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The Effects of Small Sample Bias in Threshold Autoregressive Models

Author

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  • Yamin Ahmad

    (Department of Economics, University of Wisconsin - Whitewater)

Abstract

This paper investigates the properties of a class of models which incorporate nonlinear dynamics, known as Threshold Autoregressive (TAR) models. Simulations show that within the context of the real exchange rate literature, a threshold model of exchange rates exhibits significant small sample bias even with long time series data. The results of this paper has severe implications for the properties of estimated coefficients within TAR models.

Suggested Citation

  • Yamin Ahmad, 2007. "The Effects of Small Sample Bias in Threshold Autoregressive Models," Working Papers 07-01, UW-Whitewater, Department of Economics, revised Jun 2007.
    • Handle: RePEc:uww:wpaper:07-01
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    File URL: http://www.uww.edu/documents/colleges/cobe/economics/wpapers/07_01_Ahmad.pdf
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    Cited by:

    1. Ahmad, Yamin & Lo, Ming Chien & Mykhaylova, Olena, 2013. "Causes of nonlinearities in low-order models of the real exchange rate," Journal of International Economics, Elsevier, vol. 91(1), pages 128-141.
    2. Yamin Ahmad & Stuart Glosser, 2011. "Searching for nonlinearities in real exchange rates," Applied Economics, Taylor & Francis Journals, vol. 43(15), pages 1829-1845.
    3. Ahmad, Yamin & Lo, Ming Chien & Mykhaylova, Olena, 2013. "Volatility and persistence of simulated DSGE real exchange rates," Economics Letters, Elsevier, vol. 119(1), pages 38-41.
    4. Ahmad Yamin & Donayre Luiggi, 2016. "Outliers and persistence in threshold autoregressive processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 37-56, February.

    More about this item

    Keywords

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    JEL classification:

    • F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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