IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Interactions between eurozone and US booms and busts: A Bayesian panel Markov-switching VAR model

  • Monica Billio

    (University of Venice, GRETA Association and School for Advanced Studies in Venice)

  • Roberto Casarin

    (University of Venice, GRETA Association and School for Advanced Studies in Venice)

  • Francesco Ravazzolo

    ()

    (Norges Bank (Central Bank of Norway) and BI Norwegian Business School)

  • Herman K. van Dijk

    ()

    (Econometric Institute, Erasmus University Rotterdam, Econometrics Department VU University Amsterdam)

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 modelling 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, in particular during the 90's when the monetary union was planned. Larger synchronization occurs at beginning of the Great Financial Crisis. Shocks affect the US 1-quarter in advance of the eurozone, but these spread very rapidly among economies. There exist reinforcement effects in the recession probabilities and in the probabilities of exiting recessions for both eurozone and US cycles, and substantial differences in the phase transitions within the eurozone. 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. Moreover, 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.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.norges-bank.no/en/Published/Papers/Working-Papers/2013/WP-201320/
Download Restriction: no

Paper provided by Norges Bank in its series Working Paper with number 2013/20.

as
in new window

Length: 47 pages
Date of creation: 22 Aug 2013
Date of revision:
Handle: RePEc:bno:worpap:2013_20
Contact details of provider: Postal: Postboks 1179 Sentrum, 0107 Oslo
Phone: +47 22 31 60 00
Fax: +47 22 41 31 05
Web page: http://www.norges-bank.no/
Email:


More information through EDIRC

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.:

