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The Robustness Of Estimators For Dynamic Panel Data Models To Misspecification

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Author Info
MARK N. HARRIS (Department of Econometrics and Business Statistics, Monash University, Clayton, Melbourne, Victoria 3800, Australia)
WEIPING KOSTENKO (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne, Australia)
LÁSZLÓ MÁTYÁS (Central European University, Hungary; Erudite, Universite Paris XII, Paris, France)
ISFAAQ TIMOL (Department of Econometrics and Business Statistics, Monash University, Clayton, Melbourne, Victoria 3800, Australia)

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Abstract

Transition from economic theory to a testable form of model invariably involves the use of certain "simplifying assumptions." If, however, these are not valid, misspecified models result. This article considers estimation of the dynamic linear panel data model, which often forms the basis of testable economic hypotheses. The estimators of such a model are frequently similarly based on certain assumptions which appear to be often untenable in practice. Here, the performance of these estimators is analyzed in scenarios where the theoretically required conditions are not met. Specifically, we consider three such instances of serial correlation of the idiosyncratic disturbance terms; correlation of the idiosyncratic disturbance terms and explanatory variables; and, finally, cross-sectional dependence (as a robustness check to these findings, we also consider correlations between observed and unobserved heterogeneity terms). The major findings are that the limited tests readily available tend to have poor power properties and that estimators' performance varies greatly across scenarios. In such a wide array of experiments, it is difficult to pick-out just one "winner." However, a robust estimator across all experiments and parameter settings was a variant of the Wansbeek–Bekker estimator. This is a significant finding, as this estimator is infrequently used in practice. When the experiments are extended to include correlations between observed and unobserved heterogeneity terms, one might also consider, for across-the-board performance, the Blundell and Bond estimator.

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Publisher Info
Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal The Singapore Economic Review.

Volume (Year): 54 (2009)
Issue (Month): 03 ()
Pages: 399-426
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Handle: RePEc:wsi:serxxx:v:54:y:2009:i:03:p:399-426

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Related research
Keywords: Dynamic panel data; misspecification; IV/GMM estimation; JEL Classification: C13; JEL Classification: C15; JEL Classification: C23;

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(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)
  1. Mark N. Harris & Simon Feeny, 2003. "Habit persistence in effective tax rates," Applied Economics, Taylor and Francis Journals, vol. 35(8), pages 951-958, January. [Downloadable!] (restricted)
  2. Simon Feeny & Mark N. Harris & Joanne Loundes, 2000. "A Dynamic Panel Analysis of the Profitability of Australian Tax Entities," Melbourne Institute Working Paper Series wp2000n22, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne. [Downloadable!]
    Other versions:
  3. Housung Jung & Hyeog Ug Kwon, 2007. "An Alternative System GMM Estimation in Dynamic Panel Models," Hi-Stat Discussion Paper Series d07-217, Institute of Economic Research, Hitotsubashi University. [Downloadable!]
  4. Mark N. Harris & Simon Feeny, 2000. "Habit Persistence in Effective Tax Rates: Evidence Using Australian Tax Entities," Melbourne Institute Working Paper Series wp2000n13, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne. [Downloadable!]
  5. Hosung Jung, 2005. "A Test for Autocorrelation in Dynamic Panel Data Models," Hi-Stat Discussion Paper Series d04-77, Institute of Economic Research, Hitotsubashi University. [Downloadable!]
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