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Bayesian simultaneous determination of structural breaks and lag lengths

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  • Hultblad, Brigitta

    ()
    (Dept. of Economic Statistics, Stockholm School of Economics)

  • Karlsson, Sune

    ()
    (Dept. of Economics, Statistics and Informatics)

Abstract

The detection of structural change and determination of lag lengths are long-standing issues in time series analysis. This paper demonstrates how these can be successfully married in a Bayesian analysis. By taking account of the inherent uncertainty about the lag length when deciding on the number of structural breaks and vice versa we avoid some common pitfalls and are able to draw more robust conclusions. The approach is illustrated using both real and simulated data.

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File URL: http://swopec.hhs.se/hastef/papers/hastef0630.rev.pdf
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File URL: http://swopec.hhs.se/hastef/papers/hastef0630.sim.pdf
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Bibliographic Info

Paper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 630.

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Length: 20 pages
Date of creation: 08 Jun 2006
Date of revision:
Publication status: Forthcoming in Studies in Nonlinear Dynamics & Econometrics.
Handle: RePEc:hhs:hastef:0630

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Keywords: Regime shifts; Model uncertainty; Model averaging; Markov chain Monte Carlo; Real interest rate;

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  1. René Garcia & Pierre Perron, 1995. "An Analysis of the Real Interest Rate Under Regime Shifts," CIRANO Working Papers, CIRANO 95s-05, CIRANO.
  2. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, Econometric Society, vol. 66(1), pages 47-78, January.
  3. Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers, Princeton, Department of Economics - Econometric Research Program 338, Princeton, Department of Economics - Econometric Research Program.
  4. Rappoport, Peter & Reichlin, Lucrezia, 1989. "Segmented Trends and Non-stationary Time Series," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 99(395), pages 168-77, Supplemen.
  5. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, Elsevier, vol. 45(1-2), pages 39-70.
  6. Anindya Banerjee & Robin L. Lumsdaine & James H. Stock, 1990. "Recursive and Sequential Tests of the Unit Root and Trend Break Hypothesis: Theory and International Evidence," NBER Working Papers 3510, National Bureau of Economic Research, Inc.
  7. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 11(1), pages 1-15, January.
  8. Bai, Jushan & Lumsdaine, Robin L & Stock, James H, 1998. "Testing for and Dating Common Breaks in Multivariate Time Series," Review of Economic Studies, Wiley Blackwell, Wiley Blackwell, vol. 65(3), pages 395-432, July.
  9. Marriott, John & Newbold, Paul, 2000. "The strength of evidence for unit autoregressive roots and structural breaks: A Bayesian perspective," Journal of Econometrics, Elsevier, Elsevier, vol. 98(1), pages 1-25, September.
  10. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
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Cited by:
  1. Luoto, Jani, 2011. "Aggregate infrastructure capital stock and long-run growth: Evidence from Finnish data," Journal of Development Economics, Elsevier, Elsevier, vol. 94(2), pages 181-191, March.

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