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Restoring monotonic power in Wald/LM-type tests

Wu, Jilin - In: Economics letters 126 (2015), pp. 13-17

Persistent link: https://www.econbiz.de/10011376375

Detecting structural changes under nonstationary volatility

Wu, Jilin - In: Economics letters 146 (2016), pp. 151-154

Persistent link: https://www.econbiz.de/10011619232

Adaptive estimation of AR∞ models with time-varying variances

Zhang, Erhua; Wu, Jilin - In: Economics letters 197 (2020), pp. 1-5

Persistent link: https://www.econbiz.de/10012511135

Testing for changing volatility

Wu, Jilin; Xiao, Zhijie - In: The econometrics journal 21 (2018) 2, pp. 192-217

Persistent link: https://www.econbiz.de/10012166609

Testing for trend specifications in panel data models

Wu, Jilin; Song, Xiaojun; Xiao, Zhijie - In: Journal of business & economic statistics : JBES ; a … 41 (2023) 2, pp. 453-466

Persistent link: https://www.econbiz.de/10014448241

A Powerful Test for Changing Trends in Time Series Models

Wu, Jilin; Xiao, Zhijie - In: Journal of Time Series Analysis 39 (2018) 4, pp. 488-501

Persistent link: https://www.econbiz.de/10012094914

Restoring monotonic power in Wald/LM-type tests

Wu, Jilin - In: Economics Letters 126 (2015) C, pp. 13-17

Wald/LM-type tests for a shift in mean often exhibit nonmonotonic power, due to incorrect estimation of long-run variance. In this paper, we propose a robust estimator of long-run variance that is built on nonparametric regression residuals and always converges to the true long-run variance...

Persistent link: https://www.econbiz.de/10011189494