Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-11-26T02:13:15.877Z Has data issue: false hasContentIssue false
  • English
  • Français

THE REGIME-SWITCHING VOLATILITY OF EURO AREA BUSINESS CYCLES

Published online by Cambridge University Press:  22 June 2017

Stéphane Lhuissier
Stéphane Lhuissier*
Affiliation:
CEPII
*
Address correspondence to: Stéphane Lhuissier, CEPII, 113, Rue de Grenelle, 75007 Paris Cedex, France; e-mail: [email protected]; URL: www.stephanelhuissier.eu.
Get access Rights & Permissions [Opens in a new window]

Abstract

We document the strong evidence of time variation in the volatility of Euro Area business cycles since 1970. Then we provide the quantitative sources of these changes using a medium-scale DSGE model allowing time variation in structural disturbance variances. We show that (1) the size of different types of shock oscillates, in a synchronized manner, between two regimes over time, with the high-volatility regime prevailing predominantly in the 1970s, sporadically in the 1980s and 1990s, and during the Great Recession; (2) their relative importance remains, however, unchanged across regimes, where neutral technology shocks and marginal efficiency of investment shocks are the dominant sources of business cycle fluctuations; and 3) these investment shocks, which affect the transformation of savings into productive capital, can be interpreted as an indicator of credit conditions.

Keywords

Business CyclesDSGEEuro AreaHeteroskedasticityMarkov Switching
Type
Articles
Information
Macroeconomic Dynamics , Volume 22 , Issue 2 , March 2018 , pp. 426 - 469
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

I am deeply indebted to Michel Juillard and Tao Zha for their guidance and advice. I also thank two anonymous referees, Jean-Guillaume Sahuc and participants at several seminars for their helpful comments. This paper is a revised version of the second chapter of my Ph.D. thesis. It previously circulated as “Heteroskedastic Shocks and the Great Moderation in the Euro Area.”

