MISC

2009年2月

COVARIANCE-BASED ORTHOGONALITY TESTS FOR REGRESSORS WITH UNKNOWN PERSISTENCE

ECONOMETRIC THEORY
  • Alex Maynard
  • ,
  • Katsumi Shimotsu

25
1
開始ページ
63
終了ページ
116
記述言語
英語
掲載種別
DOI
10.1017/S0266466608090038
出版者・発行元
CAMBRIDGE UNIV PRESS

This paper develops a new test of orthogonality based on a zero restriction on the covariance between the dependent variable and the predictor. The test provides a useful alternative to regression-based tests when conditioning variables have roots close or equal to unity. In this case standard predictive regression tests can suffer from well-documented size distortion. Moreover, tinder the alternative hypothesis, they force the dependent variable to share the same order of integration as the predictor, whereas in practice the dependent variable often appears stationary and the predictor may be near-nonstationary. By contrast, the new test does not enforce the same orders of integration and is therefore capable of detecting a rich set of alternatives to orthogonality that are excluded by the standard predictive regression model. Moreover, the test statistic has a standard normal limit distribution for both unit root and local-to-unity conditioning variables, without prior knowledge of the local-to-unity parameter. If the conditioning variable is stationary, the test remains conservative and consistent. Simulations suggest good small-sample performance. As an empirical application, we test for the predictability of stock returns using two persistent predictors, the dividend-price ratio and short-term interest rate.

リンク情報
DOI
https://doi.org/10.1017/S0266466608090038
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000262804400003&DestApp=WOS_CPL
ID情報
  • DOI : 10.1017/S0266466608090038
  • ISSN : 0266-4666
  • Web of Science ID : WOS:000262804400003

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