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Testing Unit Root Based on Partially Adaptive Estimation

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  • Lima Luiz Renato

    (University of Tennessee - Knoxville)

  • Xiao Zhijie

    (Boston College)

Abstract

This paper proposes unit root tests based on partially adaptive estimation. The proposed tests provide an intermediate class of inference procedures that are more efficient than the traditional OLS-based methods and simpler than unit root tests based on fully adaptive estimation using nonparametric methods. Taking into account the well documented characteristic of heavy-tail behavior in economic and financial data, we consider unit root tests coupled with a class of partially adaptive M-estimators based on the student-t distributions, which includes the normal distribution as a limiting case. Monte Carlo experiments indicate that, in the presence of heavy tail distributions, the proposed test is more powerful than the traditional ADF test. We apply the proposed test to several macroeconomic time series that have heavy-tailed distributions. The unit root hypothesis is rejected in U.S. real GNP, supporting the literature of transitory shocks in output. However, evidence against unit root is not found in real exchange rate and nominal interest rate even when heavy-tail is taken into account.

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File URL: http://www.degruyter.com/view/j/jtse.2010.2.1/jtse.2010.2.1.1038/jtse.2010.2.1.1038.xml?format=INT
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Bibliographic Info

Article provided by De Gruyter in its journal Journal of Time Series Econometrics.

Volume (Year): 2 (2010)
Issue (Month): 1 (June)
Pages: 1-34

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Handle: RePEc:bpj:jtsmet:v:2:y:2010:i:1:n:2

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  1. Campbell, John & Mankiw, Gregory, 1987. "Are Output Fluctuations Transitory?," Scholarly Articles 3122545, Harvard University Department of Economics.
  2. Cheung, Yin-Wong & Lai, Kon S., 1997. "Bandwidth Selection, Prewhitening, and the Power of the Phillips-Perron Test," Econometric Theory, Cambridge University Press, vol. 13(05), pages 679-691, October.
  3. Robert J. Gordon, 1986. "The American Business Cycle: Continuity and Change," NBER Books, National Bureau of Economic Research, Inc, number gord86-1, May.
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Cited by:
  1. Amélie Charles & Olivier Darné, 2010. "A note on the uncertain trend in US real GNP: Evidence from robust unit root test," Working Papers hal-00547737, HAL.
  2. Charles, Amélie & Darné, Olivier, 2012. "Trends and random walks in macroeconomic time series: A reappraisal," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 167-180.

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