Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-13T10:18:58.852Z Has data issue: false hasContentIssue false
  • English
  • Français

TECHNOLOGY SHOCKS AND HOURS WORKED: A CROSS-COUNTRY ANALYSIS

Published online by Cambridge University Press:  27 August 2019

Jacqueline Thomet  and
Philipp Wegmueller
Jacqueline Thomet
Affiliation:
University of Bern
Philipp Wegmueller*
Affiliation:
Swiss State Secretariat for Economic Affairs
*
Address correspondence to: Philipp Wegmueller, Swiss State Secretariat for Economic Affairs (SECO), Bern, Switzerland. e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

We reassess the evidence for (or against) a key implication of the basic real business cycle model: that aggregate hours worked increase in response to a positive technology shock. Two novel aspects are the scope (14 OECD countries) and the inclusion of data on both labor supply margins to analyze the key margin of adjustment in aggregate hours. The short-run response of aggregate hours to a positive technology shock is remarkably similar across countries, with an impact fall in 13 out of 14 countries. In contrast, its decomposition into intensive and extensive labor supply margins reveals substantial heterogeneity in labor market dynamics across OECD countries. For instance, movements in the intensive margin are the dominant channel of adjustment in aggregate hours in 6 out of 14 countries of our sample, including France and Japan.

Keywords

Structural VARTechnology ShocksAggregate Hours WorkedLabor Supply MarginsRelative Price of Investment
Type
Articles
Information
Macroeconomic Dynamics , Volume 25 , Issue 4 , June 2021 , pp. 1020 - 1052
Copyright
© Cambridge University Press 2019

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 wish to thank Luca Benati and Fabrice Collard for guidance, and Andrea Raffo and Lee Ohanian for making the data available to us. We also thank the editor of the journal, two anonymous referees, Mario Forni, Jordi Galí, Christian Myohl, and participants of the Macro Workshop at the University of Bern and of the 2017 Spring Meeting of Young Economists for valuable comments. The views, opinions, findings, and conclusions or recommendations expressed in this paper are strictly those of the authors. They do not necessarily reflect the views of the State Secretariat for Economic Affairs (SECO). SECO does not take responsibility for any errors or omissions in, or for the correctness of, the information contained in this paper.

