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Identification of TAR models using recursive estimation

Author

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  • Miguel Ángel Bermejo
  • Daniel Peña
  • Ismael Sánchez

Abstract

This paper proposes an automatic procedure to identify threshold autoregressive models and specify the values of thresholds. The proposed procedure is based on the time-varying estimation of the parameters using an arranged autoregression. The proposed method not only allows for the automatic identification of the thresholds, but also has a superior identification performance than the competitors. The performance of the proposed procedure is illustrated using Monte Carlo experiments and real data. Copyright (C) 2010 John Wiley & Sons, Ltd.

Suggested Citation

  • Miguel Ángel Bermejo & Daniel Peña & Ismael Sánchez, 2011. "Identification of TAR models using recursive estimation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(1), pages 31-50, January.
  • Handle: RePEc:jof:jforec:v:30:y:2011:i:1:p:31-50
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    File URL: http://hdl.handle.net/10.1002/for.1188
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    Cited by:

    1. García-Martos, Carolina & Rodríguez, Julio & Sánchez, María Jesús, 2013. "Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities," Applied Energy, Elsevier, vol. 101(C), pages 363-375.

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