In this paper, we use a moment-based method to test the existence of the individual and time effects in unbalanced panel data models with time-invariant regressors. Based on the difference of two variance estimators of idiosyncratic errors, three test statistics are proposed. The test statistics for individual (time) effect is robust when the time (individual) effect exists, and is robust for the correlation between explanatory variables and individual or time effect. Additionally, they do not require prior distributional assumptions on the error term. The asymptotic properties of estimators and the test statistics are given in this paper. The Monte Carlo simulations show that the test statistics have good power in finite samples at various situations and a real example is studied for illustration.
Citation: Ke Liu, Hanzhong Liu. Testing for individual and time effects in unbalanced panel data models with time-invariant regressors[J]. Electronic Research Archive, 2022, 30(12): 4574-4592. doi: 10.3934/era.2022232
In this paper, we use a moment-based method to test the existence of the individual and time effects in unbalanced panel data models with time-invariant regressors. Based on the difference of two variance estimators of idiosyncratic errors, three test statistics are proposed. The test statistics for individual (time) effect is robust when the time (individual) effect exists, and is robust for the correlation between explanatory variables and individual or time effect. Additionally, they do not require prior distributional assumptions on the error term. The asymptotic properties of estimators and the test statistics are given in this paper. The Monte Carlo simulations show that the test statistics have good power in finite samples at various situations and a real example is studied for illustration.
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Ke Liu, Hanzhong Liu. Testing for individual and time effects in unbalanced panel data models with time-invariant regressors[J]. Electronic Research Archive, 2022, 30(12): 4574-4592. doi: 10.3934/era.2022232
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