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Bayesian Analysis of Nonlinear Time Series Models with a Threshold

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Author Info
Lubrano, M.

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Abstract

This paper considers the Bayesian analysis of threshold regression models. It shows that this analysis can be conducted with simple deterministic numerical integration rules of low dimension. The shape of the posterior density is greatly determined by the type of threshold and of transition function considered. Unequal variances between the regimes usually adds one dimension to the integration problem, except in some cases where a simplification occurs.

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Publisher Info
Paper provided by Universite Aix-Marseille III in its series G.R.E.Q.A.M. with number 98a13.

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Length: 39 pages
Date of creation: 1998
Date of revision:
Handle: RePEc:fth:aixmeq:98a13

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Related research
Keywords: TIME SERIES MODELS

Other versions of this item:

Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other

Cited by:
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  1. Michael J. Dueker & Martin Sola & Fabio Spagnolo, 2006. "Contemporaneous threshold autoregressive models: estimation, testing and forecasting," Working Papers 2003-024, Federal Reserve Bank of St. Louis. [Downloadable!]
    Other versions:
  2. Deborah Gefang & Rodney Strachan, 2008. "Nonlinear Impacts of International Business Cycles on the UK — a Bayesian Smooth Transition VAR," Discussion Papers in Economics 08/4, Department of Economics, University of Leicester. [Downloadable!]
  3. Simon M. Potter, 1999. "Nonlinear time series modelling: an introduction," Staff Reports 87, Federal Reserve Bank of New York. [Downloadable!]
    Other versions:
  4. Deborah Gefang, 2008. "Revisiting money-output causality from a Bayesian logistic smooth transition VECM perspective," Discussion Papers in Economics 08/5, Department of Economics, University of Leicester. [Downloadable!]
Statistics
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