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Interactions between Eurozone and US Booms and Busts: A Bayesian Panel Markov-switching VAR Model

Author

Listed:
  • Monica Billio

    (University of Venice, GRETA Assoc. and School for Advanced Studies in Venice, Italy)

  • Roberto Casarin

    (University of Venice, GRETA Assoc. and School for Advanced Studies in Venice, Italy)

  • Francesco Ravazzolo

    (Norges Bank and BI Norwegian Business School, Norway)

  • Herman K. van Dijk

    (Erasmus University Rotterdam, and VU University Amsterdam, The Netherlands)

Abstract

Interactions between the eurozone and US booms and busts and among major eurozone economies are analyzed by introducing a panel Markov-switching VAR model well suitable for a multi-country cyclical analysis. The model accommodates changes in low and high data frequencies and endogenous time-varying transition matrices of the country-specific Markov chains. The transition matrix of each Markov chain depends on its own past history and on the history of the other chains, thus allowing for modeling of the interactions between cycles. An endogenous common eurozone cycle is derived by aggregating country-specific cycles. The model is estimated using a simulation based Bayesian approach in which an efficient multi-move strategy algorithm is defined to draw common time-varying Markov-switching chains. Our results show that the US and eurozone cycles are not fully synchronized over the 1991-2013 sample period, with evidence of more recessions in the Eurozone. Shocks affect the US 1-quarter in advance of the eurozone, but these spread very rapidly among economies. An increase in the number of eurozone countries in recession increases the probability of the US to stay within recession, while the US recession indicator has a negative impact on the probability to stay in recession for eurozone countries. Turning point analysis shows that the cycles of Germany, France and Italy are closer to the US cycle than other countries. Belgium, Spain, and Germany, provide more timely information on the aggregate recession than Netherlands and France.

Suggested Citation

  • Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2013. "Interactions between Eurozone and US Booms and Busts: A Bayesian Panel Markov-switching VAR Model," Tinbergen Institute Discussion Papers 13-142/III, Tinbergen Institute, revised 01 Nov 2014.
  • Handle: RePEc:tin:wpaper:20130142
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    Cited by:

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    2. Sylvia Kaufmann, 2014. "K-state switching models with time-varying transition distributions – Does credit growth signal stronger effects of variables on inflation?," Working Papers 14.04, Swiss National Bank, Study Center Gerzensee.
    3. Aastveit, Knut Are & Jore, Anne Sofie & Ravazzolo, Francesco, 2016. "Identification and real-time forecasting of Norwegian business cycles," International Journal of Forecasting, Elsevier, vol. 32(2), pages 283-292.
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    5. Kaufmann, Sylvia, 2015. "K-state switching models with time-varying transition distributions—Does loan growth signal stronger effects of variables on inflation?," Journal of Econometrics, Elsevier, vol. 187(1), pages 82-94.
    6. Roberto Casarin & Fausto Corradin & Francesco Ravazzolo & Nguyen Domenico Sartore, 2020. "A Scoring Rule for Factor and Autoregressive Models Under Misspecification," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(2), pages 66-103, June.
    7. Netšunajev, Aleksei & Glass, Katharina, 2017. "Uncertainty and employment dynamics in the euro area and the US," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 48-62.
    8. Adam, Tomáš & Benecká, Soňa & Matějů, Jakub, 2018. "Financial stress and its non-linear impact on CEE exchange rates," Journal of Financial Stability, Elsevier, vol. 36(C), pages 346-360.
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    10. Tomas Adam & Sona Benecka & Jakub Mateju, 2014. "Risk Aversion, Financial Stress and Their Non-Linear Impact on Exchange Rates," Working Papers 2014/07, Czech National Bank.
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    More about this item

    Keywords

    Bayesian Model; Panel VAR; Markov-switching; International Business Cycles; Interaction Mechanism;
    All these keywords.

    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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