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Maximum likelihood estimation of fixed effects dynamic panel data models covering short time periods

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  • Hsiao, Cheng
  • Hashem Pesaran, M.
  • Kamil Tahmiscioglu, A.

Abstract

A transformed likelihood approach is suggested to estimate fixed effects dynamic panel data models. Conditions on the data generating process of the exogenous variables are given to get around the issue of ?incidental parameters?. The maximum likelihood (MLE) and minimum distance estimator (MDE) are suggested. Both estimators are shown to be consistent and asymptotically more efficient than the instrumental variable (IV) or generalised method of moment (GMM) estimators. A Hausman-type specification test is suggested to test the fixed versus random effects specification or conditions on the data-generating process of the exogenous variables. Monte Carlo studies are conducted to evaluate the finite sample properties of the MLE, MDE, IV and GMM. It is shown that the likelihood approach appears to dominate the GMM approach both in terms of the bias or root mean squares error of the estimators and the size and power of the test statistics.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 109 (2002)
Issue (Month): 1 (July)
Pages: 107-150

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Handle: RePEc:eee:econom:v:109:y:2002:i:1:p:107-150

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Web page: http://www.elsevier.com/locate/jeconom

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  1. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
  2. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
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  15. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
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