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NONPARAMETRIC NONSTATIONARITY TESTS

Published online by Cambridge University Press:  20 August 2013

Federico M. Bandi*
Affiliation:
Johns Hopkins University and Edhec-Risk
Valentina Corradi*
Affiliation:
University of Warwick
*
*Address Correspondence to Federico Bandi, Johns Hopkins Carey Business School, 100 International Drive, Baltimore, MD 21202; e-mail: fbandi1@jhu.edu; or to: Valentina Corradi, Department of Economics, University of Warwick, Coventry CV4 7AL, UK; e-mail: v.corradi@warwick.ac.uk
*Address Correspondence to Federico Bandi, Johns Hopkins Carey Business School, 100 International Drive, Baltimore, MD 21202; e-mail: fbandi1@jhu.edu; or to: Valentina Corradi, Department of Economics, University of Warwick, Coventry CV4 7AL, UK; e-mail: v.corradi@warwick.ac.uk

Abstract

We propose additive functional-based nonstationarity tests that exploit the different divergence rates of the occupation times of a (possibly nonlinear) process under the null of nonstationarity (stationarity) versus the alternative of stationarity (nonstationarity). We consider both discrete-time series and continuous-time processes. The discrete-time case covers Harris recurrent Markov chains and integrated processes. The continuous-time case focuses on Harris recurrent diffusion processes. Notwithstanding finite-sample adjustments discussed in the paper, the proposed tests are simple to implement and rely on tabulated critical values. Simulations show that their size and power properties are satisfactory. Our robustness to nonlinear dynamics provides a solution to the typical inconsistency problem between assumed linearity of a time series for the purpose of nonstationarity testing and subsequent nonlinear inference.

Type
ARTICLES
Copyright
Copyright © Cambridge University Press 2013 

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