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Limit theory for an explosive autoregressive process
Wang, XiaoHu; Yu, Jun - In: Economics letters 126 (2015), pp. 176-180
Persistent link: https://www.econbiz.de/10011377248
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New distribution theory for the estimation of structural break point in mean
Jiang, Liang; Wang, XiaoHu; Yu, Jun - In: Journal of econometrics 205 (2018) 1, pp. 156-176
Persistent link: https://www.econbiz.de/10012110250
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Har testing for spurious regression in trend
Phillips, Peter C. B.; Wang, XiaoHu; Zhang, Yonghui - In: Econometrics : open access journal 7 (2019) 4/50, pp. 1-28
The usual t test, the t test based on heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimators, and the heteroskedasticity and autocorrelation robust (HAR) test are three statistics that are widely used in applied econometric work. The use of these significance tests...
Persistent link: https://www.econbiz.de/10012160687
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HAR testing for spurious regression in trend
Phillips, Peter C. B.; Zhang, Yonghui; Wang, Xiaohu - 2018
Persistent link: https://www.econbiz.de/10011948826
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Asymptotic properties of the least squares estimator in local to unity processes with fractional Gaussian noise
Wang, Xiaohu; Xiao, Weilin; Yu, Jun - In: Essays in honor of Joon Y. Park : econometric theory, (pp. 73-95). 2023
Persistent link: https://www.econbiz.de/10014313249
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HAR Testing for Spurious Regression in Trend
Phillips, Peter C. B. - 2018
The usual t test, the t test based on heteroskedasticity and autocorrelation consistent (HAC) covariance matrix estimators, and the heteroskedasticity and autocorrelation robust (HAR) test are three statistics that are widely used in applied econometric work. The use of these significance tests...
Persistent link: https://www.econbiz.de/10012906697
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In-fill asymptotic theory for structural break point in autoregressions
Jiang, Liang; Wang, Xiaohu; Yu, Jun - In: Econometric reviews 40 (2021) 4, pp. 359-386
Persistent link: https://www.econbiz.de/10012515605
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Bubble testing under polynomial trends
Wang, Xiaohu; Yu, Jun - In: The econometrics journal 26 (2023) 1, pp. 25-44
Persistent link: https://www.econbiz.de/10013543273