Testing for a Unit Root in the Nonlinear STAR Framework

Andrew Snell, George Kapetanios, Y. Shin

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we propose a simple testing procedure to detect the presence of nonstationarity against nonlinear but globally stationary exponential smooth transition autoregressive processes. We provide an advance over the existing literature in three senses. First, we derive the limiting nonstandard distribution of the proposed tests. Second, we find via Monte Carlo simulation exercises that under the alternative of a globally stationary ESTAR process, our proposed test has better power than the standard Dickey–Fuller test, in the region of the null, where the processes are highly persistent. Third, we provide an application to ex post real interest rates and bilateral real exchange rates with the US Dollar from the 11 major OECD countries, and find our test is able to reject a unit root in many cases, whereas the linear DF tests fail, providing some evidence of nonlinear mean-reversion in both real interest and exchange rates.
Original languageEnglish
Pages (from-to)359-379
Number of pages20
JournalJournal of Econometrics
Volume112
Issue number2
Publication statusPublished - Feb 2003

Keywords

  • exponential smooth transition autoregressive model
  • unit roots
  • globally stationary nonlinear processes
  • monte carlo simulations
  • real interest and exchange rates

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