as in new window
  1. Marco Del Negro & Marc P. Giannoni & Frank Schorfheide, 2015. "Inflation in the Great Recession and New Keynesian Models," American Economic Journal: Macroeconomics, American Economic Association, vol. 7(1), pages 168-96, January.
  2. M. Hashem Pesaran & Til Schuermann & Scott M. Weiner, 2002. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Center for Financial Institutions Working Papers 01-38, Wharton School Center for Financial Institutions, University of Pennsylvania.
  3. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
  4. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended New Keynesian Phillips Curve Models with Non-filtered Data," Tinbergen Institute Discussion Papers 13-090/III, Tinbergen Institute.
  5. Lucrezia Reichlin & Mario Forni & Marc Hallin & Marco Lippi, 2001. "Coincident and leading indicators for the Euro area," ULB Institutional Repository 2013/10137, ULB -- Universite Libre de Bruxelles.
  6. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1 National Bureau of Economic Research, Inc.
  7. Harding, Don & Pagan, Adrian, 2011. "An Econometric Analysis of Some Models for Constructed Binary Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 86-95.
  8. Stephane Dees & Filippo di Mauro & M. Hashem Pesaran & L. Vanessa Smith, 2004. "Exploring the International Linkages of the Euro Area: A Global VAR Analysis," IEPR Working Papers 04.6, Institute of Economic Policy Research (IEPR).
  9. Kose, M. Ayhan & Otrok, Christopher & Prasad, Eswar, 2008. "Global Business Cycles: Convergence or Decoupling?," IZA Discussion Papers 3442, Institute for the Study of Labor (IZA).
  10. Canova, Fabio & Marrinan, Jane, 1998. "Sources and propagation of international output cycles: Common shocks or transmission?," Journal of International Economics, Elsevier, vol. 46(1), pages 133-166, October.
  11. Estrella, Arturo & Hardouvelis, Gikas A, 1991. " The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-76, June.
  12. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
  13. Sylvia Kaufmann, 2010. "Dating and forecasting turning points by Bayesian clustering with dynamic structure: a suggestion with an application to Austrian data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(2), pages 309-344.
  14. Michael P. Clements & Hans-Martin Krolzig, 1998. "A comparison of the forecast performance of Markov-switching and threshold autoregressive models of US GNP," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages C47-C75.
  15. Chang-Jin Kim & Christian J. Murray, 2002. "Permanent and transitory components of recessions," Empirical Economics, Springer, vol. 27(2), pages 163-183.
  16. Fabio Canova & Matteo Ciccarelli, 2007. "Estimating Multi-country VAR models," Discussion Papers 7_2007, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
  17. Don Harding & Adrian Pagan, 2000. "Disecting the Cycle: A Methodological Investigation," Econometric Society World Congress 2000 Contributed Papers 1164, Econometric Society.
  18. Allan W. Gregory & Allen C. Head & Jacques Raynauld, 1994. "Measuring World Business Cycles," Working Papers 902, Queen's University, Department of Economics.
  19. Hans-Martin Krolzig, 2000. "Predicting Markov-Switching Vector Autoregressive Processes," Economics Series Working Papers 2000-W31, University of Oxford, Department of Economics.
  20. Kim, Kenneth A. & Limpaphayom, Piman, 1997. "The effect of economic regimes on the relation between term structure and real activity in Japan," Journal of Economics and Business, Elsevier, vol. 49(4), pages 379-392.
  21. Jacques Anas & Monica Billio & Laurent Ferrara & Gian Luigi Mazzi, 2008. "A System For Dating And Detecting Turning Points In The Euro Area," Manchester School, University of Manchester, vol. 76(5), pages 549-577, 09.
  22. Lumsdaine, Robin L. & Prasad, Eswar, 2002. "Identifying the Common Component of International Economic Fluctuations: A New Approach," IZA Discussion Papers 487, Institute for the Study of Labor (IZA).
  23. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series," Tinbergen Institute Discussion Papers 13-011/III, Tinbergen Institute.
  24. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series," Tinbergen Institute Discussion Papers 13-011/III, Tinbergen Institute.
  25. Christopher A. Sims & Tao Zha, 1996. "Bayesian methods for dynamic multivariate models," FRB Atlanta Working Paper No. 96-13, Federal Reserve Bank of Atlanta.
  26. Simon Gilchrist & Egon Zakrajsek, 2012. "Credit Spreads and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 102(4), pages 1692-1720, June.
  27. Plosser, Charles I. & Geert Rouwenhorst, K., 1994. "International term structures and real economic growth," Journal of Monetary Economics, Elsevier, vol. 33(1), pages 133-155, February.
  28. Chang-Jin Kim & Jeremy Piger, 2000. "Common Stochastic Trends, Common Cycles, and Asymmetry in Economic Fluctuations," Discussion Papers in Economics at the University of Washington 0021, Department of Economics at the University of Washington.
  29. 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, vol. 11(1), pages 1-15, January.
  30. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," Review of Economic Studies, Oxford University Press, vol. 72(3), pages 821-852.
  31. Hamilton, James Douglas & Kim, Dong Heon, 2000. "A Re-examination of the Predictability of Economic Activity Using the Yield Spread," University of California at San Diego, Economics Working Paper Series qt69v8p1m9, Department of Economics, UC San Diego.
