Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-24T13:04:02.179Z Has data issue: false hasContentIssue false
  • English
  • Français

THE PROPAGATION OF INDUSTRIAL BUSINESS CYCLES

Published online by Cambridge University Press:  21 September 2017

Maximo Camacho  and
Danilo Leiva-Leon
Maximo Camacho
Affiliation:
University of Murcia
Danilo Leiva-Leon*
Affiliation:
University of Murcia
*
Address correspondence to: Danilo Leiva-Leon, ADG Economics and Research, Banco de España, Alcalá 48, Madrid-Spain; e-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper examines the evolution of the distribution of industry-specific business cycle linkages, which are modeled through a multivariate Markov-switching model and estimated by Gibbs sampling. Using nonparametric density estimation approaches, we find that the number and location of modes in the distribution of industrial dissimilarities change over the business cycle. There is a relatively stable trimodal pattern during expansionary and recessionary phases characterized by highly, moderately, and lowly synchronized industries. However, during phase changes, the density mass spreads from moderately synchronized industries to lowly synchronized industries. This agrees with a sequential transmission of the industrial business cycle dynamics.

Keywords

Business CyclesOutput GrowthTime Series
Type
Articles
Information
Macroeconomic Dynamics , Volume 23 , Issue 1 , January 2019 , pp. 144 - 177
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

We are thankful to Gabriel Perez Quiros, the editor, and two anonymous referees for their comments. M. Camacho acknowledges the financial support from projects ECO2013-45698-P and ECO2016-76178-P, whose contribution also is the result of the activity carried out under the program Groups of Excellence of the region of Murcia, the Fundacion Seneca, Science and Technology Agency of the region of Murcia project 19884/GERM/15. All remaining errors are our responsibility. The views expressed in this paper are those of the authors and do not represent the views of the Banco de España or the Eurosystem.

