Inference for Autocorrelations in the Possible Presence of a Unit Root

13 Pages Posted: 29 Mar 2004

See all articles by Dimitris N. Politis

Dimitris N. Politis

University of California, San Diego (UCSD) - Department of Mathematics

Joseph P. Romano

Stanford University - Department of Statistics

Michael Wolf

University of Zurich - Department of Economics

Abstract

We consider the problem of making inference for the autocorrelations of a time series in the possible presence of a unit root. Even when the underlying series is assumed to be strictly stationary, the robustness against a unit root is a desirable property to ensure good finite-sample coverage in case the series has a near unit root. In addition to discussing a confidence interval for the autocorrelation at a given lag, we also consider a simultaneous confidence band for the first k autocorrelations. We suggest the use of the subsampling method applied to properly studentized statistics, which results in confidence intervals and bands with asymptotically correct coverage probability. An application to practical model selection is given, while a simulation study examines finite-sample performance.

Keywords: Autocorrelations, confidence band, confidence interval, integrated series

Suggested Citation

Politis, Dimitris and Romano, Joseph P. and Wolf, Michael, Inference for Autocorrelations in the Possible Presence of a Unit Root. Available at SSRN: https://ssrn.com/abstract=513723

Dimitris Politis (Contact Author)

University of California, San Diego (UCSD) - Department of Mathematics ( email )

9500 Gilman Drive
La Jolla, CA 92093-0112
United States
858-534-5861 (Phone)
858-534-5273 (Fax)

Joseph P. Romano

Stanford University - Department of Statistics ( email )

Stanford, CA 94305
United States

Michael Wolf

University of Zurich - Department of Economics ( email )

Wilfriedstrasse 6
Zurich, 8032
Switzerland

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