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

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Author Info
Maurice J.G. Bun ()
Jan F. Kiviet () (University of Amsterdam)

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Abstract

Through Monte Carlo experiments the small sample behavior is examined of various inference techniques for dynamic panel data models when both the time-series and cross-section dimensions of the data set are small. The LSDV technique and corrected versions of it are compared with IV and GMM regarding: coefficient bias, accuracy of variance estimators - both of the disturbances and of the coefficient estimators - and the actual size of coefficient tests. A reasonably simple and consistent bias adjusted LSDV estimator, for which we find an analytical and a bootstrap consistent estimator of its variance, performs relatively well. Further higher-order refinements of the bias correction do not improve the accuracy considerably. Most techniques show substantial size distortions for asymptotic t tests. Finally, it is illustrated how these findings help to interpret empirical results on the relationship between so-called dynamic externalities and local economic activity in Moroccan urban areas.

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Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 01-006/4.

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Date of creation: 17 Jan 2001
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Handle: RePEc:dgr:uvatin:20010006

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