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Size Distortions of Tests of the Null Hypothesis of Stationarity: Evidence and Implications for Applied Work

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Author Info
Mehmet Caner () (Bilkent University)
Lutz Kilian () (University of Michigan)

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Abstract

It is common in applied econometrics to test a highly persistent process under the null hypothesis against an alternative of a unit root process. We show that the conventional asymptotic critical values for the stationarity tests of Kwiatkowski et al. and Leybourne and McCabe may have substantial size distortions if the model under the null hypothesis is highly persistent. Such size distortions have not been recognized in the literature. The practical importance of these distortions is illustrated when testing for long-run purchasing power parity under current float. Size distortions of tests of the null of a unit root may be overcome by the use of finite sample or bootstrap critical values. We show such corrections are not possible when testing the null of stationarity, and we conclude that tests of this null cannot be recommended for applied work unless the sample size is very large.

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Publisher Info
Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1999 with number 511.

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Date of creation: 01 Mar 1999
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Handle: RePEc:sce:scecf9:511

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  1. Francis X. Diebold & Lutz Kilian, 1999. "Unit Root Tests Are Useful for Selecting Forecasting Models," NBER Working Papers 6928, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  2. Baharumshah, Ahmad Zubaidi & Aggarwal, Raj & Chan, Tze-Haw, 2005. "East Asian Real Exchange Rates and PPP: New Evidence from panel-data tests," MPRA Paper 2023, University Library of Munich, Germany, revised 2007. [Downloadable!]
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