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

Author

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  • Lokshin, Boris

    (UNU-MERIT, and Maastricht University)

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.

Suggested Citation

  • Lokshin, Boris, 2008. "Further results on bias in dynamic unbalanced panel data models with an application to firm R&D investment," MERIT Working Papers 2008-039, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    • Handle: RePEc:unm:unumer:2008039
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    File URL: https://www.merit.unu.edu/publications/wppdf/2008/wp2008-039.pdf
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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.

    More about this item

    Keywords

    Bias Correction; Unbalanced Panel Data; GMM; Dynamic Models;
    All these keywords.

    JEL classification:

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

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