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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.

Suggested Citation

  • Vincenzo Atella & Marco Centoni & Gianluca Cubadda, 2007. "Technology shocks, structural breaks and the effects on the business cycle," CEIS Research Paper 105, Tor Vergata University, CEIS.
  • Handle: RePEc:rtv:ceisrp:105

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    References listed on IDEAS

    1. Gali, Jordi & Lopez-Salido, J. David & Valles, Javier, 2003. "Technology shocks and monetary policy: assessing the Fed's performance," Journal of Monetary Economics, Elsevier, vol. 50(4), pages 723-743, May.
    2. Candelon, Bertrand & Lutkepohl, Helmut, 2001. "On the reliability of Chow-type tests for parameter constancy in multivariate dynamic models," Economics Letters, Elsevier, vol. 73(2), pages 155-160, November.
    3. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
    4. 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.
    5. 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.
    6. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    7. Christina D. Romer & David H. Romer, 1989. "Does Monetary Policy Matter? A New Test in the Spirit of Friedman and Schwartz," NBER Chapters,in: NBER Macroeconomics Annual 1989, Volume 4, pages 121-184 National Bureau of Economic Research, Inc.
    8. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    9. Bertrand Candelon & Gianluca Cubadda, 2006. "Testing for Parameter Stability in Dynamic Models across Frequencies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 741-760, December.
    10. Atella, Vincenzo & Centoni, Marco & Cubadda, Gianluca, 2008. "Technology shocks, structural breaks and the effects on the business cycle," Economics Letters, Elsevier, vol. 100(3), pages 392-395, September.
    11. Duffy, John & Engle-Warnick, Jim, 2006. "Multiple Regimes in U.S. Monetary Policy? A Nonparametric Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(5), pages 1363-1377, August.
    12. 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.
    13. 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.
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    Cited by:

    1. Atella, Vincenzo & Centoni, Marco & Cubadda, Gianluca, 2008. "Technology shocks, structural breaks and the effects on the business cycle," Economics Letters, Elsevier, vol. 100(3), pages 392-395, September.
    2. Cubadda, Gianluca & Triacca, Umberto, 2011. "An alternative solution to the Autoregressivity Paradox in time series analysis," Economic Modelling, Elsevier, vol. 28(3), pages 1451-1454, May.

    More about this item


    Business cycle; technology shocks; structural breaks;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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