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Outliers and Persistence in Threshold Autoregressive Processes: A Puzzle?

Author

Listed:
  • Yamin Ahmad

    (Department of Economics, University of Wisconsin - Whitewater)

  • Luiggi Donayre

    (Department of Economics, University of Minnesota - Duluth)

Abstract

We conduct Monte Carlo simulations to investigate the effects of outlier observations on the properties of linearity tests against threshold autoregressive (TAR) processes. By considering different specifications and levels of persistence of the data generating processes, we find that outliers distort the size of the test and that the distortion increases with the level of persistence. However, contrary to what one might expect, we also find that larger outliers could help improve the power of the test in the case of persistent TAR processes.

Suggested Citation

  • Yamin Ahmad & Luiggi Donayre, 2014. "Outliers and Persistence in Threshold Autoregressive Processes: A Puzzle?," Working Papers 14-02, UW-Whitewater, Department of Economics.
    • Handle: RePEc:uww:wpaper:14-02
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    File URL: http://www.uww.edu/documents/colleges/cobe/economics/wpapers/14-02_Ahmad_Donayre.pdf
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    Cited by:

    1. Rinke, Saskia, 2016. "The Influence of Additive Outliers on the Performance of Information Criteria to Detect Nonlinearity," Hannover Economic Papers (HEP) dp-575, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.

    More about this item

    Keywords

    Outliers; Persistence; Monte Carlo Simulations; Threshold Autoregressionn; Size; Power;
    All these keywords.

    JEL classification:

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

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