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Testing for Panel Unit Roots in the Presence of an Unknown Structural Break and Cross-Sectional Dependency

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Author Info

  • Almasri, Abdullah

    (Karlstad University)

  • Månsson, Kristofer

    (HUI Research)

  • Sjölander, Pär

    (HUI Research)

  • Shukur, Ghazi

    (The Swedish Research Institute of Trade (HUI))

Abstract

This paper introduces two different non-parametric tests for panel unit root based on the wavelet decomposition of time series which may be used in the presence of cross-sectional dependency and an unknown structural break in the data. These tests are compared with the parametric IPS test proposed by Im, Pesaran and Shin (1997) and the Wald test suggested by Taylor and Sarno (1998). By means of Monte Carlo simulations, the results shown that the size and power properties of the new non-parametric tests are robust to cross sectional dependency of the error terms. Furthermore, it is shown that the tests may be used when the time series has an unknown structural break. These tests have also shown to have high power against the alternative hypothesis under the above mentioned conditioned, whiles the IPS and the Wald did not have any power to reject the alternative hypothesis in the presence of structural break in the data.

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Bibliographic Info

Paper provided by HUI Research in its series HUI Working Papers with number 63.

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Length: 17 pages
Date of creation: 18 Apr 2012
Date of revision:
Handle: RePEc:hhs:huiwps:0063

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Related research

Keywords: Panel unit root test; cross-sectional dependency; structural break; wavelet;

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  1. Ghazi Shukur & Panagiotis Mantalos, 2000. "A simple investigation of the Granger-causality test in integrated-cointegrated VAR systems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(8), pages 1021-1031.
  2. Gencay, Ramazan & Fan, Yanqin, 2007. "Unit Root Tests with Wavelets," MPRA Paper 9832, University Library of Munich, Germany.
  3. Pesaran, M.H., 2003. "A Simple Panel Unit Root Test in the Presence of Cross Section Dependence," Cambridge Working Papers in Economics 0346, Faculty of Economics, University of Cambridge.
  4. David Edgerton & Ghazi Shukur, 1999. "Testing autocorrelation in a system perspective testing autocorrelation," Econometric Reviews, Taylor & Francis Journals, vol. 18(4), pages 343-386.
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