Title: Panel data models with nonadditive unobserved heterogeneity: Estimation and inference
Abstract: Quantitative EconomicsVolume 4, Issue 3 p. 453-481 Open Access Panel data models with nonadditive unobserved heterogeneity: Estimation and inference Iván Fernández-Val, Iván Fernández-Val Department of Economics, Boston University; [email protected]Search for more papers by this authorJoonhwah Lee, Joonhwah Lee Department of Economics, MIT; [email protected] This paper is based in part on the second chapter of Fernández-Val (2005). We wish to thank Josh Angrist, Victor Chernozhukov, and Whitney Newey for encouragement and advice. For suggestions and comments, we are grateful to Manuel Arellano, Mingli Chen, the editor, three anonymous referees, and the participants at the Brown and Harvard–MIT Econometrics seminar. We thank Aju Fenn for providing the data for the empirical example. All remaining errors are ours. Fernández-Val gratefully acknowledges financial support from Fundación Caja Madrid, Fundación Ramón Areces, and the National Science Foundation.Search for more papers by this author Iván Fernández-Val, Iván Fernández-Val Department of Economics, Boston University; [email protected]Search for more papers by this authorJoonhwah Lee, Joonhwah Lee Department of Economics, MIT; [email protected] This paper is based in part on the second chapter of Fernández-Val (2005). We wish to thank Josh Angrist, Victor Chernozhukov, and Whitney Newey for encouragement and advice. For suggestions and comments, we are grateful to Manuel Arellano, Mingli Chen, the editor, three anonymous referees, and the participants at the Brown and Harvard–MIT Econometrics seminar. We thank Aju Fenn for providing the data for the empirical example. All remaining errors are ours. Fernández-Val gratefully acknowledges financial support from Fundación Caja Madrid, Fundación Ramón Areces, and the National Science Foundation.Search for more papers by this author First published: 18 November 2013 https://doi.org/10.3982/QE75Citations: 17 AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Abstract This paper considers fixed effects estimation and inference in linear and nonlinear panel data models with random coefficients and endogenous regressors. The quantities of interest—means, variances, and other moments of the random coefficients—are estimated by cross sectional sample moments of generalized method of moments (GMM) estimators applied separately to the time series of each individual. To deal with the incidental parameter problem introduced by the noise of the within-individual estimators in short panels, we develop bias corrections. These corrections are based on higher-order asymptotic expansions of the GMM estimators and produce improved point and interval estimates in moderately long panels. Under asymptotic sequences where the cross sectional and time series dimensions of the panel pass to infinity at the same rate, the uncorrected estimators have asymptotic biases of the same order as their asymptotic standard deviations. The bias corrections remove the bias without increasing variance. 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