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Measures of Technology and the Business Cycle


  • Alexius, Annika

    (Department of Economics)

  • Carlsson, Mikael

    (Department of Economics)


Empirical evidence on the relationship between technology shocks and e.g. hours worked hinges crucially on the identification of the unobservable technological progress. In this paper, we study different measures of technology in order to find out (i) to what extent they capture the same underlying phenomenon and (ii) whether the implications for macroeconomic theory are robust across the approaches. Several versions of the productions function approach and structural VAR models are investigated. Our main finding is that the different technology measures are highly correlated. However, the exact formulation of the identifying restrictions seems to matter for the results. While we replicate the standard finding of a strongly procyclical Solow residual, all other measures of technology are either acyclical or countercyclical.

Suggested Citation

  • Alexius, Annika & Carlsson, Mikael, 2002. "Measures of Technology and the Business Cycle," Working Paper Series 2002:10, Uppsala University, Department of Economics, revised 02 Mar 2006.
  • Handle: RePEc:hhs:uunewp:2002_010 Note: Revised version of the second half of the paper.

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    References listed on IDEAS

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    Cited by:

    1. Lundborg, Per, 2005. "Wage Fairness, Growth and the Utilization of R&D Workers," Working Paper Series 206, Trade Union Institute for Economic Research.
    2. Mikael Carlsson & Jon Smedsaas, 2007. "Technology Shocks and the Labor-Input Response: Evidence from Firm-Level Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(6), pages 1509-1520, September.
    3. Holmlund, Bertil & Alexius, Annika, 2008. "Monetary Policy and Swedish Unemployment Fluctuations," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 2, pages 1-25.
    4. Morten O. Ravn & Saverio Simonelli, 2008. "Labor Market Dynamics and the Business Cycle: Structural Evidence for the United States," Scandinavian Journal of Economics, Wiley Blackwell, vol. 109(4), pages 743-777, March.
    5. Alexius, Annika & Post, Erik, 2006. "Cointegration and the stabilizing role of exchange rates," Working Paper Series 2006:8, Uppsala University, Department of Economics.
    6. Lundborg, Per, 2005. "Wage Theories for the Swedish Labour Market," Working Paper Series 207, Trade Union Institute for Economic Research.
    7. Annika Alexius & Erik Post, 2008. "Exchange rates and asymmetric shocks in small open economies," Empirical Economics, Springer, vol. 35(3), pages 527-541, November.
    8. Werner Hölzl & Serguei Kaniovski & Andreas Reinstaller, 2015. "The exposure of technology and knowledge intense sectors to the business cycle," Bulletin of Applied Economics, Risk Market Journals, vol. 2(1), pages 1-19.
    9. Selén, Jan & Ståhlberg, Ann-Charlotte, 2004. "Wage and Compensation Inequality — How Different?," Working Paper Series 197, Trade Union Institute for Economic Research.
    10. Takuji Fueki & Takuji Kawamoto, 2008. "Does Information Technology Raise Japan's Productivity?," Bank of Japan Working Paper Series 08-E-8, Bank of Japan.
    11. Alexius, Annika, 2005. "Productivity shocks and real exchange rates," Journal of Monetary Economics, Elsevier, vol. 52(3), pages 555-566, April.
    12. Fueki, Takuji & Kawamoto, Takuji, 2009. "Does information technology raise Japan's productivity?," Japan and the World Economy, Elsevier, vol. 21(4), pages 325-336, December.
    13. Ko, Jun-Hyung & Kwon, Hyeog Ug, 2015. "Do technology shocks lower hours worked? – Evidence from Japanese industry level data," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 138-157.
    14. Holzl, Werner & Reinstaller, Andreas, 2007. "The impact of productivity and demand shocks on structural dynamics: Evidence from Austrian manufacturing," Structural Change and Economic Dynamics, Elsevier, vol. 18(2), pages 145-166, June.
    15. Andrew Young & William Shughart, 2010. "The consequences of the US DOJ’s antitrust activities: A macroeconomic perspective," Public Choice, Springer, vol. 142(3), pages 409-422, March.

    More about this item


    Technology shocks; productions function approach; strcture VAR models;

    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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