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Uniform Test for Predictive Regression With AR Errors
Authors:Chenxue Li  Deyuan Li  Liang Peng
Institution:1. Department of Mathematics and Statistics, Georgia State University, Atlanta, GA 30303 (chenxuelee@foxmail.com);2. School of Management, Fudan University, Shanghai, 200433, P.R. China (deyuanli@fudan.edu.cn);3. Department of Risk Management and Insurance, Georgia State University, Atlanta, 30303, GA (lpeng@gsu.edu)
Abstract:Testing predictability is of importance in economics and finance. Based on a predictive regression model with independent and identically distributed errors, some uniform tests have been proposed in the literature without distinguishing whether the predicting variable is stationary or nearly integrated. In this article, we extend the empirical likelihood methods of Zhu, Cai, and Peng with independent errors to the case of an AR error process. Again, the proposed new tests do not need to know whether the predicting variable is stationary or nearly integrated, and whether it has a finite variance or an infinite variance. A simulation study shows the new methodologies perform well in finite sample.
Keywords:AR errors  Empirical likelihood  Jackknife empirical likelihood  Predictive regression  Weighted score
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