Robust Standard Errors in Transformed Likelihood Estimation of Dynamic Panel Data Models

Kazuhiko Hayakawa and Mohammad Pesaran

No 6583, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are crosssectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that arises, and its implications for estimation and inference. We approach the problem by working with a mis-specified homoskedastic model. It is shown that the transformed maximum likelihood estimator continues to be consistent even in the presence of cross-sectional heteroskedasticity. We also obtain standard errors that are robust to cross-sectional heteroskedasticity of unknown form. By means of Monte Carlo simulation, we investigate the finite sample behavior of the transformed maximum likelihood estimator and compare it with various GMM estimators proposed in the literature. Simulation results reveal that, in terms of median absolute errors and accuracy of inference, the transformed likelihood estimator outperforms the GMM estimators in almost all cases.

Keywords: Monte Carlo simulation; cross-sectional heteroskedasticity; dynamic panels; GMM estimation (search for similar items in EconPapers)
JEL-codes: C12 C13 C23 (search for similar items in EconPapers)
Pages: 51 pages
Date: 2012-05
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (8)

Published - published as 'Robust standard errors in transformed likelihood estimation of dynamic panel data models with cross-sectional heteroskedasticity' in: Journal of Econometrics, 2015, 188 (1), 111-134

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Related works:
Working Paper: Robust Standard Errors in Transformed Likelihood Estimation of Dynamic Panel Data Models (2012)
Working Paper: Robust Standard Errors in Transformed Likelihood Estimation of Dynamic Panel Data Models (2012)
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