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Business Cycle Analysis with Multivariate Markov Switching Models

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Author Info
Monica Billio () (Department of Economics, University Of Venice Cà Foscari)
Jacques Anas (Coe Rexecode, Paris)
Laurent Ferrara (Banque de Frances)
Marco Lo Duca (European Central Bank)

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Abstract

The class of Markov switching models can be extended in two main directions in a multivariate framework. In the first approach, the switching dynamics are introduced by way of a common latent factor. In the second approach a VAR model with parameters depending on one common Markov chain is considered (MSVAR). We will extend the MSVAR approach allowing for the presence of specific Markov chains in each equation of the VAR (MMSVAR). In the MMSVAR approach we also explore the introduction of correlated Markov chains which allow us to evaluate the relationships among phases in different economies or sectors and introduce causality relationships, which allow a more parsimonious representation. We apply our model to study the relationship between cyclical phases of the industrial production in the US and Euro zone. Moreover, we construct a MMS model to explore the cyclical relationship between the Euro zone industrial production and the industrial component of the European Sentiment Index.

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Publisher Info
Paper provided by University of Venice "Ca' Foscari", Department of Economics in its series Working Papers with number 2007_32.

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Length: 31
Date of creation: 2007
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Handle: RePEc:ven:wpaper:2007_32

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Related research
Keywords: Economic cycles; Multivariate models; Markov switching models; Common latent factors; Causality; Euro-zone;

Find related papers by JEL classification:
C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Jean-Jacques Vanhaelen & Luc Dresse & Jan De Mulder, 2000. "The Belgian industrial confidence indicator: leading indicator of economic activity in the euro area ?," Documents series 200011, National Bank of Belgium. [Downloadable!]
  2. Warne, Anders, 2000. "Causality and Regime Inference in a Markov Switching VAR," Working Paper Series 118, Sveriges Riksbank (Central Bank of Sweden). [Downloadable!]
  3. Vanhaelen, J.J. & Dresse, L. & de Mulder, J., 2000. "The Belgian Industrial Confidence Indicator: Leading Indicator of Economic Activity in the Euro Area?," Papers 12, Warwick - Development Economics Research Centre.
  4. Michael D. Boldin, 1996. "A Check on the Robustness of Hamilton's Markov Switching Model Approach to the Economic Analysis of the Business Cycle," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 1(1). [Downloadable!]
  5. Mosconi, Rocco & Seri, Raffaello, 2006. "Non-causality in bivariate binary time series," Journal of Econometrics, Elsevier, vol. 132(2), pages 379-407, June. [Downloadable!] (restricted)
  6. Robert Breunig & Serinah Najarian & Adrian Pagan, 2003. "Specification Testing of Markov Switching Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 65(s1), pages 703-725, December. [Downloadable!] (restricted)
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Monica Billio & Roberto Casarin, 2008. "Identifying Business Cycle Turning Points with Sequential Monte Carlo Methods," Working Papers 0815, University of Brescia, Department of Economics. [Downloadable!]
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