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

Boris Lokshin

No 2008-039, MERIT Working Papers from United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (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.

Keywords: Bias Correction; Unbalanced Panel Data; GMM; Dynamic Models (search for similar items in EconPapers)
JEL-codes: C23 (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://unu-merit.nl/publications/wppdf/2008/wp2008-039.pdf (application/pdf)

Related works:
Journal Article: Further results on bias in dynamic unbalanced panel data models with an application to firm R&D investment (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:unm:unumer:2008039

Access Statistics for this paper

More papers in MERIT Working Papers from United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT) Contact information at EDIRC.
Bibliographic data for series maintained by Ad Notten ( this e-mail address is bad, please contact ).