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On marginal likelihood computation in change-point models

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Author Info

  • Bauwens, Luc
  • Rombouts, Jeroen V.K.

Abstract

Change-point models are useful for modeling time series subject to structural breaks. For interpretation and forecasting, it is essential to estimate correctly the number of change points in this class of models. In Bayesian inference, the number of change points is typically chosen by the marginal likelihood criterion, computed by Chib’s method. This method requires one to select a value in the parameter space at which the computation is performed. Bayesian inference for a change-point dynamic regression model and the computation of its marginal likelihood are explained. Motivated by results from three empirical illustrations, a simulation study shows that Chib’s method is robust with respect to the choice of the parameter value used in the computations, among posterior mean, mode and quartiles. However, taking into account the precision of the marginal likelihood estimator, the overall recommendation is to use the posterior mode or median. Furthermore, the performance of the Bayesian information criterion, which is based on maximum likelihood estimates, in selecting the correct model is comparable to that of the marginal likelihood.

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Bibliographic Info

Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

Volume (Year): 56 (2012)
Issue (Month): 11 ()
Pages: 3415-3429

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Handle: RePEc:eee:csdana:v:56:y:2012:i:11:p:3415-3429

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Web page: http://www.elsevier.com/locate/csda

Related research

Keywords: BIC; Change-point model; Chib’s method; Marginal likelihood;

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References

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  1. M. Hashem Pesaran & Davide Pettenuzzo & Allan Timmermann, 2004. "Forecasting Time Series Subject to Multiple Structural Breaks," CESifo Working Paper Series 1237, CESifo Group Munich.
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Cited by:
  1. Joshua C.C. Chan & Angelia L. Grant, 2014. "Fast Computation of the Deviance Information Criterion for Latent Variable Models," CAMA Working Papers 2014-09, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  2. van den Hout, Ardo & Muniz-Terrera, Graciela & Matthews, Fiona E., 2013. "Change point models for cognitive tests using semi-parametric maximum likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 684-698.

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