On Maximum Likelihood estimation of dynamic panel data models
We analyze the finite sample properties of maximum likelihood estimators for dynamic panel data models. In particular, we consider Transformed Maximum Likelihood (TML) and Random effects Maximum Likelihood (RML) estimation. We show that TML and RML estimators are solutions to a cubic first-order condition in the autoregressive parameter. Furthermore, in finite samples both likelihood estimators might lead to a negative estimate of the variance of the individual specific effects. We consider different approaches taking into account the non-negativity restriction for the variance. We show that these approaches may lead to a boundary solution different from the unique global unconstrained maximum. In an extensive Monte Carlo study we find that this boundary solution issue is non-negligible for small values of T and that different approaches might lead to substantially different finite sample properties. Furthermore, we find that the Likelihood Ratio statistic provides size control in small samples, albeit with low power due to the flatness of the log-likelihood function. We illustrate these issues modeling U.S. state level unemployment dynamics.
|Date of creation:||16 Dec 2014|
|Contact details of provider:|| Postal: Dept. of Econometrics, Universiteit van Amsterdam, Valckenierstraat 65, NL - 1018 XE Amsterdam, The Netherlands|
Web page: http://www.ase.uva.nl/uva-econometrics
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- Binder, Michael & Hsiao, Cheng & Pesaran, M. Hashem, 2005.
"Estimation And Inference In Short Panel Vector Autoregressions With Unit Roots And Cointegration,"
Cambridge University Press, vol. 21(04), pages 795-837, August.
- Michael Binder & Cheng Hsiao & M. Hashem Pesaran, 2000. "Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration," Working Papers 0005, Banco de España;Working Papers Homepage.
- Michael Binder, Cheng Hsiao, and M. Hashem Pesaran, 2001. "Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration," Computing in Economics and Finance 2001 36, Society for Computational Economics.
- Michael Binder & Cheng Hsiao & M. Hashem Pesaran, 2000. "Estimation and Inference In Short Panel Vector Autoregressions with Unit Roots And Cointegration," CESifo Working Paper Series 374, CESifo Group Munich.
- Binder, M. & Hsaio, C. & Pesaran, M.H., 2000. "Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration," Cambridge Working Papers in Economics 0003, Faculty of Economics, University of Cambridge.
- Kazuhiko Hayakawa & M. Hashem Pesaran, 2012. "Robust Standard Errors in Transformed Likelihood Estimation of Dynamic Panel Data Models," Working Paper Series 38_12, The Rimini Centre for Economic Analysis.
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- Kazuhiko Hayakawa & M. Hashem Pesaran, 2012. "Robust Standard Errors in Transformed Likelihood Estimation of Dynamic Panel Data Models," CESifo Working Paper Series 3850, CESifo Group Munich.
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- Kruiniger, Hugo, 2013. "Quasi ML estimation of the panel AR(1) model with arbitrary initial conditions," Journal of Econometrics, Elsevier, vol. 173(2), pages 175-188.
- Hugo Kruiniger, 2006. "Quasi ML Estimation of the Panel AR(1) Model with Arbitrary Initial Conditions," Working Papers 582, Queen Mary University of London, School of Economics and Finance.
- Maddala, G S, 1971. "The Use of Variance Components Models in Pooling Cross Section and Time Series Data," Econometrica, Econometric Society, vol. 39(2), pages 341-358, March.
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- Arturas Juodis, 2013. "First Difference Transformation in Panel VAR models: Robustness, Estimation and Inference," UvA-Econometrics Working Papers 13-06, Universiteit van Amsterdam, Dept. of Econometrics. Full references (including those not matched with items on IDEAS)
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