A Heteroskedasticity Test Robust to Conditional Mean Misspecification
This paper proposes a new test statistic to deter the presence of heteroskedasticity. The proposed test does not require a parametric specification of the mean regression function in the first stage regression. The regression function is estimated nonparametrically by the kernel estimation method. The nonparametric residual is estimated and used as a proxy for the random disturbance term. This nonparametric residual is robust to regression function misspecification. Asymptotic normality is established using extensions of classical U-statistic theorems. The test statistic is computed using the nonparametric quantities, but the resulting inference has a standard chi-square distribution. Copyright 1992 by The Econometric Society.
Volume (Year): 60 (1992)
Issue (Month): 1 (January)
|Contact details of provider:|| Phone: 1 212 998 3820|
Fax: 1 212 995 4487
Web page: http://www.econometricsociety.org/
More information through EDIRC
|Order Information:|| Web: https://www.econometricsociety.org/publications/econometrica/access/ordering-back-issues Email: |
When requesting a correction, please mention this item's handle: RePEc:ecm:emetrp:v:60:y:1992:i:1:p:159-71. See general information about how to correct material in RePEc.
If references are entirely missing, you can add them using this form.