Markov Regime-Switching and Unit Root Tests

33 Pages Posted: 12 Dec 2000

See all articles by Charles R. Nelson

Charles R. Nelson

Dept of Economics

Jeremy Piger

University of Oregon - Department of Economics

Eric Zivot

University of Washington - Department of Economics

Date Written: September 2000

Abstract

We investigate the power and size performance of unit root tests when the true data generating process undergoes Markov regime-switching. All tests, including those robust to a single break in trend growth rate, have very low power against a process with a Markov-switching trend growth rate as in Lam (1990). However, for the case of business cycle non-linearities, unit root tests are very powerful against models used as alternatives to Lam (1990) that specify regime-switching in the transitory component of output. Under the null hypothesis, the received literature documents size distortions in Dickey-Fuller type tests caused by a single break in trend growth rate or variance. We find these results do not generalize to most parameterizations of Markov-switching in trend or variance. However, Markov-switching in variance can lead to over-rejection in tests robust to a single break in the level of trend.

Keywords: stochastic trends, deterministic trends, structural change, heteroskedasticity, unit root tests, and markov switching

Suggested Citation

Nelson, Charles R. and Piger, Jeremy M. and Zivot, Eric W., Markov Regime-Switching and Unit Root Tests (September 2000). Available at SSRN: https://ssrn.com/abstract=248028 or http://dx.doi.org/10.2139/ssrn.248028

Charles R. Nelson (Contact Author)

Dept of Economics ( email )

Box 353330
Seattle, WA 98195-3330
United States

Jeremy M. Piger

University of Oregon - Department of Economics ( email )

Eugene, OR 97403
United States

Eric W. Zivot

University of Washington - Department of Economics ( email )

Box 353330
Seattle, WA 98195-3330
United States
206-543-6715 (Phone)
206-685-7477 (Fax)

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
268
Abstract Views
2,008
rank
142,487
PlumX Metrics