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Testing error serial correlation in fixed effects nonparametric panel data models

Author

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  • Green, Carl
  • Long, Wei
  • Hsiao, Cheng

Abstract

In this paper we consider the problem of testing serial correlation in fixed effects panel data model in a nonparametric framework. Using asymptotic results developed in Su and Lu (2013), we show that our test statistic has a standard normal distribution under the null hypothesis of zero serial correlation. The test statistic diverges to infinity at the rate of N under the alternative hypothesis that error is serially correlated, where N is the cross sectional sample size. Simulations show that the proposed test works well in finite sample applications.

Suggested Citation

  • Green, Carl & Long, Wei & Hsiao, Cheng, 2015. "Testing error serial correlation in fixed effects nonparametric panel data models," Journal of Econometrics, Elsevier, vol. 188(2), pages 466-473.
    • Handle: RePEc:eee:econom:v:188:y:2015:i:2:p:466-473
    DOI: 10.1016/j.jeconom.2015.03.011
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    References listed on IDEAS

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    More about this item

    Keywords

    Panel data model; Nonparametric; Test serial correlation; Fixed effects;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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