Further results on bias in dynamic unbalanced panel data models with an application to firm R&D investment

Lokshin, Boris (2008). Further results on bias in dynamic unbalanced panel data models with an application to firm R&D investment. UNU-MERIT.

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UNU-MERIT Working Papers

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  • Author Lokshin, Boris
    Title Further results on bias in dynamic unbalanced panel data models with an application to firm R&D investment
    Publication Date 2008
    Publisher UNU-MERIT
    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.
    Keyword Bias correction
    Unbalanced panel data
    GMM
    Dynamic model
    JEL C23
    Copyright Holder UNU-MERIT
    Copyright Year 2008
    ISSN 1871-9872
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    Created: Wed, 11 Dec 2013, 16:16:06 JST