  32. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended Phillips Curve Models with non-filtered Data," Koç University-TUSIAD Economic Research Forum Working Papers 1321, Koc University-TUSIAD Economic Research Forum.
  33. Fabio Canova & Matteo Ciccarelli, 2000. "Forecasting And Turning Point Predictions In A Bayesian Panel Var Model," Working Papers. Serie AD 2000-05, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  34. M. Ayhan Kose & Christopher Otrok & Charles H. Whiteman, 2003. "International Business Cycles: World, Region, and Country-Specific Factors," American Economic Review, American Economic Association, vol. 93(4), pages 1216-1239, September.
  35. Chauvet, Marcelle & Piger, Jeremy, 2008. "A Comparison of the Real-Time Performance of Business Cycle Dating Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 42-49, January.
  36. Sylvia Kaufmann, 2011. "K-state switching models with endogenous transition distributions," Working Papers 2011-13, Swiss National Bank.
  37. Don Harding, 2010. "Applying shape and phase restrictions in generalized dynamic categorical models of the business cycle," NCER Working Paper Series 58, National Centre for Econometric Research.
  38. Monica Billio & Laurent Ferrara & Dominique Guegan & Gian Luigi Mazzi, 2013. "Evaluation of Regime Switching Models for Real-Time Business Cycle Analysis of the Euro Area," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00965005, HAL.
  39. Monica Billio & Laurent Ferrara & Dominique Guegan & Gian Luigi Mazzi, 2009. "Evaluation of Nonlinear time-series models for real-time business cycle analysis of the Euro area," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00423890, HAL.
  40. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Combination schemes for turning point predictions," Working Papers 2012_15, Department of Economics, University of Venice "Ca' Foscari".
  41. Altissimo, Filippo & Bassanetti, Antonio & Cristadoro, Riccardo & Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia & Veronese, Giovanni, 2001. "EuroCOIN: A Real Time Coincident Indicator of the Euro Area Business Cycle," CEPR Discussion Papers 3108, C.E.P.R. Discussion Papers.
  42. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
  43. Peter Lenk & Wayne DeSarbo, 2000. "Bayesian inference for finite mixtures of generalized linear models with random effects," Psychometrika, Springer, vol. 65(1), pages 93-119, March.
  44. Filippo Altissimo & Antonio Bassanetti & Riccardo Cristadoro & Mario Forni & Marco Lippi & Lucrezia Reichlin & Giovanni Veronese, 2001. "A real time coincident indicator of the euro area business cycle," Temi di discussione (Economic working papers) 436, Bank of Italy, Economic Research and International Relations Area.
  45. Marco Terrones & M. Ayhan Kose & Stijn Claessens, 2008. "What Happens During Recessions, Crunches, and Busts?," IMF Working Papers 08/274, International Monetary Fund.
  46. Billio, M. & Monfort, A. & Robert, C. P., 1999. "Bayesian estimation of switching ARMA models," Journal of Econometrics, Elsevier, vol. 93(2), pages 229-255, December.
  47. Forni, Mario & Lippi, Marco, 2001. "The Generalized Dynamic Factor Model: Representation Theory," Econometric Theory, Cambridge University Press, vol. 17(06), pages 1113-1141, December.
  48. Marc Hallin & Roman Liska, 2008. "Dynamic Factors in the Presence of Block Structure," Economics Working Papers ECO2008/22, European University Institute.
  49. Samad Sarferaz & Francesco Furlanetto & Francesco Furlanetto, 2014. "Identification of Financial Factors in Economic Fluctuations," KOF Working papers 14-364, KOF Swiss Economic Institute, ETH Zurich.
  50. Chib, Siddhartha & Greenberg, Edward, 1995. "Hierarchical analysis of SUR models with extensions to correlated serial errors and time-varying parameter models," Journal of Econometrics, Elsevier, vol. 68(2), pages 339-360, August.
  51. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Extended New Keynesian Phillips Curve Models with Non-filtered Data," Tinbergen Institute Discussion Papers 13-090/III, Tinbergen Institute.
  52. Chang-Jin Kim & Charles R. Nelson, 1999. "Has The U.S. Economy Become More Stable? A Bayesian Approach Based On A Markov-Switching Model Of The Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 608-616, November.
  53. Monfort, Alain & Renne, Jean-Paul & Rüffer, Rasmus & Vitale, Giovanni, 2003. "Is Economic Activity in the G7 Synchronized? Common Shocks versus Spillover Effects," CEPR Discussion Papers 4119, C.E.P.R. Discussion Papers.
  54. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  55. Ferrara, Laurent, 2003. "A three-regime real-time indicator for the US economy," Economics Letters, Elsevier, vol. 81(3), pages 373-378, December.
  56. Nalan Basturk & Cem Cakmakli & Pinar Ceyhan & Herman K. van Dijk, 2013. "Posterior-Predictive Evidence on US Inflation using Phillips Curve Models with Non-Filtered Time Series," Tinbergen Institute Discussion Papers 13-011/III, Tinbergen Institute.
  57. Simon Gilchrist & Benoît Mojon, 2014. "Credit Risk in the Euro Area," NBER Working Papers 20041, National Bureau of Economic Research, Inc.
  58. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, October.
  59. Monica Billio & Roberto Casarin & Francesco Ravazzolo & Herman K. van Dijk, 2012. "Time-varying Combinations of Predictive Densities using Nonlinear Filtering," Tinbergen Institute Discussion Papers 12-118/III, Tinbergen Institute.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:bno:worpap:2013_20. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.