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A Modified residual-based test for Serial Correlation in Linear Panel Data Models

Acta Mathematicae Applicatae Sinica 2014年第2期30卷 401-410页

作者： Jian-hong WU Wei-hua SU School of Statistics and Mathematics Zhejiang Gongshang University Zhejiang University of Finance and Economics Application of Statistical Science Research Center of Renmin University of China Key Research Institute

This paper suggests a modified serial correlation test for linear panel data models, which is based on the parameter estimates for an artificial autoregression modeled by differencing and centering residual vectors. Specifically, the differencing operator over the time index and the centering operator over the individual index are, respectively, used to eliminate the potential individual effects and time effects so that the resultant serial correlation test is robust to the two potential effects. Clearly, the test is also robust to the potential correlation between the covariates and the random effects. The test is asymptotically chi-squared distributed under the null hypothesis. Power study shows that the test can detect local alternatives distinct at the parametric rate from the null hypothesis. The finite sample properties of the test are investigated by means of Monte Carlo simulation experiments, and a real data example is analyzed for illustration.

关键词： panel data residual-based test serial correlation

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testing for Serial Correlation in Three-dimensional Panel Data Models

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Acta Mathematicae Applicatae Sinica 2017年第1期33卷 239-250页

作者： Jian-hong WU Qing DING Jin-xu QIN College of Mathematics and Science Shanghai Normal University Shanghai 200234 China

This paper studies serial correlation testing for a general three-dimensional panel data model. As a step for hypothesis testing, the robust within estimation of parameter coefficients is investigated, and shown to asymptotically consistent and normal under some mild conditions. A residual-based statistic is then constructed to test for serial correlation in the idiosyncratic errors, which is based on the parameter estimates for an artificial autoregression modeled by centering and differencing residuals. The test can be shown to asymptotically chisquare distributed under the null hypothesis. Power study shows that the test can detect local alternatives distinct at the parametric rate from the null hypothesis. The test needs no distribution assumptions of the error components, and is robust to the misspecification of various specific effects. Monte Carlo simulations are carried out for illustration.

关键词： three-dimensional panel data serial correlation residual-based test

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