Estimating standard errors in finance panel data sets

comparing approaches

Estimating standard errors in finance panel d ...
Mitchell A. Petersen, Mitchell ...
Not in Library

My Reading Lists:

Create a new list

Check-In

×Close
Add an optional check-in date. Check-in dates are used to track yearly reading goals.
Today


Buy this book

Last edited by MARC Bot
December 13, 2020 | History

Estimating standard errors in finance panel data sets

comparing approaches

"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.

Publish Date
Language
English

Buy this book

Edition Availability
Cover of: Estimating standard errors in finance panel data sets
Estimating standard errors in finance panel data sets: comparing approaches
2005, National Bureau of Economic Research
Electronic resource in English

Add another edition?

Book Details


Edition Notes

Also available in print.
Includes bibliographical references.
Title from PDF file as viewed on 5/5/2005.
System requirements: Adobe Acrobat Reader.
Mode of access: World Wide Web.

Published in
Cambridge, MA
Series
NBER working paper series ;, working paper 11280, Working paper series (National Bureau of Economic Research : Online) ;, working paper no. 11280.

Classifications

Library of Congress
HB1

The Physical Object

Format
Electronic resource

ID Numbers

Open Library
OL3477973M
LCCN
2005617849

Community Reviews (0)

Feedback?
No community reviews have been submitted for this work.

Lists

This work does not appear on any lists.

History

Download catalog record: RDF / JSON
December 13, 2020 Edited by MARC Bot import existing book
December 5, 2010 Edited by Open Library Bot Added subjects from MARC records.
December 10, 2009 Created by WorkBot add works page