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TESTING INSTABILITY IN A PREDICTIVE REGRESSION MODEL WITH NONSTATIONARY REGRESSORS

Published online by Cambridge University Press:  27 October 2014

Zongwu Cai ,
Yunfei Wang  and
Yonggang Wang
Zongwu Cai*
Affiliation:
University of Kansas and Xiamen University
Yunfei Wang
Affiliation:
Sun Trust Bank
Yonggang Wang
Affiliation:
First Tennessee Bank
*
*Address correspondence to Zongwu Cai, Department of Economics, University of Kansas, Lawrence, KS 66045, USA; e-mail: [email protected].
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Abstract

It is well known that allowing the coefficients to be time-varying in a predictive model with possibly nonstationary regressors can help to deal with instability in predictability associated with linear predictive models. In this paper, an L2-type test statistic is proposed to test the stability of the coefficient vector, and the asymptotic distributions of the proposed test statistic are developed under both null and alternative hypotheses. A Monte Carlo experiment is conducted to evaluate the finite sample performance of the proposed test statistic and an empirical example is examined to demonstrate the practical application of the proposed testing method.

Type
ARTICLES
Information
Econometric Theory , Volume 31 , Issue 5 , October 2015 , pp. 953 - 980
Copyright
Copyright © Cambridge University Press 2014 

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