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Interconnections Between Eurozone and us Booms and Busts Using a Bayesian Panel Markov‐Switching VAR Model

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  • Monica Billio
  • Roberto Casarin
  • Francesco Ravazzolo
  • Herman K. Van Dijk

Abstract

Interconnections between Eurozone and United States booms and busts and among major Eurozone economies are analyzed using a Panel Markov-Switching VAR model. The model accommodates changes in low and high data frequencies and incorporates endogenous time-varying transition matrices of country-specific Markov chains. These country-specific Markov chains depend on their own past history and the history of other chains, thus allowing for interconnections between cycles, and an endogenous common Eurozone cycle is derived by aggregating the country-specific cycles. The model is estimated using a simulation based Bayesian approach in which an efficient multi-move sampling algorithm is defined to draw time-varying Markov-switching chains. Using industrial production growth and credit spread data for all countries, several empirical results have emerged. Recession, slow gro wth and expansion are empirically identified as three regimes with slow growth becoming persistent in the Eurozone in recent years different from the US. The Eurozone and the US regimes appear not fully synchronized, with evidence of more recessions in the Eurozone. Second, turning point analysis indicates larger synchronization at the beginning of the Great Financial Crisis: this shock affects the US first, leading the Eurozone cycle, and spreads then rapidly among these economies. Third, amplification effects influence recession probabilities for Eurozone countries when shocks occur. The evidence is different for the US where this reinforcement does not exist. In recent years there are more imbalances among regimes in Eurozone countries. Fourth, a credit shock results in substantial negative industrial production growth for several months in Germany, Spain and the US.
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Suggested Citation

  • Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. Van Dijk, 2016. "Interconnections Between Eurozone and us Booms and Busts Using a Bayesian Panel Markov‐Switching VAR Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(7), pages 1352-1370, November.
  • Handle: RePEc:wly:japmet:v:31:y:2016:i:7:p:1352-1370
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Roberto Casarin & Claudia Foroni & Massimiliano Marcellino & Francesco Ravazzolo, 2016. "Uncertainty Through the Lenses of A Mixed-Frequency Bayesian Panel Markov Switching Model," Working Papers 585, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    2. Hauzenberger, Niko & Huber, Florian, 2018. "Model instability in predictive exchange rate regressions," Working Papers in Economics 2018-8, University of Salzburg.
    3. Fisher, Mark & Jensen, Mark J., 2019. "Bayesian inference and prediction of a multiple-change-point panel model with nonparametric priors," Journal of Econometrics, Elsevier, vol. 210(1), pages 187-202.
    4. Francis, Neville & Owyang, Michael T. & Soques, Daniel, 2019. "Business Cycles Across Space and Time," Working Papers 2019-10, Federal Reserve Bank of St. Louis.
    5. repec:eee:chieco:v:51:y:2018:i:c:p:1-19 is not listed on IDEAS
    6. repec:gam:jecnmx:v:7:y:2019:i:1:p:8-:d:212762 is not listed on IDEAS
    7. Florian Huber & Michael Pfarrhofer & Thomas O. Zorner, 2018. "Stochastic model specification in Markov switching vector error correction models," Papers 1807.00529, arXiv.org.
    8. repec:spr:empeco:v:55:y:2018:i:4:d:10.1007_s00181-017-1337-z is not listed on IDEAS
    9. Liu, Laura & Matthes, Christian & Petrova, Katerina, 2018. "Monetary Policy across Space and Time," Working Paper 18-14, Federal Reserve Bank of Richmond.

    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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