TY  - RPRT
        AU  - Hayakawa, Kazuhiko
AU  - Pesaran, M. Hashem
        TI  - Robust Standard Errors in Transformed Likelihood Estimation of Dynamic Panel Data Models
        PY  - 2012/May/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 6583
        UR  - https://www.iza.org/index.php/publications/dp6583
        AB  - 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.
        KW  - Monte Carlo simulation
KW  - cross-sectional heteroskedasticity
KW  - dynamic panels
KW  - GMM estimation
        ER  -