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

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  • Boris Lokshin

Abstract

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.

Suggested Citation

  • Boris Lokshin, 2009. "Further results on bias in dynamic unbalanced panel data models with an application to firm R&D investment," Applied Economics Letters, Taylor & Francis Journals, vol. 16(12), pages 1227-1233.
  • Handle: RePEc:taf:apeclt:v:16:y:2009:i:12:p:1227-1233
    DOI: 10.1080/13504850701367270
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    Cited by:

    1. Fabrice Murtin & Romain Wacziarg, 2014. "The democratic transition," Journal of Economic Growth, Springer, vol. 19(2), pages 141-181, June.
    2. Leandro D�Aurizio & Stefano Iezzi, 2011. "Investment forecasting with business survey data," Temi di discussione (Economic working papers) 832, Bank of Italy, Economic Research and International Relations Area.

    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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