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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. repec:hal:spmain:info:hdl:2441/5m0od0o9jn9pqbdmos7fpt28hg is not listed on IDEAS
    3. 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.
    4. repec:spo:wpmain:info:hdl:2441/5m0od0o9jn9pqbdmos7fpt28hg is not listed on IDEAS

    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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