References

REFERENCES

Acemoglu, D., Carvalho, V., Ozdaglar, A. and Tahbaz-Salehi, A. (2012) The network origins of aggregate fluctuations. Econometrica 80, 1977–2016.Google Scholar
Barker, M. (2011) Manufacturing employment hard hit during the 2007-09 recession. Monthly Labor Review April(2011), 28–33.Google Scholar
Bengoechea, P., Camacho, M. and Quiros, G. Perez (2006) A useful tool for forecasting the Euro-area business cycle phases. International Journal of Forecasting 22, 735–749.Google Scholar
Berman, J. and Pfleeger, J. (1997) Which industries are sensitive to business cycles? Monthly Labor Review 120 (2), 19–25.Google Scholar
Bureau of Labor Statistics (2012) The recession of 2007-2009. BLS Spotlight on Statistics February (2012), 1–18.Google Scholar
Camacho, M. and Quiros, G. Perez (2006) A new framework to analyze business cycle synchronization. In Milas, C., Rothman, P. and van Dijk, D. (eds.), Nonlinear Time Series Analysis of Business Cycles, Chap. 5, pp. 133–149. Amsterdam: Elsevier.Google Scholar
Carlino, G. and DeFina, R. H. (2004) How strong is co-movement in employment over the business cycle? Evidence from state/industry data. Journal of Urban Economics 55, 298–315.Google Scholar
Carvalho, V. M. (2008) Aggregate Fluctuations and the Network Structure of Intersectoral Trade. Economics working papers 1206, Department of Economics and Business, Universitat Pompeu Fabra.Google Scholar
Christiano, L. and Fitzgerald, T. (1998) The business cycle: It's still a puzzle. Economic Perspectives, Federal Reserve Bank of Chicago Q IV, 56–83.Google Scholar
Clark, S. (1973) Labor hoarding in durable goods industries. American Economic Review 63, 811–824.Google Scholar
Conlon, F. (2011) Professional and business services: Employment trends in the 2007–09 recession. Monthly Labor Review April(2011), 34–39.Google Scholar
Dupor, B. (1999) Aggregation and irrelevance in multi-sector models. Journal of Monetary Economics 43, 391–409.Google Scholar
Filardo, A. (1997) Cyclical implications of the declining manufacturing employment share. Federal Reserve Bank of Kansas City Economic Review II 82, 63–87.Google Scholar
Foerster, A., Sarte, P. and Watson, M. (2011) Sectorial versus aggregate shocks: A structural factor analysis of industrial production. Journal of Political Economy 119, 1–38.Google Scholar
Forni, M. and Reichlin, L. (1998) Let's get real: A factor analytical approach to disaggregated business cycle dynamics. Review of Economic Studies 65, 453–473.Google Scholar
Gabaix, X. (2011) The granular origins of aggregate fluctuations. Econometrica 79, 733–772.Google Scholar
Goodman, W. (2001) Employment in services industries affected by recessions and expansions. Monthly Labor Review 124 (10), 3–11.Google Scholar
Goodman, W. and Mance, S. (2011) Employment loss and the 2007–09 recession: An overview. Monthly Labor Review April(2011), 3–12.Google Scholar
Groshen, E. and Potter, S. (2003) Has structural change contributed to a jobless recovery? Current Issues in Economics and Finance, Federal Reserve Bank of New York 9 (8), 1–7.Google Scholar
Hamilton, J. (1989) A new approach to the economic analysis of nonstationary time series and the business cycles. Econometrica 57, 357–384.Google Scholar
Hamilton, J. and Owyang, M. (2012) The propagation of regional recessions. Review of Economics and Statistics 94, 935–947.Google Scholar
Horvath, M. (1998) Cyclicality and sectoral linkages: Aggregate fluctuations from sectoral shocks. Review of Economic Dynamics 1, 781–808.Google Scholar
Horvath, M. (2000) Sectoral shocks and aggregate fluctuations. Journal of Monetary Economics 45, 69–106.Google Scholar
Karadimitropoulou, A. and Leon-Ledesma, M. (2013) World, country, and sector factors in international business cycles. Journal of Economic Dynamics and Control 37 (12), 2913–2927.Google Scholar
Leiva-Leon, D. (2017) Measuring business cycles intra-synchronization in US: A regimeswitching interdependence framework. Oxford Bulletin of Economics and Statistics, 79 (4), 513–545.Google Scholar
Long, J. B. and Plosser, C. I. (1983) Real business cycles. Journal of Political Economy 91, 39–69.Google Scholar
Long, J. B. and Plosser, C. I. (1987) Sectoral vs. aggregate shocks in the business cycle. American Economic Review 77, 333–336.Google Scholar
Malmendier, U. and Nagel, S. (2011) Depression babies: Do macroeconomic experiences affect risk taking? Quarterly Journal of Economics 126, 373–416.Google Scholar
Owyang, M., Piger, J. and Wall, H. (2005) Business cycle phases in the U.S. states. Review of Economics and Statistics 87, 604–616.Google Scholar
Owyang, M., Piger, J., Wall, H. and Wheeler, C. (2008) The economic performance of cities: A Markov-switching approach. Journal of Urban Economics 64, 538–550.Google Scholar
Parsons, O. (1986) The employment relationship: Job attachment, work effort and the nature of contracts. In Ashenfelter, O. and Layard, R. (eds.), Handbook of Labor Economics, vol. 2, pp. 789–848. Amsterdam: North-Holland.Google Scholar
Peterson, B. and Strongin, S. (1996) Why are some industries more cyclical than others? Journal of Business and Economic Statistics 14 (2), 189–198.Google Scholar
Phillips, K. (1991) A two-country model of stochastic output with changes in regime. Journal of International Economics 31, 121–142.Google Scholar
Rotemberg, J. and Summers, L. (1990) Inflexible prices and procyclical productivity. Quarterly Journal of Economics 105, 851–874.Google Scholar
Shea, J. (2002) Complementarities and comovements. Journal of Money, Credit and Banking 34, 412–433.Google Scholar
Silverman, B. (1981) Using kernel density estimates to investigate multimodality. Journal of the Royal Statistical Society, Series B 43, 97–99.Google Scholar
Tim, N. H. (2002) Applied Multivariate Analysis, Springer Texts in Statistics. New York: Springer.Google Scholar
Urquhart, M. (1981) The services industry: Is it recession-proof? Monthly Labor Review 104 (10), 12–18.Google Scholar