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Unit root quantile autoregression testing using covariates

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  • Galvao Jr., Antonio F.
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    Abstract

    This paper extends unit root tests based on quantile regression proposed by Koenker and Xiao [Koenker, R., Xiao, Z., 2004. Unit root quantile autoregression inference, Journal of the American Statistical Association 99, 775-787] to allow stationary covariates and a linear time trend. The limiting distribution of the test is a convex combination of Dickey-Fuller and standard normal distributions, with weight determined by the correlation between the equation error and the regression covariates. A simulation experiment is described, illustrating the finite sample performance of the unit root test for several types of distributions. The test based on quantile autoregression turns out to be especially advantageous when innovations are heavy-tailed. An application to the CPI-based real exchange rates using four different countries suggests that real exchange rates are not constant unit root processes.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Econometrics.

    Volume (Year): 152 (2009)
    Issue (Month): 2 (October)
    Pages: 165-178

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    Handle: RePEc:eee:econom:v:152:y:2009:i:2:p:165-178

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    Web page: http://www.elsevier.com/locate/jeconom

    Related research

    Keywords: Unit root Quantile Covariates Linear time trend;

    References

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    Cited by:
    1. Lijuan Huo & Tae-Hwan Kim & Yunmi Kim, 2013. "Testing for Autocorrelation in Quantile Regression Models," Working papers 2013rwp-54, Yonsei University, Yonsei Economics Research Institute.
    2. Mehdi Hosseinkouchack & Maik Wolters, 2012. "Do large recessions reduce output permanently?," Kiel Working Papers 1815, Kiel Institute for the World Economy.
    3. Fossati, Sebastian, 2011. "Unit Root Testing with Stationary Covariates and a Structural Break in the Trend Function," Working Papers 2011-10, University of Alberta, Department of Economics.
    4. Peter Tillmann & Maik H. Wolters, 2012. "The changing dynamics of US inflation persistence: a quantile regression approach," MAGKS Papers on Economics 201206, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    5. Fossati, Sebastian, 2012. "Covariate unit root tests with good size and power," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3070-3079.
    6. Lee, Cheng-Feng & Hu, Te-Chung & Li, Ping-Cheng & Tsong, Ching-Chuan, 2013. "Asymmetric behavior of unemployment rates: Evidence from the quantile covariate unit root test," Japan and the World Economy, Elsevier, vol. 28(C), pages 72-84.
    7. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2012. "Quantile regression for long memory testing: A case of realized volatility," Working Papers w201207, Banco de Portugal, Economics and Research Department.

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