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Contemporaneous threshold autoregressive models: estimation, testing and forecasting

  • Michael J. Dueker
  • Martin Sola
  • Fabio Spagnolo

This paper proposes a contemporaneous smooth transition threshold autoregressive model (C-STAR) as a modification of the smooth transition threshold autoregressive model surveyed in Teräsvirta (1998), in which the regime weights depend on the ex ante probability that a latent regime-specific variable will exceed a threshold value. We argue that the contemporaneous model is well-suited to rational expectations applications (and pricing exercises), in that it does not require the initial regimes to be predetermined. We investigate the properties of the model and evaluate its finite-sample maximum likelihood performance. We also propose a method to determine the number of regimes based on a modified Hansen (1992) procedure. Furthermore, we construct multiple-step ahead forecasts and evaluate the forecasting performance of the model. Finally, an empirical application of the short term interest rate yield is presented and discussed. ; Earlier title: Contemporaneous threshold autoregressive models: estimation, forecasting and rational expectations applications

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Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2003-024.

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Date of creation: 2006
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Handle: RePEc:fip:fedlwp:2003-024
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