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Estimating standard errors in finance panel data sets : comparing approaches

Author: Mitchell A Petersen; National Bureau of Economic Research.
Publisher: Cambridge, Mass. : National Bureau of Economic Research, ©2005.
Series: Working paper series (National Bureau of Economic Research), working paper no. 11280.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:
"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 and 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 Rogers standard errors, while asset pricing has used the Fama-MacBeth  Read more...
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Details

Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Mitchell A Petersen; National Bureau of Economic Research.
OCLC Number: 60395468
Notes: "April 2005."
Description: 63 pages : illustrations ; 22 cm.
Series Title: Working paper series (National Bureau of Economic Research), working paper no. 11280.
Responsibility: Mitchell A. Petersen.

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 and 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 Rogers standard errors, while asset pricing has used the Fama-MacBeth procedure to estimate standard errors. This paper will examine the different methods used in the literature and explain 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"--National Bureau of Economic Research web site.

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