Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/65839
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Journal article |
Title: | Simultaneous specification testing of mean and variance structures in nonlinear time series regression |
Author: | Chen, Song Xi Gao, Jiti |
Citation: | Econometric Theory, 2011; 27(4):792-843 |
Publisher: | Cambridge Univ Press |
Issue Date: | 2011 |
ISSN: | 0266-4666 |
School/Discipline: | School of Economics |
Statement of Responsibility: | Song Xi Chen, Jiti Gao |
Abstract: | This paper proposes a nonparametric simultaneous test for parametric specification of the conditional mean and variance functions in a time series regression model. The test is based on an empirical likelihood (EL) statistic that measures the goodness of fit between the parametric estimates and the nonparametric kernel estimates of the mean and variance functions. A unique feature of the test is its ability to distribute natural weights automatically between the mean and the variance components of the goodness-of-fit measure. To reduce the dependence of the test on a single pair of smoothing bandwidths, we construct an adaptive test by maximizing a standardized version of the empirical likelihood test statistic over a set of smoothing bandwidths. The test procedure is based on a bootstrap calibration to the distribution of the empirical likelihood test statistic. We demonstrate that the empirical likelihood test is able to distinguish local alternatives that are different from the null hypothesis at an optimal rate. |
Rights: | Copyright © Cambridge University Press 2011 |
DOI: | 10.1017/S0266466610000502 |
Appears in Collections: | Economics publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.