References

REFERENCES

Abbritti, M., Weber, S., et al. (2018) Reassessing the role of labor market institutions for the business cycle, International Journal of Central Banking 14(1), 1–34.Google Scholar
Andolfatto, D. (1996) Business cycles and labor-market search, The American Economic Review 86(1), 112–132.Google Scholar
Basu, S., Fernald, J. G., and Kimball, M. S. (2006) Are technology improvements contractionary?, The American Economic Review 96(5), 1418–1448.CrossRefGoogle Scholar
Beaudry, P., Moura, A., and Portier, F. (2015) Reexamining the cyclical behavior of the relative price of investment, Economics Letters 135, 108–111.CrossRefGoogle Scholar
Bernanke, B., and Blinder, A. (1992) The Federal Funds Rate and the channels of monetary transmission, The American Economic Review 82(4), 901–921.Google Scholar
Blanchard, O. J., and Quah, D. (1989) The Dynamic Effects of Aggregate Demand and Supply Disturbances, The American Economic Review 79(4), 655–673.Google Scholar
Caldara, D., Fuentes-Albero, C., Gilchrist, S., and Zakrajšek, E. (2016) The macroeconomic impact of financial and uncertainty shocks, European Economic Review 88, 185–207.CrossRefGoogle Scholar
Canova, F., Lopez-Salido, D., and Michelacci, C. (2010) The effects of technology shocks on hours and output: A robustness analysis, Journal of Applied Econometrics 25(5), 755–773.CrossRefGoogle Scholar
Chaudourne, J., Fève, P., and Guay, A. (2014) Understanding the effect of technology shocks in SVARs with long-run restrictions, Journal of Economic Dynamics and Control 41, 154–172.CrossRefGoogle Scholar
Christiano, L. J., Eichenbaum, M., and Vigfusson, R. (2003) What happens after a technology shock? NBER Working Papers.CrossRefGoogle Scholar
Christiano, L. J., Eichenbaum, M., and Vigfusson, R. (2004) The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology, Journal of the European Economic Association 2(2–3), 381–395.CrossRefGoogle Scholar
Cummins, J. G., and Violante, G. L. (2002) Investment-specific technical change in the United States (1947–2000) Measurement and macroeconomic consequences, Review of Economic Dynamics 5(2), 243–284.CrossRefGoogle Scholar
Dupaigne, M., and Fève, P. (2009) Technology shocks around the world, Review of Economic Dynamics 12(4), 592–607.CrossRefGoogle Scholar
Erceg, C. J., Guerrieri, L., and Gust, C. (2005) Can Long-Run Restrictions Identify Technology Shocks?, Journal of the European Economic Association 3(6), 1237–1278.CrossRefGoogle Scholar
Faust, J., and Leeper, E. M. (1997) When Do Long-Run Identifying Restrictions Give Reliable Results?, Journal of Business & Economic Statistics 15(3), 345–353.Google Scholar
Fernald, J. G. (2007) Trend breaks, long-run restrictions, and contractionary technology improvements, Journal of Monetary Economics 54(8), 2467–2485.CrossRefGoogle Scholar
Fisher, J. D. (1999) The New View of Growth and Business Cycles, Economic Perspectives 23(1), 35.Google Scholar
Fisher, J. D. (2006) The dynamic effects of neutral and investment-specific technology shocks, Journal of Political Economy 114(3), 413–451.CrossRefGoogle Scholar
Francis, N., Owyang, M. T., Roush, J. E., and DiCecio, R. (2014) A flexible finite-horizon alternative to long-run restrictions with an application to technology shocks, Review of Economics and Statistics 96(4), 638–647.CrossRefGoogle Scholar
Francis, N., and Ramey, V. A. (2005) Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited, Journal of Monetary Economics 52(8), 1379–1399.CrossRefGoogle Scholar
Francis, N., and Ramey, V. A. (2006) The source of historical economic fluctuations: An analysis using long-run restrictions. In: NBER International Seminar on Macroeconomics 2004, NBER Chapters, pp. 17–73. Chicago: National Bureau of Economic Research.Google Scholar
Francis, N., and Ramey, V. A. (2009) A Century of Work and Leisure, American Economic Journal. Macroeconomics 1(2), 189.Google Scholar
Galí, J. (1999) Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?, The American Economic Review 89(1), 249–271.CrossRefGoogle Scholar
Galí, J. (2004) On the role of technology shocks as a source of business cycles: some new evidence, Journal of the European Economic Association 2(2–3), 372–380.CrossRefGoogle Scholar
Galí, J., López-Salido, J. D., and Vallés, J. (2003) Technology shocks and monetary policy: assessing the Fed’s performance, Journal of Monetary Economics 50(4), 723–743.CrossRefGoogle Scholar
Galí, J., and Rabanal, P. (2005) Technology shocks and aggregate fluctuations: How well does the real business cycle model fit postwar US data? In: NBER Macroeconomics Annual 2004, Volume 19, pp. 225–318. Chicago: MIT Press.Google Scholar
Gordon, R. J. (1990) The Measurement of Durable Goods Prices, Chicago: University of Chicago Press.CrossRefGoogle Scholar
Greenwood, J., Hercowitz, Z., and Huffman, G. W. (1988) Investment, capacity utilization, and the real business cycle, The American Economic Review 78(3), 402–417.Google Scholar
Greenwood, J., Hercowitz, Z., and Krusell, P. (1997) Long-run implications of investment-specific technological change, American Economic Review 87(3), 342–62.Google Scholar
Greenwood, J., Hercowitz, Z., and Krusell, P. (2000) The role of investment-specific technological change in the business cycle, European Economic Review 44(1), 91–115.CrossRefGoogle Scholar
Hansen, G. D. (1985) Indivisible labor and the business cycle, Journal of Monetary Economics 16(3), 309–327.CrossRefGoogle Scholar
Hantzsche, A., Savsek, S., and Weber, S. (2018) Labour market adjustments to financing conditions under sectoral rigidities in the euro area, Open Economies Review, 1–26.CrossRefGoogle Scholar
Ireland, P. N. (2000) Interest rates, inflation, and Federal Reserve policy since 1980, Journal of Money, Credit and Banking 32(3), 417–34.CrossRefGoogle Scholar
Justiniano, A., Primiceri, G., and Tambalotti, A. (2011) Investment Shocks and the Relative Price of Investment, Review of Economic Dynamics 14(1), 101–121.CrossRefGoogle Scholar
Kydland, F. E., and Prescott, E. (1982) Time to Build and Aggregate Fluctuations, Econometrica 50(6), 1345–1370.CrossRefGoogle Scholar
Long, John B. J., and Plosser, C. I. (1983) Real Business Cycles, Journal of Political Economy 91(1), 39–69.CrossRefGoogle Scholar
Lütkepohl, H. (2005) New Introduction to Multiple Time Series Analysis, Berlin: Springer Science & Business Media.CrossRefGoogle Scholar
Merz, M. (1995) Search in the labor market and the real business cycle, Journal of Monetary Economics 36(2), 269–300.CrossRefGoogle Scholar
Mortensen, D. T., and Pissarides, C. A. (1994) Job creation and job destruction in the theory of unemployment, The Review of Economic Studies 61(3), 397–415.CrossRefGoogle Scholar
Ohanian, L., Raffo, A., and Rogerson, R. (2008) Long-term changes in labor supply and taxes: Evidence from OECD countries, 1956–2004, Journal of Monetary Economics 55(8), 1353–1362.CrossRefGoogle 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
Schmitt-Grohé, S., and Uribe, M. (2011) Business Cycles With A Common Trend in Neutral and Investment-Specific Productivity, Review of Economic Dynamics 14(1), 122–135.CrossRefGoogle Scholar
Sims, C. A. (1992) Interpreting the macroeconomic time series facts: The effects of monetary policy, European Economic Review 36(5), 975–1000.CrossRefGoogle Scholar
Smets, F., and Wouters, R. (2007) Shocks and frictions in US business cycles: A Bayesian DSGE approach, The American Economic Review 97(3), 586–606.CrossRefGoogle Scholar
Taylor, J. B. (1993) Discretion versus policy rules in practice. In: Carnegie-Rochester Conference Series on Public Policy, volume 39, pp. 195–214. Rochester: Elsevier.Google Scholar
Uhlig, H. (2003) What drives GNP?, Unpublished manuscript, Euro Area Business Cycle Network.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
Watanabe, S. (2012) The Role of Technology and Nontechnology Shocks in Business Cycles, International Economic Review 53(4), 1287–1321.CrossRefGoogle Scholar
Whelan, K. T. (2009) Technology shocks and hours worked: Checking for robust conclusions, Journal of Macroeconomics 31(2), 231–239.CrossRefGoogle Scholar