Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches

Kellogg Finance Dept. Working Paper No. 329

AFA 2006 Boston Meetings Paper

68 Pages Posted: 5 Feb 2005

Multiple version iconThere are 3 versions of this paper

Date Written: May, 2006


In both 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.

Keywords: Clustered standard errors, Rogers standard errors, White standard errors, Fama-MacBeth standard errors, Fixed effect models, Panel Data

JEL Classification: G30, G12, C23

Suggested Citation

Petersen, Mitchell A., Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches (May, 2006). Kellogg Finance Dept. Working Paper No. 329, AFA 2006 Boston Meetings Paper, Available at SSRN: or

Mitchell A. Petersen (Contact Author)

Northwestern University - Kellogg School of Management ( email )

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National Bureau of Economic Research (NBER) ( email )

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