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Testing Unit Root Based on Partially Adaptive Estimation

Author

Listed:
  • 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.

Suggested Citation

  • Lima Luiz Renato & Xiao Zhijie, 2010. "Testing Unit Root Based on Partially Adaptive Estimation," Journal of Time Series Econometrics, De Gruyter, vol. 2(1), pages 1-34, June.
    • Handle: RePEc:bpj:jtsmet:v:2:y:2010:i:1:n:2
    DOI: 10.2202/1941-1928.1038
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    Cited by:

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    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.
    3. Flôres Junior, Renato Galvão, 2004. "On the use (fulness) of CGE modelling in trade negotiations and policy," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 564, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

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    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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