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Central limit theorems for generalized U-statistics with applications in nonparametric specification
Authors:
Jiti Gao ab;
Yongmiao Hong cd
| Affiliations: | a School of Economics, The University of Adelaide, Adelaide, South Australia, Australia |
| b School of Mathematics and Statistics, The University of Western Australia, Crawley, Western Australia, Australia | |
| c Department of Economics and Department of Statistical Science, Cornell University, Ithaca, NY, USA | |
| d Wang Yanan Institute for Studies in Economics, Xiamen University, P.R. China |
DOI:
10.1080/10485250801899596
Publication Frequency:
8 issues per year
Subjects:
Mathematical Economics;
Mathematical Finance;
Medical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
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Abstract
In this paper, we establish some new central limit theorems for generalized U-statistics of dependent processes under some mild conditions. Such central limit theorems complement existing results available from both the econometrics literature and statistics literature. We then look at applications of the established results to a number of test problems in time series regression models.
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| Keywords: central limit theorem; nonparametric specification; quadratic form; strict stationarity; stochastic process |
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