standarderror (Mitch peterson)

Standarderror - January 2007 Estimating Standard Errors in Finance Panel Data Sets Comparing Approaches Mitchell A Petersen Kellogg School of

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January, 2007 Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches Mitchell A. Petersen Kellogg School of Management, Northwestern University and NBER Abstract In corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms or across time, and OLS standard errors can be biased. Historically, the two literatures have used different solutions to this problem. Corporate finance has relied on clustered standard errors, while asset pricing has used the Fama-MacBeth procedure. This paper examines the different methods used in the literature and explains when the different methods yield the same (and correct) standard errors and when they diverge. The intent is to provide intuition as to why the different approaches sometimes give different answers and give researchers guidance for their use. I thank the Center for Financial Institutions and Markets at Northwestern University’s Kellogg School for support. In writing this paper, I have benefitted greatly from discussions with John Ammer, Robert Chirinko, Toby Daglish, Kent Daniel, Joey Engelberg, Gene Fama, Michael Faulkender, Wayne Ferson, Mariassunta Giannetti, John Graham, William Greene, Chris Hansen, Wei Jiang, Toby Moskowitz, Chris Polk, Joshua Rauh, Michael Roberts, Paola Sapienza, Georgios Skoulakis, Doug Staiger, Jeff Wooldridge and Annette Vissing-Jorgensen as well as the comments of seminar participants at the American Finance Association Meetings, Arizona State University, Federal Reserve Bank of Chicago, Financial Management Association Meetings, Harvard Business School, Duke University, Northwestern University, Stanford University, Stockholm School of Economics, and the Universities of California at Berkeley, Chicago, Columbia, Florida, Iowa, Michigan, Pennsylvania (Wharton), Texas at Dallas and Washington. The research assistance of Marie Grabinski, Nick Halpern, Casey Liang, Matt Withey, Sungjoon Park, and Amit Patel is greatly appreciated.
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1 I searched papers published in the Journal of Finance , the Journal of Financial Economics , and the Review of Financial Studies in the years 2001- 2004 for a description of how the coefficients and standard errors were estimated in a panel data set. Panel data sets are data sets which contain multiple observations on a given unit. This can be multiple observations per firm, per industry, per year, or per country. I refer to the unit (e.g. firm or industry) as a cluster. I included both linear regressions as well as non-linear techniques such as logits and tobits in my survey. I included only papers which report at least five observations in each dimension (e.g. firms and years). 207 papers met the selection criteria. Papers which did not report the method for estimating the standard errors, or reported correcting the standard errors only for heteroscedasticity (i.e. White standard errors which are not robust to within cluster dependence) are coded as not having corrected the standard errors for within cluster dependence. Where the paper’s description was ambiguous,
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This note was uploaded on 01/10/2011 for the course ECON 7427 taught by Professor Hamersma during the Spring '06 term at University of Florida.

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Standarderror - January 2007 Estimating Standard Errors in Finance Panel Data Sets Comparing Approaches Mitchell A Petersen Kellogg School of

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