Further results on bias in dynamic unbalanced panel data models with an application to firm R&D investment
This article extends the LSDV bias-corrected estimator in (Bun and Carree, 2005) to unbalanced panels and discusses the analytic method of obtaining the solution. Using a Monte Carlo approach the article 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 labour productivity in an unbalanced panel of innovating firms.
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Volume (Year): 16 (2009)
Issue (Month): 12 ()
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