Bias Correction in the Estimation of Dynamic Panel Models In Corporate Finance

Published in Journal of Corporate Finance 25 (2014) 494–513 DOI:10.1016/j.jcorpfin.2014.01.009

Posted: 22 Jun 2016

See all articles by Qing Zhou

Qing Zhou

Department of Applied Finance and Actuarial Studies, Macquarie University

Robert W. Faff

University of Queensland

Karen Alpert

University of Queensland - Business School; Financial Research Network (FIRN)

Date Written: April 2, 2015

Abstract

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.

Keywords: Dynamic panels, Corporate finance, Bias-correction

JEL Classification: G30, C23

Suggested Citation

Zhou, Qing and Faff, Robert W. and Alpert, Karen, Bias Correction in the Estimation of Dynamic Panel Models In Corporate Finance (April 2, 2015). Published in Journal of Corporate Finance 25 (2014) 494–513 DOI:10.1016/j.jcorpfin.2014.01.009. Available at SSRN: https://ssrn.com/abstract=2798480

Qing Zhou (Contact Author)

Department of Applied Finance and Actuarial Studies, Macquarie University ( email )

Sydney, NSW
Australia

Robert W. Faff

University of Queensland ( email )

St Lucia
Brisbane, Queensland 4072
Australia

Karen Alpert

University of Queensland - Business School ( email )

Brisbane, Queensland 4072
Australia

Financial Research Network (FIRN) ( email )

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

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