on the Quantile Regression Process," Econometric Society World Congress 2000 Contributed Papers 0886, Econometric Society.
    4. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2016. "Quantile Regression for Long Memory Testing: A Case of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 693-724.
    5. 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.
    6. Chen, Shu-Ling, 2011. "Modeling Temperature Dynamics for Aquaculture Index Insurance In Taiwan: A Nonlinear Quantile Approach," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 104229, Agricultural and Applied Economics Association.
    7. Zhang, Zhinan & Xu, Xiangyun, 2023. "Sustainable financial risk, resources abundance and technological innovation: Evidence from resources abundance economies," Resources Policy, Elsevier, vol. 83(C).
    8. Marco Angrisani & Antonio Guarino & Philippe Jehiel & Toru Kitagawa, 2019. "Information Redundancy Neglect versus Overconfidence: A Social Learning Experiment," PSE Working Papers halshs-02183322, HAL.
    9. Jelena Laušev, 2012. "Public Sector Pay Gap In Serbia During Large-Scale Privatisation,By Educational Qualification," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 57(192), pages 7-24, January –.
    10. Komunjer, Ivana, 2005. "Quasi-maximum likelihood estimation for conditional quantiles," Journal of Econometrics, Elsevier, vol. 128(1), pages 137-164, September.
    11. Yoon-Jae Whang, 2003. "Smoothed Empirical Likelihood Methods for Quantile Regression Models," Econometrics 0310005, University Library of Munich, Germany.
    12. Delgado, Miguel A. & Domínguez, Manuel A., 1997. "Consistent specification testing of quantile regression models," DES - Working Papers. Statistics and Econometrics. WS 6211, Universidad Carlos III de Madrid. Departamento de Estadística.
    13. Zhai, Muxin & Kishan, Ruby P. & Showalter, Dean, 2022. "Social capital and suicidal behaviors: Evidence from the United States counties," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 98(C).
    14. Xiaofeng Lv & Rui Li, 2013. "Smoothed empirical likelihood analysis of partially linear quantile regression models with missing response variables," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(4), pages 317-347, October.
    15. Victor Chernozhukov & Ivan Fernandez-Val & Blaise Melly, 2012. "Inference on counterfactual distributions," CeMMAP working papers 05/12, Institute for Fiscal Studies.
    16. Christis Katsouris, 2023. "Quantile Time Series Regression Models Revisited," Papers 2308.06617, arXiv.org, revised Aug 2023.
    17. David Powell, 2013. "A New Framework for Estimation of Quantile Treatment Effects Nonseparable Disturbance in the Presence of Covariates," Working Papers WR-824-1, RAND Corporation.
    18. Kim, Mo Se & Lee, Byung Sung & Lee, Hye Seon & Lee, Seung Ho & Lee, Junseok & Kim, Wonse, 2020. "Robust estimation of outage costs in South Korea using a machine learning technique: Bayesian Tobit quantile regression," Applied Energy, Elsevier, vol. 278(C).
    19. Song, Song & Ritov, Ya’acov & Härdle, Wolfgang K., 2012. "Bootstrap confidence bands and partial linear quantile regression," Journal of Multivariate Analysis, Elsevier, vol. 107(C), pages 244-262.
    20. Chen, Ming & Chen, Junying, 2023. "Natural resources extraction in emerging economies: Does it promote sustainable development or crowd-out real sector?," Resources Policy, Elsevier, vol. 83(C).
    21. Wang, Yafeng & Graham, Brett, 2009. "Generalized Maximum Entropy estimation of discrete sequential move games of perfect information," MPRA Paper 21331, University Library of Munich, Germany.
    22. Christophe Muller & Christophe Nordman, 2005. "Human capital and wages in two leading industries in Tunisia: evidence from matched worker-firm data," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 48(1-2), pages 183-208.
    23. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
    24. Claudiu Tiberiu Albulescu & Camélia Turcu, 2022. "Productivity, financial performance, and corporate governance: evidence from Romanian R&D firms," Post-Print hal-03810531, HAL.
    25. Karin Hoisl, 2009. "Does mobility increase the productivity of inventors?," The Journal of Technology Transfer, Springer, vol. 34(2), pages 212-225, April.
    26. Mohamed Jellal & Christophe Nordman & Francois-Charles Wolff, 2008. "Evidence on the glass ceiling effect in France using matched worker-firm data," Applied Economics, Taylor & Francis Journals, vol. 40(24), pages 3233-3250.
