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Prior Elicitation In Multiple Change-Point Models

  • Gary Koop
  • Simon M. Potter

This article discusses Bayesian inference in change-point models. The main existing approaches treat all change-points equally, a priori, using either a Uniform prior or an informative hierarchical prior. Both approaches assume a known number of change-points. Some undesirable properties of these approaches are discussed. We develop a new Uniform prior that allows some of the change-points to occur out of sample. This prior has desirable properties, can be interpreted as "noninformative," and treats the number of change-points as unknown. Artificial and real data exercises show how these different priors can have a substantial impact on estimation and prediction. Copyright © (2009) by the Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1468-2354.2009.00547.x
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Article provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.

Volume (Year): 50 (2009)
Issue (Month): 3 (08)
Pages: 751-772

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Handle: RePEc:ier:iecrev:v:50:y:2009:i:3:p:751-772
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  1. John M Maheu & Stephen Gordon, 2007. "Learning, Forecasting and Structural Breaks," Working Papers tecipa-284, University of Toronto, Department of Economics.
  2. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
  3. Gary Koop & Simon M. Potter, 2001. "Are apparent findings of nonlinearity due to structural instability in economic time series?," Econometrics Journal, Royal Economic Society, vol. 4(1), pages 38.
  4. Lubos Pástor & Robert F. Stambaugh, . "The Equity Premium and Structural Breaks," Rodney L. White Center for Financial Research Working Papers 21-98, Wharton School Rodney L. White Center for Financial Research.
  5. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
  6. Pesaran, M Hashem & Pettenuzzo, Davide & Timmermann, Allan G, 2004. "Forecasting Time Series Subject to Multiple Structural Breaks," CEPR Discussion Papers 4636, C.E.P.R. Discussion Papers.
  7. Michael P. Clements & David F. Hendry, 2001. "Forecasting Non-Stationary Economic Time Series," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531895.
  8. Gary Koop & Simon M. Potter, 2004. "Forecasting and estimating multiple change-point models with an unknown number of change points," Staff Reports 196, Federal Reserve Bank of New York.
  9. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
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