Further Results on Bias in Dynamic Unbalanced Panel Data Models with an Application to Firm R&D Investment

14 Pages Posted: 8 Jun 2011

See all articles by Boris Lokshin

Boris Lokshin

Maastricht University, School of Business and Economics

Date Written: June 8, 2011

Abstract

This paper extends the LSDV bias-corrected estimator in [Bun, M., Carree, M.A. 2005. Bias-corrected estimation in dynamic panel data models, Journal of Business and Economic Statistics, 23(2): 200-10] to unbalanced panels and discusses the analytic method of obtaining the solution. Using a Monte Carlo approach the paper compares the performance of this estimator with three other available techniques for dynamic panel data models. Simulation reveals that LSDV-bc estimator is a good choice except for samples with small T, where it may be unpractical. The methodology is applied to examine the impact of internal and external R&D on labor productivity in an unbalanced panel of innovating firms.

Keywords: bias correction, unbalanced panel data, GMM, dynamic model

JEL Classification: C23

Suggested Citation

Lokshin, Boris, Further Results on Bias in Dynamic Unbalanced Panel Data Models with an Application to Firm R&D Investment (June 8, 2011). Applied Economics Letters, Vol. 16, No. 10-12, 2009. Available at SSRN: https://ssrn.com/abstract=1860051

Boris Lokshin (Contact Author)

Maastricht University, School of Business and Economics ( email )

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