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Median-Unbiased Estimation in Fixed-Effects Dynamic Panels

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  • Rodolfo Cermeño

Abstract

This paper extends Andrews' [1993] median-unbiased estimation for autoregressive/unit root time series to panel data dynamic fixed effects models. It is shown that median-unbiased estimation applies straightforwardly to models that include linear time trends as well as to those including more general time specific effects. Using Monte Carlo simulations, median-unbiased LSDV estimators are computed and found to be robust to groupwise heteroskedastic and cross-sectionally correlated disturbances. The behavior of these estimators in the presence of exogenous regressors as well as AR parameter heterogeneity is also evaluated in this paper. As an application, these estimators are used to evaluate conditional convergence in the cases of 48 USA states, 13 OECD countries, and two wider samples from Summers and Heston's Penn World Tables, with 57 and 100 countries. It is found that median-unbiased estimates support conditional convergence only among USA states and OECD countries.

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  • Rodolfo Cermeño, 1999. "Median-Unbiased Estimation in Fixed-Effects Dynamic Panels," Annals of Economics and Statistics, GENES, issue 55-56, pages 351-368.
    • Handle: RePEc:adr:anecst:y:1999:i:55-56:p:351-368
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    File URL: http://www.jstor.org/stable/20076203
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    Cited by:

    1. P. Čížek & M. Aquaro, 2018. "Robust estimation and moment selection in dynamic fixed-effects panel data models," Computational Statistics, Springer, vol. 33(2), pages 675-708, June.
    2. Martin A. Carree, 2002. "Nearly Unbiased Estimationin Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 02-008/2, Tinbergen Institute.
    3. Rodolfo Cermeño, 2002. "Growth convergence clubs: Evidence from Markov-switching models using panel data," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 D5-3, International Conferences on Panel Data.

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