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Moment-based tests for individual and time effects in panel data models

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  • Wu, Jianhong
  • Li, Guodong

Abstract

This paper proposes two Hausman-type tests respectively for individual and time effects in a two-way error component regression model by comparing estimators of the variance of the idiosyncratic error at different robust levels. They are both robust to the presence of the other effect, and the test for the individual effect has a larger asymptotic power than the corresponding ANOVA F test when the effects are correlated with covariates. Tests jointly for both effects are also discussed. Monte Carlo evidence shows their good size properties and better power properties than competing tests, and the application to the crime rate study gives further support.

Suggested Citation

  • Wu, Jianhong & Li, Guodong, 2014. "Moment-based tests for individual and time effects in panel data models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 569-581.
  • Handle: RePEc:eee:econom:v:178:y:2014:i:p3:p:569-581
    DOI: 10.1016/j.jeconom.2013.08.020
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Wu, Jianhong & Li, Jinchang, 2014. "Testing for individual and time effects in panel data models with interactive effects," Economics Letters, Elsevier, vol. 125(2), pages 306-310.
    2. Wu, Jianhong & Qin, Jinxu & Ding, Qing, 2015. "A moment-based test for individual effects in the error component model with incomplete panels," Statistics & Probability Letters, Elsevier, vol. 104(C), pages 153-162.
    3. Wu, Jianhong, 2016. "Robust random effects tests for two-way error component models with panel data," Economic Modelling, Elsevier, vol. 59(C), pages 1-8.

    More about this item

    Keywords

    Estimation of moment; Hausman-type test; Individual effect; Panel data; Time effect;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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