Estimating Dynamic Panel Models in Corporate Finance

46 Pages Posted: 25 Mar 2008 Last revised: 15 Oct 2012

See all articles by Mark J. Flannery

Mark J. Flannery

University of Florida - Department of Finance, Insurance and Real Estate

Kristine Watson Hankins

University of Kentucky

Date Written: July 29, 2012

Abstract

Dynamic panel models play a natural role in several important areas of corporate finance, but the combination of fixed effects and lagged dependent variables introduces serious econometric bias. Several methods of counteracting these biases are available and these methodologies have been tested on small datasets with independent, normally-distributed explanatory variables. However, no one has evaluated the methods’ performance with corporate finance data, in which the dependent variable may be clustered or censored and independent variables may be missing, correlated with one another, or endogenous. We find that the data’s properties substantially affect the estimators’ performances. We provide evidence about the impact of various data set characteristics on the estimators, so that researchers can determine the best approach for their datasets.

Keywords: Corporate finance, financial econometrics, dynamic panel estimation

JEL Classification: G30, C13, C23

Suggested Citation

Flannery, Mark Jeffrey and Hankins, Kristine Watson, Estimating Dynamic Panel Models in Corporate Finance (July 29, 2012). Journal of Corporate Finance, Forthcoming, Available at SSRN: https://ssrn.com/abstract=1108684 or http://dx.doi.org/10.2139/ssrn.1108684

Mark Jeffrey Flannery

University of Florida - Department of Finance, Insurance and Real Estate ( email )

P.O. Box 117168
Gainesville, FL 32611
United States
352-392-3184 (Phone)
352-392-0103 (Fax)

Kristine Watson Hankins (Contact Author)

University of Kentucky ( email )

College of Business & Economics
Lexington, KY 40506-0034
United States

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