Using heteroscedasticity-non-consistent or heteroscedasticity-consistent variances in linear regression

Chor-yiu (CY) Sin and Cheng Few Lee

Econometrics and Statistics, 2021, vol. 18, issue C, 117-142

Abstract: The properties of the heteroscedasticity non-consistent variances and heteroscedasticity consistent variances are reviewed. Unlike the related existing results, the following cases are discussed separately: (i) the cases where the explanatory variables are strictly exogenous; and (ii) the cases where the explanatory variables may or may not be strictly exogenous. The latter cases allow weakly dependent explanatory variables such as those generating from an autoregressive process. New results on the original robust variance (denoted by HC0) and its variants (denoted by HC1,HC2,HC3,HC4 and HCj) are derived. In particular, the followings are shown: (i) the ordering of the original robust variance and its variants; (ii) the asymptotic equivalence among different variants of robust variance; and (iii) under quadratic form of heteroscedasticity (with mesokurtic/leptokurtic normalized error) or GARCH(1,1)-error, non-robust variance rejects more often than robust variance. Simulation studies suggest HC4 by and large does not over-rejects or mildly under-rejects.

Keywords: Asymptotic properties; Finite-sample properties; non-robust variance; Robust variance; Strictly exogenous; Weakly dependent (search for similar items in EconPapers)
JEL-codes: C12 C22 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:18:y:2021:i:c:p:117-142

DOI: 10.1016/j.ecosta.2020.10.002

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