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Testing for Unit Roots in Models with Structural Change

Published online by Cambridge University Press:  11 February 2009

Joon Y. Park  and
Jaewhan Sung
Joon Y. Park
Affiliation:
Seoul National University
Jaewhan Sung
Affiliation:
Korea Economic Research Institute
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Abstract

This paper considers the unit root tests in models with structural change. Particular attention is given to their dependency on the limiting ratios of the subsample sizes between breaks. The dependency is analyzed in detail, and the invariant testing procedure based on a transformed model is developed. The required transformation is essentially identical to the generalized least-squares correction for heteroskedasticity. The limiting distributions of the new tests do not depend on the relative sizes of the subsamples and are shown to be simple mixtures of the limiting distributions of the corresponding tests from the independent unit root models without structural change.

Type
Articles
Information
Econometric Theory , Volume 10 , Issue 5 , December 1994 , pp. 917 - 936
Copyright
Copyright © Cambridge University Press 1994

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References

1Andrews, D.W.K.Heteroskedasticity and autocorrelation consistent co-variance matrix estimation. Econometrica 59 (1991): 817–858.CrossRefGoogle Scholar
2Dickey, D.A. & Fuller, W.A.. Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74 (1979): 427–431.Google Scholar
3Dickey, D.A. & Fuller, W.A.. Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica 49 (1981): 1057–1072.CrossRefGoogle Scholar
4Doob, J.L.Stochastic Processes. New York: Wiley, 1953.Google Scholar
5Nelson, C.R. & Plosser, C.I.. Trends and random walks in macroeconomic time series. Journal of Monetary Economics 10 (1982): 139–162.CrossRefGoogle Scholar
6Ouliaris, S., Park, J.Y. & Phillips, P.C.B.. Testing for a unit root in the presence of a maintained trend. In Raj, B. (ed.), Advances in Econometrics and Modelling, pp. 7–28. Amsterdam: Kluwer, 1989.CrossRefGoogle Scholar
7Park, J.Y. & Choi, B.. A New Approach to Testing for a Unit Root. CAE working paper #88-23, Cornell University, Ithaca, New York, 1988.Google Scholar
8Park, J.Y. & Phillips, P.C.B.. Statistical inference in regressions with integrated processes: Part 1. Econometric Theory 4 (1988): 468–497.CrossRefGoogle Scholar
9Park, J.Y. & Phillips, P.C.B.. Statistical inference in regressions with integrated processes: Part 2. Econometric Theory 5 (1989): 95–131.CrossRefGoogle Scholar
10Perron, P.The great crash, the oil price shock, and the unit root hypothesis. Econometrica 57 (1989): 1361–1401.CrossRefGoogle Scholar
11Phillips, P.C.B.Time series regression with a unit root. Econometrica 55 (1987): 277–301.CrossRefGoogle Scholar
12Phillips, P.C.B.Towards a unified asymptotic theory for autoregression. Biometrika 74 (1987): 535–547.CrossRefGoogle Scholar
13Phillips, P.C.B. & Ouliaris, S.. Asymptotic properties of residual based tests for cointegration. Econometrica 58 (1990): 165–193.CrossRefGoogle Scholar
14Phillips, P.C.B. & Perron, P.Testing for a unit root in time series regression. Biometrika 75 (1988): 335–346.CrossRefGoogle Scholar
15Said & Dickey. Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika 71 (1984): 599–607.CrossRefGoogle Scholar
16Zivot, E. & Andrews, D.W.K.. Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business and Economic Statistics 10 (1992): 251–270.CrossRefGoogle Scholar