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The Accuracy of Inference in Small Samples of Dynamic Panel Data Models

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  • Maurice J.G. Bun
  • Jan F. Kiviet

    (University of Amsterdam)

Abstract

Through Monte Carlo experiments the small sample behavior is examinedof various inference techniques for dynamic panel data models whenboth the time-series and cross-section dimensions of the data set aresmall. The LSDV technique and corrected versions of it are comparedwith IV and GMM regarding: coefficient bias, accuracy of varianceestimators - both of the disturbances and of the coefficientestimators - and the actual size of coefficient tests. A reasonablysimple and consistent bias adjusted LSDV estimator, for which we findan analytical and a bootstrap consistent estimator of its variance,performs relatively well. Further higher-order refinements of thebias correction do not improve the accuracy considerably. Mosttechniques show substantial size distortions for asymptotic t tests.Finally, it is illustrated how these findings help to interpretempirical results on the relationship between so-called dynamicexternalities and local economic activity in Moroccan urban areas.

Suggested Citation

  • Maurice J.G. Bun & Jan F. Kiviet, 2001. "The Accuracy of Inference in Small Samples of Dynamic Panel Data Models," Tinbergen Institute Discussion Papers 01-006/4, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20010006
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