    27. Antonio F. Galvao & Gabriel Montes-Rojas, 2015. "On Bootstrap Inference for Quantile Regression Panel Data: A Monte Carlo Study," Econometrics, MDPI, vol. 3(3), pages 1-13, September.
    28. Gimenes, Nathalie & Guerre, Emmanuel, 2022. "Quantile regression methods for first-price auctions," Journal of Econometrics, Elsevier, vol. 226(2), pages 224-247.
    29. Mohammedi, Mustapha & Bouzebda, Salim & Laksaci, Ali, 2021. "The consistency and asymptotic normality of the kernel type expectile regression estimator for functional data," Journal of Multivariate Analysis, Elsevier, vol. 181(C).
    30. Dimitris Politis, 2013. "Model-free model-fitting and predictive distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 183-221, June.
    31. Antonio F. Galvao & Thomas Parker & Zhijie Xiao, 2021. "Bootstrap inference for panel data quantile regression," Papers 2111.03626, arXiv.org.
    32. J. Carlos Escanciano & Carlos Velasco, 2010. "Specification tests of parametric dynamic conditional quantiles," Post-Print hal-00732534, HAL.
    33. Tim Bollerslev & Jia Li & Leonardo Salim Saker Chaves, 2021. "Generalized Jump Regressions for Local Moments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1015-1025, October.
    34. Christophe Muller & Christophe Nordman, 2005. "Which Human Capital Matters for Rich and Poor’s Wages? Evidence from Matched Worker-Firm Data from Tunisia," Labor and Demography 0501009, University Library of Munich, Germany.
    35. Andreas Hagemann, 2017. "Cluster-Robust Bootstrap Inference in Quantile Regression Models," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 446-456, January.
    36. 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.
    37. Hu, Hao & Li, Ruida & Zhang, Leilei, 2023. "Financial development and resources curse hypothesis: China's COVID-19 perspective of natural resources extraction," Resources Policy, Elsevier, vol. 85(PB).
    38. Hideo Kozumi & Genya Kobayashi, 2009. "Gibbs Sampling Methods for Bayesian Quantile Regression," Discussion Papers 2009-02, Kobe University, Graduate School of Business Administration.
    39. Shaddady, Ali & Moore, Tomoe, 2019. "Investigation of the effects of financial regulation and supervision on bank stability: The application of CAMELS-DEA to quantile regressions," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 96-116.
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    42. Sun, Y., 2003. "A Consistent Nonparametric Equality Test of Conditional Quantile Functions," Working Papers 2003-10, University of Guelph, Department of Economics and Finance.
    43. Bo Honore & Shakeeb Khan & James L. Powell, 2000. "Quantile Regression Under Random Censoring," Econometric Society World Congress 2000 Contributed Papers 1894, Econometric Society.
    44. Lamarche, Carlos, 2011. "Measuring the incentives to learn in Colombia using new quantile regression approaches," Journal of Development Economics, Elsevier, vol. 96(2), pages 278-288, November.
    45. Ftiti, Zied & Ben Ameur, Hachmi & Louhichi, Waël, 2021. "Does non-fundamental news related to COVID-19 matter for stock returns? Evidence from Shanghai stock market," Economic Modelling, Elsevier, vol. 99(C).
    46. Christophe Muller & Tae-Hwan Kim, 2005. "Two-Stage Huber Estimation," Working Papers. Serie AD 2005-17, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    47. Maricruz Lacalle†Calderon & Manuel Perez†Trujillo & Isabel Neira, 2018. "Does Microfinance Reduce Poverty among the Poorest? A Macro Quantile Regression Approach," The Developing Economies, Institute of Developing Economies, vol. 56(1), pages 51-65, March.
    48. Ni, Xiewen, 2023. "Natural resources and COP26 targets of developed countries: Pandemic perspective of natural resources extraction," Resources Policy, Elsevier, vol. 83(C).
    49. Anthoulla Phella, 2020. "Consistent Specification Test of the Quantile Autoregression," Papers 2010.03898, arXiv.org, revised Jan 2024.
    50. Christophe Muller & Sami Bibi, 2006. "Focused Targeting Against Poverty Evidence From Tunisia," Working Papers. Serie AD 2006-01, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    51. Robert L. Bray & Haim Mendelson, 2012. "Information Transmission and the Bullwhip Effect: An Empirical Investigation," Management Science, INFORMS, vol. 58(5), pages 860-875, May.
