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Reducing the Size Distortion of the KPSS Test

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  • Eiji Kurozumi
  • Shinya Tanaka

Abstract

This paper proposes a new stationarity test based on the KPSS test with less size distortion. We extend the boundary rule proposed by Sul, Phillips and Choi (2005) to the autoregressive spectral density estimator and parametrically estimate the long-run variance. We also derive the finite sample bias of the numerator of the test statistic up to the 1/T order and propose a correction to the bias term in the numerator. Finite sample simulations show that the correction term effectively reduces the bias in the numerator and that the finite sample size of our test is close to the nominal one as long as the long-run parameter in the model satisfies the boundary condition.

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File URL: http://gcoe.ier.hit-u.ac.jp/research/discussion/2008/pdf/gd09-085.pdf
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Bibliographic Info

Paper provided by Institute of Economic Research, Hitotsubashi University in its series Global COE Hi-Stat Discussion Paper Series with number gd09-085.

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Date of creation: Sep 2009
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Handle: RePEc:hst:ghsdps:gd09-085

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Keywords: Stationary test; size distortion; boundary rule; bias correction;

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  1. Josep Carrion-i-Silvestre & Andreu Sansó, 2006. "A guide to the computation of stationarity tests," Empirical Economics, Springer, vol. 31(2), pages 433-448, June.
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Cited by:
  1. Eiji Kurozumi & Daisuke Yamazaki & Kaddour Hadri, 2012. "Covariate Unit Root Test for Cross-Sectionally Dependent Panel Data," Global COE Hi-Stat Discussion Paper Series gd12-256, Institute of Economic Research, Hitotsubashi University.
  2. Anton Skrobotov, 2012. "Bias Correction of KPSS Test with Structural Break for Reducing of Size Distortion," Working Papers 0043, Gaidar Institute for Economic Policy, revised 2012.

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