On the estimation of panel regression models with fixed effects
AbstractThis paper considers estimation of panel data models with fixed effects. First, we will show that a consistent ``unrestricted fixed effects'' estimator does not exist for autoregressive panel data models with initial conditions. We will derive necessary and sufficient conditions for the consistency of estimators for these models. In particular, we will show that various widely used GMM estimators for the conditional AR(1) panel model are inconsistent under trending fixed effects sequences. Next, we will derive, justify, and compare restricted Fixed Effects GMM and (Q)ML estimators for this model. We find that the FEML estimator is asymptotically efficient, whereas the Modified ML estimator is not. We will also compare the fixed effects approach for estimating the conditional AR(1) panel model and covariance parameters in static panel data models with the correlated random effects approach.
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Bibliographic InfoPaper provided by International Conferences on Panel Data in its series 10th International Conference on Panel Data, Berlin, July 5-6, 2002 with number C6-2.
Date of creation: Mar 2002
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Other versions of this item:
- Hugo Kruiniger, 2002. "On the Estimation of Panel Regression Models with Fixed Effects," Working Papers 450, Queen Mary, University of London, School of Economics and Finance.
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2002-07-04 (All new papers)
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