Testing for serial correlation in linear panel-data models

Because serial correlation in linear panel-data models biases the standard errors and causes the results to be less efficient, researchers need to identify serial correlation in the idiosyncratic error term in a panel-data model. A new test for serial correlation in random- or fixed-effects one-way models derived by Wooldridge (2002) is attractive because it can be applied under general conditions and is easy to implement. This paper presents simulation evidence that the new Wooldridge test has good size and power properties in reasonably sized samples.


Issue Date:
2003
Publication Type:
Journal Article
DOI and Other Identifiers:
st0039 (Other)
PURL Identifier:
http://purl.umn.edu/116069
Published in:
Stata Journal, Volume 03, Number 2
Page range:
168-177
Total Pages:
10

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 Record created 2017-04-01, last modified 2017-08-26

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