    52. Khan, Zeeshan & Hossain, Mohammad Razib & Badeeb, Ramez Abubakr & Zhang, Changyong, 2023. "Aggregate and disaggregate impact of natural resources on economic performance: Role of green growth and human capital," Resources Policy, Elsevier, vol. 80(C).
    53. Malmendier, Ulrike M. & Botsch, Matthew J., 2020. "The Long Shadows of the Great Inflation: Evidence from Residential Mortgages," CEPR Discussion Papers 14934, C.E.P.R. Discussion Papers.
    54. Jose A. F. Machado & Jose Mata, 2000. "Box-Cox quantile regression and the distribution of firm sizes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(3), pages 253-274.
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    Cited by:

    1. Chen, Xiaohong & Liao, Zhipeng, 2014. "Sieve M inference on irregular parameters," Journal of Econometrics, Elsevier, vol. 182(1), pages 70-86.
    2. Bijwaard, Govert & Ridder, Geert, 2009. "A Simple GMM Estimator for the Semi-Parametric Mixed Proportional Hazard Model," IZA Discussion Papers 4543, Institute of Labor Economics (IZA).
    3. Bo E. Honoré & Aureo de Paula, 2009. ""Interdependent Durations" Third Version," PIER Working Paper Archive 09-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Feb 2008.
    4. de Paula, Aureo, 2020. "The Informativeness of Estimation Moments," CEPR Discussion Papers 14298, C.E.P.R. Discussion Papers.
    5. Horowitz, Joel L. & Lee, Sokbae, 2004. "Semiparametric estimation of a panel data proportional hazards model with fixed effects," Journal of Econometrics, Elsevier, vol. 119(1), pages 155-198, March.
    6. Abbring, Jaap H. & Berg, Gerard J. van den, 2000. "The non-parametric identification of the mixed proportional hazards competing risks model," Serie Research Memoranda 0024, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    7. Van den Berg, Gerard J., 2000. "Duration Models: Specification, Identification, and Multiple Durations," MPRA Paper 9446, University Library of Munich, Germany.
    8. Sadat Reza & Paul Rilstone, 2016. "Semiparametric Efficiency Bounds and Efficient Estimation of Discrete Duration Models with Unspecified Hazard Rate," Econometric Reviews, Taylor & Francis Journals, vol. 35(5), pages 693-726, May.
    9. Bearse, Peter & Canals, Jose & Rilstone, Paul, 1998. "Consistent standard errors for semiparametric duration models with unobserved heterogeneity," Economics Letters, Elsevier, vol. 59(2), pages 153-156, May.
    10. Bo E. Honore & Aureo de Paula, 2007. "Interdependent Durations, Second Version," PIER Working Paper Archive 08-044, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Nov 2008.
    11. Bo E. Honoré & Áureo de Paula, 2016. "A new model for interdependent durations with an application to joint retirement," CeMMAP working papers 07/16, Institute for Fiscal Studies.
    12. Jerry Hausman & Tiemen M. Woutersen, 2005. "Estimating a semi-parametric duration model without specifying heterogeneity," CeMMAP working papers CWP11/05, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    14. Bo E. Honoré & Thomas Jorgensen & Áureo de Paula, 2019. "Sensitivity of Estimation Precision to Moments with an Application to a Model of Joint Retirement Planning of Couples," CeMMAP working papers CWP36/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Michael Baker & Angelo Melino, 1999. "Duration Dependence and Nonparametric Heterogeneity: A Monte Carlo Study," Working Papers melino-99-01, University of Toronto, Department of Economics.
    16. Lancaster, Tony, 2000. "The incidental parameter problem since 1948," Journal of Econometrics, Elsevier, vol. 95(2), pages 391-413, April.
    17. Bo E. Honor & Áureo De Paula, 2010. "Interdependent Durations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(3), pages 1138-1163.
    18. Jerry Hausman & Tiemen Woutersen, 2014. "Estimating the Derivative Function and Counterfactuals in Duration Models with Heterogeneity," Econometric Reviews, Taylor & Francis Journals, vol. 33(5-6), pages 472-496, August.
    19. Joel L. Horowitz & Sokbae (Simon) Lee, 2002. "Semiparametric estimation of a panel data proportional hazards model with fixed effects," CeMMAP working papers 21/02, Institute for Fiscal Studies.

Chapters

  1. Jinyong Hahn & Jerry Hausman, 2010. "Estimation with Valid and Invalid Instruments," NBER Chapters, in: Contributions in Memory of Zvi Griliches, pages 25-57, National Bureau of Economic Research, Inc.
    See citations under working paper version above.Sorry, no citations of chapters recorded.
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