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Nonlinearly testing for a unit root in the presence of a break in the mean

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  • Gluschenko, Konstantin

Abstract

This paper deals with testing a time series with a structural break in its mean for a unit root when the break date is known. A nonlinear (with respect to coefficients) test equation is used, providing asymptotically efficient estimates. Finite-sample and quasi-asymptotic empirical distributions of the unit root test statistics are estimated, comparing them with those associated with the Perron-type equations. Asymptotic distributions of the nonlinear test statistics are found to be the Dickey-Fuller distributions. The nonlinear test proves to have more power than the test based on the linear model.

Suggested Citation

  • Gluschenko, Konstantin, 2004. "Nonlinearly testing for a unit root in the presence of a break in the mean," MPRA Paper 678, University Library of Munich, Germany, revised Sep 2005.
    • Handle: RePEc:pra:mprapa:678
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    File URL: https://mpra.ub.uni-muenchen.de/678/1/MPRA_paper_678.pdf
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    References listed on IDEAS

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    Cited by:

    1. Gluschenko, Konstantin, 2011. "Price convergence and market integration in Russia," Regional Science and Urban Economics, Elsevier, vol. 41(2), pages 160-172, March.

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    More about this item

    Keywords

    structural break; nonlinear regression; nonstandard distribution;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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