Testing for Serial Correlation in Fixed-Effects Panel Data Models

Benjamin Born and Jörg Breitung ()

Econometric Reviews, 2016, vol. 35, issue 7, 1290-1316

Abstract: In this article, we propose various tests for serial correlation in fixed-effects panel data regression models with a small number of time periods. First, a simplified version of the test suggested by Wooldridge (2002) and Drukker (2003) is considered. The second test is based on the Lagrange Multiplier (LM) statistic suggested by Baltagi and Li (1995), and the third test is a modification of the classical Durbin--Watson statistic. Under the null hypothesis of no serial correlation, all tests possess a standard normal limiting distribution as N tends to infinity and T is fixed. Analyzing the local power of the tests, we find that the LM statistic has superior power properties. Furthermore, a generalization to test for autocorrelation up to some given lag order and a test statistic that is robust against time dependent heteroskedasticity are proposed.

Date: 2016
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Citations: View citations in EconPapers (61)

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DOI: 10.1080/07474938.2014.976524

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