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Technology shocks, structural breaks and the effects on the business cycle

  • Vincenzo Atella

    (CEIS & Dipartimento SEFEMEQ - Università di Roma "Tor Vergata")

  • Marco Centoni

    (Dipartimento SEGES - Università del Molise)

  • Gianluca Cubadda

    (Dipartimento SEFEMEQ - Università di Roma "Tor Vergata")

This paper contributes to the literature on the role of technology shocks as source of the business cycle in two ways. First, we document that time-series of US productivity and hours are apparently affected by a structural break in the late 60’s, which is likely due to a major change in the monetary policy. Second, we show that the importance of demand shocks over the business cycle has sharply increased after the break.

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Paper provided by Tor Vergata University, CEIS in its series CEIS Research Paper with number 105.

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Date of creation: 17 Oct 2007
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Handle: RePEc:rtv:ceisrp:105
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  1. Clarida, Richard & Galí, Jordi & Gertler, Mark, 1998. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," CEPR Discussion Papers 1908, C.E.P.R. Discussion Papers.
  2. Christina D. Romer and David H. Romer., 1989. "Does Monetary Policy Matter? A New Test in the Spirit of Friedman and Schwartz," Economics Working Papers 89-107, University of California at Berkeley.
  3. Luca Gambetti & Jordi Galí, 2009. "On the Sources of the Great Moderation," American Economic Journal: Macroeconomics, American Economic Association, vol. 1(1), pages 26-57, January.
  4. Atella, Vincenzo & Centoni, Marco & Cubadda, Gianluca, 2007. "Technology shocks, structural breaks and the effects on the business cycle," Economics & Statistics Discussion Papers esdp07041, University of Molise, Dept. EGSeI.
  5. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
  6. Candelon, Bertrand & Lütkepohl, Helmut, 2000. "On the reliability of chow type test for parameter constancy in multivariate dynamic models," SFB 373 Discussion Papers 2000,95, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  7. John Duffy and Jim Engle-Warnick, 2001. "Multiple Regimes in U.S. Monetary Policy? A Nonparametric Approach," Computing in Economics and Finance 2001 151, Society for Computational Economics.
  8. Jordi Galí & David López-Salido & Javier Vallés, 2000. "Technology Shocks and Monetary policy: Assessing the Fed's Performance," Working Papers 0013, Banco de España;Working Papers Homepage.
  9. Candelon Bertrand & Cubadda Gianluca, 2005. "Testing for Parameter Stability in Dynamic Models across Frequencies," Research Memorandum 022, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  10. Perron, P. & Bai, J., 1995. "Estimating and Testing Linear Models with Multiple Structural Changes," Cahiers de recherche 9552, Universite de Montreal, Departement de sciences economiques.
  11. Centoni, Marco & Cubadda, Gianluca, 2003. "Measuring the business cycle effects of permanent and transitory shocks in cointegrated time series," Economics Letters, Elsevier, vol. 80(1), pages 45-51, July.
  12. Jushan Bai & Robin L. Lumsdaine & James H. Stock, 1998. "Testing For and Dating Common Breaks in Multivariate Time Series," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 395-432.
  13. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
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