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A two-stage estimation for panel data models with grouped fixed effects
Authors:Hao Qu
Institution:1. School of Mathematics and Statistics, Northeast Normal University, Changchun, China;2. Department of Management Engineering, Guidaojiaotong Polytechnic Institute, Shenyang, ChinaORCID Iconhttps://orcid.org/0000-0002-4101-0227
Abstract:ABSTRACT

This paper considers panel data models with fixed effects which have grouped patterns with unknown group membership. A two-stage estimation (TSE) procedure is developed to improve the properties of the GFE estimators of common parameters when the time span is small. Firstly, the common parameters are estimated. Subsequently, the optimal group assignment and the estimators of group effects are obtained by the K-means algorithm. Monte Carlo results reveal that the TSE estimator has a much smaller bias than the GFE estimator when the values of difference between effects are moderately small or at high variance of the idiosyncratic error.
Keywords:Exogenous variables  Instrumental variable estimation  K-means algorithm  Monte Carlo simulations  Panel data models  Predetermined variables
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