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Panel-Data Estimation in Finance: Testable Assumptions and Parameter (In)Consistency

Published online by Cambridge University Press:  14 September 2018

Abstract

We investigate the strict-exogeneity assumption, a necessary condition for estimator consistency in many finance panel-data applications. We outline tests for strict exogeneity in both traditional (non–instrumental variable (IV)) and IV settings. When we apply these tests in common traditional finance panel regressions, we find that the strict-exogeneity assumption is often strongly rejected, suggesting large inference errors. We test for strict exogeneity in specific finance panel-data IV settings and illustrate the potential for these tests to help confirm, or rule out, the validity of common panel-data IV estimators. We offer recommendations to address the strict-exogeneity issue in finance research.

Type
Research Article
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2018 

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Footnotes

1

We thank an anonymous referee, Bernard Black, Jennifer Conrad (the editor), Todd Gormley, Jeff Wooldridge, and seminar participants at the University of Iowa, the University of Nebraska, the 2015 London Business School (LBS) Symposium on Causal Inference, and the 2016 Financial Research Association Meetings for helpful comments and suggestions. All errors remain our own.

References

Agrawal, A., and Matsa, D. A.. “Labor Unemployment Risk and Corporate Financing Decisions.” Journal of Financial Economics, 108 (2013), 449470.Google Scholar
Angrist, J. D., and Pischke, J.-S.. Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton, NJ: Princeton University Press (2009).Google Scholar
Arellano, M., and Bond, S.. “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations.” Review of Economic Studies, 58 (1991), 277297.Google Scholar
Atanasov, V., and Black, B.. “The Trouble with Instruments: Re-Examining Shock-Based IV Designs.” Working Paper, Northwestern University (2016).Google Scholar
Blundell, R., and Bond, S.. “Initial Conditions and Moment Restrictions in Dynamic Panel Data Models.” Journal of Econometrics, 87 (1998), 115143.Google Scholar
Cameron, A. C., and Trivedi, P. K.. Microeconometrics: Methods and Applications. New York, NY: Cambridge University Press (2005).Google Scholar
Chen, H. J., and Chen, S. J.. “Investment-Cash Flow Sensitivity Cannot Be a Good Measure of Financial Constraints: Evidence from the Time Series.” Journal of Financial Economics, 105 (2012), 393410.Google Scholar
Dang, V. A.; Kim, M.; and Shin, Y.. “In Search of Robust Methods for Dynamic Panel Data Models in Empirical Corporate Finance.” Journal of Banking and Finance, 53 (2015), 8498.Google Scholar
Demsetz, H., and Lehn, K.. “The Structure of Corporate Ownership: Causes and Consequences.” Journal of Political Economy, 93 (1985), 11551177.Google Scholar
Fischer, E. O.; Heinkel, R.; and Zechner, J.. “Dynamic Capital Structure Choice: Theory and Tests.” Journal of Finance, 44 (1989), 1940.Google Scholar
Flannery, M. J., and Hankins, K. W.. “Estimating Dynamic Panel Models in Corporate Finance.” Journal of Corporate Finance, 19 (2013), 119.Google Scholar
Gormley, T. A., and Matsa, D. A.. “Common Errors: How to (and Not to) Control for Unobserved Heterogeneity.” Review of Financial Studies, 27 (2014), 617661.Google Scholar
Hennessy, C. A., and Whited, T. M.. “Debt Dynamics.” Journal of Finance, 60 (2005), 11291165.Google Scholar
Hermalin, B. E., and Weisbach, M. S.. “Endogenously Chosen Boards of Directors and Their Monitoring of the CEO.” American Economic Review, 88 (1998), 96118.Google Scholar
Hoechle, D.; Schmid, M.; Walter, I.; and Yermack, D.. “How Much of the Diversification Discount Can Be Explained by Poor Corporate Governance?Journal of Financial Economics, 103 (2012), 4160.Google Scholar
Iliev, P., and Welch, I.. “Reconciling Estimates of the Speed of Adjustment of Leverage Ratios.” Working Paper, University of California at Los Angeles (2011).Google Scholar
Matsa, D. A.Capital Structure as a Strategic Variable: Evidence from Collective Bargaining.” Journal of Finance, 65 (2010), 11971232.Google Scholar
Nickell, S. A.Biases in Dynamic Models with Fixed Effects.” Econometrica, 49 (1981), 1471–1426.Google Scholar
Perez-Gonzalez, F., and Yun, H.. “Risk Management and Firm Value: Evidence from Weather Derivatives.” Journal of Finance, 68 (2013), 21432176.Google Scholar
Petersen, M. A.Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches.” Review of Financial Studies, 22 (2009), 435480.Google Scholar
Roberts, M. R., and Whited, T. M.. “Endogeneity in Empirical Corporate Finance.” In Handbook of the Economics of Finance, Vol. 2, Constantinides, G., Harris, M., and Stulz, R., eds. Amsterdam, Netherlands: Elsevier, North-Holland (2012).Google Scholar
Strebulaev, I. A., and Whited, T. M.. “Dynamic Models and Structural Estimation in Corporate Finance.” Foundations and Trends in Finance, 6 (2012), 1163.Google Scholar
Thompson, S. B.Simple Formulas for Standard Errors That Cluster by Both Firm and Time.” Journal of Financial Economics, 99 (2011), 110.Google Scholar
Wintoki, M. B.; Linck, J. S.; and Netter, J. M.. “Endogeneity and the Dynamics of Internal Corporate Governance.” Journal of Financial Economics, 105 (2012), 581606.Google Scholar
Wooldridge, J. M. Econometric Analysis of Cross Section and Panel Data. 2nd ed. Cambridge, MA: MIT Press (2010).Google Scholar
Wooldridge, J. M.“Linear Panel Data Models.” Lecture Notes from Summer Tutorial in Modern Applied Tools of Econometrics, Michigan State University (2016).Google Scholar