Abstract

http://ssrn.com/abstract=661481
 
 

References (58)



 
 

Citations (1,260)



 


 



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)

May, 2006

Kellogg Finance Dept. Working Paper No. 329
AFA 2006 Boston Meetings Paper

Abstract:     
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

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Date posted: February 5, 2005  

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: http://ssrn.com/abstract=661481 or http://dx.doi.org/10.2139/ssrn.661481

Contact Information

Mitchell A. Petersen (Contact Author)
Northwestern University - Kellogg School of Management ( email )
2001 Sheridan Road
Evanston, IL 60208
United States
847-467-1281 (Phone)
847-491-5719 (Fax)
National Bureau of Economic Research (NBER) ( email )
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
847-467-1281 (Phone)
847-491-5719 (Fax)
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