In this paper we propose a new nonparametric test for conditional heteroskedasticity based on a measure of nonparametric goodness-of-fit (R2) 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 R2 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.
Cambridge University Press
SU, Liangjun and ULLAH, Aman.
A Nonparametric Goodness-of-fit-based Test for Conditional Heteroskedasticity. (2013). Econometric Theory. 29, (1), 187-212. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1557
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