Testing for error cross-sectional uncorrelatedness in a two-way error components panel data model

Guangyu Mao

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 19, 4808-4839

Abstract: This paper proposes a new test for the error cross-sectional uncorrelatedness in a two-way error components panel data model based on large panel data sets. By virtue of an existing statistic under the raw data circumstance, an analogous test statistic using the within residuals of the model is constructed. We show that the resulting statistic needs bias correction to make valid inference, and then propose a method to implement feasible correction. Simulation shows that the test based on the feasible bias-corrected statistic performs well. Additionally, we employ a real data set to illustrate the use of the new test.

Date: 2018
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DOI: 10.1080/03610926.2018.1446087

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