Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches
Mitchell A. Petersen
Northwestern University - Kellogg School of Management; National Bureau of Economic Research (NBER)
Kellogg Finance Dept. Working Paper No. 329
AFA 2006 Boston Meetings Paper
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.
Number of Pages in PDF File: 68
Keywords: Clustered standard errors, Rogers standard errors, White standard errors, Fama-MacBeth standard errors, Fixed effect models, Panel Data
JEL Classification: G30, G12, C23
Date posted: February 5, 2005
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