Bias correction in the estimation of dynamic panel models in corporate finance

Zhou, Qing, Faff, Robert and Alpert, Karen (2014) Bias correction in the estimation of dynamic panel models in corporate finance. Journal of Corporate Finance, 25 494-513. doi:10.1016/j.jcorpfin.2014.01.009

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Author Zhou, Qing
Faff, Robert
Alpert, Karen
Title Bias correction in the estimation of dynamic panel models in corporate finance
Journal name Journal of Corporate Finance   Check publisher's open access policy
ISSN 0929-1199
Publication date 2014-04
Sub-type Article (original research)
DOI 10.1016/j.jcorpfin.2014.01.009
Open Access Status
Volume 25
Start page 494
End page 513
Total pages 20
Place of publication Amsterdam, Netherlands
Publisher Elsevier North-Holland
Collection year 2015
Language eng
Formatted abstract
• We explore biases in empirical corporate finance research.
• We examine dynamic panel modeling in a capital structure setting.
• We show that biases have a material impact on inferences.
• We propose a bias-corrected combination estimator solution.
• Our estimator reconciles divergent speeds of leverage adjustment in the literature.

Dynamic panel models play an increasingly important role in numerous areas of corporate finance research, and a variety of (biased) estimation methods have been proposed in the literature. The biases inherent in these estimation methods have a material impact on inferences about corporate behavior, especially when the empirical model is misspecified. We propose a bias-corrected global minimum variance (GMV) combined estimation procedure to mitigate this estimation problem. We choose the capital structure speed of adjustment (SOA) setting to illustrate the proposed method using both simulated and actual empirical corporate finance data. The GMV estimator non-trivially reduces bias and hence meaningfully increases the reliability of inferences based on parameter estimates. This method can be readily applied to many other corporate finance contexts.
Keyword Dynamic panels
Corporate finance
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Available online 9 February 2014

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2015 Collection
UQ Business School Publications
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Citation counts: TR Web of Science Citation Count  Cited 5 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 5 times in Scopus Article | Citations
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Created: Wed, 12 Feb 2014, 08:42:44 EST by Karen Morgan on behalf of UQ Business School