A NONPARAMETRIC GOODNESS-OF-FIT-BASED TEST FOR CONDITIONAL HETEROSKEDASTICITY

Content Provider	Scilit
Author	Su, Liangjun Ullah, Aman
Copyright Year	2012
Description	In this paper we propose a new nonparametric test for conditional heteroskedasticity based on a measure of nonparametric goodness-of-fit $(R^{2}$) that is obtained from the local polynomial regression of the residuals from a parametric regression on some covariates. We show that after being appropriately standardized, the nonparametric $R^{2}$ is asymptotically normally distributed under the null hypothesis and a sequence of Pitman local alternatives. We also prove the consistency of the test and propose a bootstrap method to obtain the bootstrap p-values. We conduct a small set of simulations and compare our test with some popular parametric and nonparametric tests in the literature.
Related Links	http://pdfs.semanticscholar.org/c140/d806e63ca84120cf26ce4a3082b1379e89dd.pdf https://www.cambridge.org/core/services/aop-cambridge-core/content/view/F008B39340CC9B9CBFA86669EC708391/S0266466612000278a.pdf/div-class-title-a-nonparametric-goodness-of-fit-based-test-for-conditional-heteroskedasticity-div.pdf
Ending Page	212
Page Count	26
Starting Page	187
ISSN	02664666
e-ISSN	14694360
DOI	10.1017/s0266466612000278
Journal	Econometric Theory
Issue Number	1
Volume Number	29
Language	English
Publisher	Cambridge University Press (CUP)
Publisher Date	2013-02-01
Access Restriction	Open
Subject Keyword	Econometric Theory Statistics and Probability Heteroskedasticity
Content Type	Text
Resource Type	Article
Subject	Social Sciences Economics and Econometrics