A NONPARAMETRIC GOODNESS-OF-FIT-BASED TEST FOR CONDITIONAL HETEROSKEDASTICITY
In this paper we propose a new nonparametric test for conditional heteroskedasticity based on a measure of nonparametric goodness-of-fit (R<sup>2</sup>) 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<sup>2</sup> 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 <italic>p</italic>-values. We conduct a small set of simulations and compare our test with some popular parametric and nonparametric tests in the literature.
Year of publication: |
2013
|
---|---|
Authors: | Su, Liangjun ; Ullah, Aman |
Published in: |
Econometric Theory. - Cambridge University Press. - Vol. 29.2013, 01, p. 187-212
|
Publisher: |
Cambridge University Press |
Description of contents: | Abstract [journals.cambridge.org] |
Saved in:
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