Hostname: page-component-784d4fb959-pn44h Total loading time: 0 Render date: 2025-07-14T05:20:41.410Z Has data issue: false hasContentIssue false

TESTS OF NONNESTED HYPOTHESES IN NONSTATIONARY REGRESSIONS WITH AN APPLICATION TO MODELING INDUSTRIAL PRODUCTION

Published online by Cambridge University Press:  01 March 2000

John C. Chao
Affiliation:
University of Maryland
Norman R. Swanson
Affiliation:
Texas A&M University

Abstract

In the context of I(1) time series, we provide some asymptoticresults for the Davidson-MacKinnon J-type test. We examine both the case where our regressor sets x1t and x2t are notcointegrated, and the case where they are.In the former case, the OLS estimatorof the weighting coefficient from the artificial compound model converges at rate T to a mixed normal distribution, and the associated t-statistic has an asymptotic standard normal distribution.In the latter case, we find that the J-test also has power against violation ofweak exogeneity (with respect to the short-run coefficients of the null model),which is caused by correlation between the disturbance of the null model andthat of the cointegrating equation linking x1t and x2t.Moreover, unlike the previous case, theOLS estimator of the weighting coefficient from the artificial compound modelconverges at \sqrt{T} to an asymptotic normaldistribution when the null model is specified correctly.In an empirical illustration, we use the tests to examinean industrial production data set for sixcountries.

Information

Type
Research Article
Copyright
© 2000 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable