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Testing for serial independence of panel errors
Affiliation:1. Department of Economics and Center for Policy Research, 426 Eggers Hall, Syracuse, NY 13244-1020, USA;2. Department of Economics, 110 Eggers Hall, Syracuse, NY 13244-1020, USA;1. Department of Applied Informatics, Faculty of Science and Engineering, Hosei University, Koganei, Tokyo 184-8584, Japan;2. Division of System Engineering for Mathematics, Muroran Institute of Technology, Muroran, Hokkaido 050-8585, Japan;3. Oyama National College of Technology, Oyama, Tochigi 323-0806, Japan
Abstract:A test for the serial independence of errors in panel data models is proposed. The test is based on the difference between the joint empirical characteristic function of residuals at different lags and the product of their marginal empirical characteristic functions. The test is nuisance-parameter-free and powerful against any type of pairwise dependence at all lags. A simple random permutation procedure is used to approximate the limit distribution of the test. A Monte Carlo experiment illustrates the finite sample performance of the test, and supports that the test statistic based on the estimated residuals has the same asymptotic distribution as the corresponding statistic based on the unobservable true errors.
Keywords:Empirical characteristic function  Panel data  Parameter estimation uncertainty  Permutation test  Serial dependence  Unobservable errors
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