References

REFERENCES

Altig, D., Christiano, L., Eichenbaum, M., and Linde, J. (2011) Firm-specific capital, nominal rigidities, and the business cycle. Review of Economic Dynamics 14 (2), 225–247.CrossRefGoogle Scholar
An, S. and Schorfheide, F. (2007) Bayesian analysis of DSGE models. Econometric Review 26 (2–4), 113–172.CrossRefGoogle Scholar
Angeloni, I., Kashyap, A., and Mojon, B. (2003) Monetary Policy Transmission in the Euro Area: A Study by the Eurosystem Monetary Transmission Network. Angeloni, Ignazio, Kashyap, Anil K., and Mojon, Benoît (eds.). Cambridge: Cambridge University Press.Google Scholar
Avouyi-Dovi, S. and Sahuc, J.-G. (2016) On the sources of macroeconomic stability in the Euro area. European Economic Review 83, 40–63.CrossRefGoogle Scholar
Bernanke, B.S. and Mihov, I. (1998) Measuring monetary policy. Quarterly Journal of Economics 113 (3), 869–902.CrossRefGoogle Scholar
Bianchi, F. (2013) Regimes switches, agents' beliefs, and Post-World War II U.S. macroeconomic dynamics. Review of Economic Studies 80 (2), 463–490.CrossRefGoogle Scholar
Bianchi, F. and Ilut, C. (forthcoming) Monetary/Fiscal policy mix and agents' beliefs. Review of Economic Dynamics.Google Scholar
Calvo, G.A. (1983) Staggered prices in a utility-maximizing framework. Journal of Monetary Economics 12 (3), 383–398.CrossRefGoogle Scholar
Canova, F., Gambetti, L., and Pappa, E. (2008) The structural dynamics of output growth and inflation: Some international evidence. Economic Journal 117, C167–C191.CrossRefGoogle Scholar
Canova, F., Lopez-Salido, D., and Michelacci, C. (2006) On the Robust Effects of Technology on Hours Worked and Output. Mimeo, Universitat Pompeu Fabra.CrossRefGoogle Scholar
Carlstrom, C.T. and Fuerst, T.S. (1997) Agency costs, net worth, and business fluctuations: A computable general equilibrium analys. American Economic Review 87 (5), 893–910.Google Scholar
Cecioni, M. and Neri, S. (2011) The Monetary Transmission Mechanism in the Euro Area: Has It Changed and Why?' Working paper, Banca d'Italia.CrossRefGoogle Scholar
Chang, Y. and Hong, J.H. (2006) Do technological improvements in the manufacturing sector raise or lower employment? American Economic Review 96 (1), 352–368.CrossRefGoogle Scholar
Christiano, L.J., Eichenbaum, M., and Evans, C.L. (2005) Nominal rigidities and the dynamic effects of a shock to monetary policy. Journal of Political Economy 113 (1), 1–45.Google Scholar
Christiano, L., Eichenbaum, M., and Vigfusson, R. (2004) What Happens After a Technology Shock? Mimeo, Northwestern University.CrossRefGoogle Scholar
Clarida, R., Gali, J., and Gertler, M. (1998) Monetary policy rules in practice: Some international evidence. European Economic Review 42, 1033–1067.CrossRefGoogle Scholar
Clarida, R., Gali, J., and Gertler, M. (2000) Monetary policy rules and macroeconomic stability: Evidence and some theory. Quarterly Journal of Economics (2), 147–180.CrossRefGoogle Scholar
Cogley, T. and Sargent, T.J. (2005) Drift and volatilities: Monetary policies and outcomes in the Post-WWII U.S. Review of Economic Dynamics 8, 262–302.CrossRefGoogle Scholar
Davig, T. and Doh, T. (2014) Monetary policy regime shifts and inflation persistence. Review of Economics and Statistics 96 (5), 862–875.Google Scholar
Erceg, C.J., Henderson, D.W., and Levin, A.T. (2000) Optimal monetary policy with staggered wage and price contracts. Journal of Monetary Economics 46 (2), 281–313.CrossRefGoogle Scholar
Fagan, G., Henry, J., and Mestre, R. (2005) An area-wide model for the Euro Area. Economic Modelling 22, 39–59.Google Scholar
Fisher, J.D.M. (2006) The dynamic effects of neutral and investment-specific technology shocks. Journal of Political Economy 114 (3), 413–451.Google Scholar
Francis, N. and Ramey, V.A. (2009) Measures of hours per capita and their implications for the technology-hours debate. Journal of Money, Credit, and Banking 41 (6), 1071–1097.CrossRefGoogle Scholar
Fruhwirth-Schnatter, S. (2004) Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques. Econometrics Journal 7 (1), 143–167.Google Scholar
Gali, J. (1999) Technology, employment, and the business cycle: Do technology shocks explain aggregate fluctuations? American Economic Review 89 (1), 249–271.CrossRefGoogle Scholar
Gertler, M. and Kiyotaki, N. (2010) Financial intermediation and credit policy in business cycle analysis. Handbook of Monetary Economics 3, 547–599.Google Scholar
Geweke, J. (1999) Using simulation methods for Bayesian econometric models: Inference, development, and communication. Econometric Review 18 (1), 1–73.Google Scholar
Gilchrist, S. and Mojon, B. (forthcoming) Credit risk in the Euro area. The Economic Journal.Google Scholar
Hamilton, J.D. (1989) A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57, 357–384.Google Scholar
Hamilton, J.D., Waggoner, D.F., and Zha, T. (2007) Normalization in econometrics. Econometric Reviews 26, 221–252.CrossRefGoogle Scholar
Justiniano, A. and Primiceri, G.E. (2008) The time-varying volatility of macroeconomic fluctuations. American Economic Review 98 (3), 601–641.Google Scholar
Justiniano, A., Primiceri, G.E., and Tambalotti, A. (2011) Investment shocks and the relative price of Investment. Review of Economic Dynamics 14 (1), 101–121.Google Scholar
Kim, C.-J. (1994) Dynamic linear models with Markov-switching. Journal of Econometrics 60, 1–22.Google Scholar
Kim, C.-J. and Nelson, C.R. (1999) State-space Models with Regime Switching. Cambridge, MA: MIT Press.Google Scholar
Lhuissier, S. and Zabelina, M. (2015) On the stability of Calvo-style price-setting behavior. Journal of Economic Dynamics and Control 57, 77–95.Google Scholar
Liu, Z., Waggoner, D.F., and Zha, T. (2011) Sources of macroeconomic fluctuations: A regime-switching DSGE Approach. Quantitative Economics 2 (2), 251–301.CrossRefGoogle Scholar
Lubik, T. and Schorfheide, F. (2004) Testing for indeterminacy: An application to U.S. monetary policy. American Economic Review 94 (1), 190–219.Google Scholar
Meng, X. and Wong, W.H. (1996) Simulating ratios of normalizing constants via a simple identity: A theoretical exploration. Statistica Sinica (6), 831–860.Google Scholar
Ohanian, L.E. and Raffo, A. (2012) Aggregate hours worked in OECD countries: New measurement and implications for business cycles. Journal of Monetary Economics 59 (1), 40–56.CrossRefGoogle Scholar
Peersman, G. and Smets, F. (2001) The Monetary Transmission Mechanism in the Euro Area: More Evidence from VAR Analysis. Working paper.Google Scholar
Primiceri, G.E. (2005) Time-varying structural vector autoregressions and monetary policy. Review of Economic Studies 72, 821–852.CrossRefGoogle Scholar
Sahuc, J.-G. and Smets, F. (2008) Differences in interest rate policy at the ECB and the Fed: An investigation with a medium-scale DSGE model. Journal of Money, Credit, and Banking 40 (2–3), 505–521.CrossRefGoogle Scholar
Sims, C.A., Waggoner, D.F., and Zha, T. (2008) Methods for inference in large multiple-equation Markov-switching models. Journal of Econometrics 146, 255–274.CrossRefGoogle Scholar
Sims, C.A. and Zha, T. (2006) Were there regime switches in U.S. monetary policy? American Economic Review 96 (1), 54–81.CrossRefGoogle Scholar
Smets, F.R. and Wouters, R. (2007) Shocks and frictions in U.S. business cycles: A Bayesian DSGE approach. American Economic Review 97 (3), 586–606.Google Scholar
Uhlig, H. (2004) Do technology shocks lead to a fall in total hours worked. Journal of the European Economic Association 2 (2–3), 361–371.CrossRefGoogle Scholar