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Inference in Autoregression under Heteroskedasticity
Author(s) -
Phillips Peter C. B.,
Xu KeLi
Publication year - 2006
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2005.00466.x
Subject(s) - heteroscedasticity , mathematics , autoregressive model , inference , nonparametric statistics , econometrics , autoregressive conditional heteroskedasticity , vector autoregression , statistics , computer science , artificial intelligence , volatility (finance)
. A scalar p th‐order autoregression (AR( p )) is considered with heteroskedasticity of the unknown form delivered by a transition function of time. A limit theory is developed and three heteroskedasticity‐robust test statistics are proposed for inference, one of which is based on the nonparametric estimation of the variance function. The performance of the resulting testing procedures in finite samples is compared in simulations and some suggestions for practical application are given.