Testing for Serial Correlation in Three-dimensional Panel Data Models

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 sta...

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Bibliographic Details
Published in:Acta Mathematicae Applicatae Sinica 2017-02, Vol.33 (1), p.239-250
Main Authors: Wu, Jian-hong, Ding, Qing, Qin, Jin-xu
Format: Article
Language:English
Subjects:
Applications of Mathematics
Computer simulation
Correlation analysis
Economic models
Longitudinal studies
Math Applications in Computer Science
Mathematical and Computational Physics
Mathematics
Mathematics and Statistics
Null hypothesis
Regression analysis
Theoretical
Three dimensional models
三维
中心差分
假设检验
数据模型
模型估计
蒙特卡洛模拟
误差序列
面板
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Description
Summary: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.
ISSN:0168-9673
1618-3932
DOI:10.1007/s10255-017-0654-5