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Technology shocks and hours worked: Checking for robust conclusions


  • Whelan, Karl T.


This paper presents some new results on the effects of technology shocks on hours worked based on structural VAR specifications containing various measures of US productivity growth and hours. These specifications can produce different answers depending on which sector of the economy is examined, which transformation of hours worked is used, and on how many lags are chosen for the VAR. However, it is shown that the results from the stochastic trend specification used by Galí [Galí, Jordi., 1999. Technology, employment and the business cycle: do technology shocks explain aggregate fluctuations. American Economic Review, 89, 249-271] are robust across changes in data definition and lag length, while the results from the per capita hours specification of Christiano, Eichenbaum, and Vigfusson [Christiano, Lawrence., Eichenbaum, M., Vigfusson, R., 2003. What happens after a technology shock? Federal Reserve Board, International Finance Discussion Paper, 2003, p. 768] are not. These results provide support for Galí's findings that technology shocks have a negative impact effect on hours worked and that these shocks play a limited role in generating the business cycle.

Suggested Citation

  • Whelan, Karl T., 2009. "Technology shocks and hours worked: Checking for robust conclusions," Journal of Macroeconomics, Elsevier, vol. 31(2), pages 231-239, June.
  • Handle: RePEc:eee:jmacro:v:31:y:2009:i:2:p:231-239

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    References listed on IDEAS

    1. Miles S. Kimball & John G. Fernald & Susanto Basu, 2006. "Are Technology Improvements Contractionary?," American Economic Review, American Economic Association, vol. 96(5), pages 1418-1448, December.
    2. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    3. 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.
    4. Neville Francis & Michael T. Owyang & Athena T. Theodorou, 2003. "The use of long-run restrictions for the identification of technology shocks," Review, Federal Reserve Bank of St. Louis, issue Nov, pages 53-66.
    5. Jordi Gali Garreta & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations; How Well Does the RBC Model Fit Postwar U.S. Data?," IMF Working Papers 04/234, International Monetary Fund.
    6. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    7. Fernald, John G., 2007. "Trend breaks, long-run restrictions, and contractionary technology improvements," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2467-2485, November.
    8. Matthew Shapiro & Mark Watson, 1988. "Sources of Business Cycles Fluctuations," NBER Chapters,in: NBER Macroeconomics Annual 1988, Volume 3, pages 111-156 National Bureau of Economic Research, Inc.
    9. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    10. Jordi Gali Garreta & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations; How Well Does the RBC Model Fit Postwar U.S. Data?," IMF Working Papers 04/234, International Monetary Fund.
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    Cited by:

    1. Cantore, C. & Ferroni, F. & León-Ledesma, M A., 2011. "Interpreting the Hours-Technology time-varying relationship," Working papers 351, Banque de France.
    2. Charles, Amélie & Darné, Olivier & Tripier, Fabien, 2015. "Are Unit Root Tests Useful In The Debate Over The (Non)Stationarity Of Hours Worked?," Macroeconomic Dynamics, Cambridge University Press, vol. 19(01), pages 167-188, January.
    3. Federico S. Mandelman & Francesco Zanetti, 2008. "Estimating general equilibrium models: an application with labour market frictions," Technical Books, Centre for Central Banking Studies, Bank of England, edition 1, number 1.
    4. Don J. Webber & Michael Horswell, 2009. "Microeconomic foundations of geographical variations in labour productivity," Working Papers 0913, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    5. Cristiano Cantore & Vasco J. Gabriel & Paul Levine & Joseph Pearlman & Bo Yang, 2013. "The science and art of DSGE modelling: I – construction and Bayesian estimation," Chapters,in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 18, pages 411-440 Edward Elgar Publishing.
    6. Jordi Galí, 2005. "Trends in hours, balanced growth, and the role of technology in the business cycle," Review, Federal Reserve Bank of St. Louis, issue Jul, pages 459-486.
    7. Federico S. Mandelman & Francesco Zanetti, 2008. "Technology shocks, employment, and labor market frictions," FRB Atlanta Working Paper 2008-10, Federal Reserve Bank of Atlanta.
    8. Rebei, Nooman, 2014. "What (really) accounts for the fall in hours after a technology shock?," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 330-352.
    9. Jordi Galí, 2004. "Trends in Hours, Balanced Growth, and the Role of Technology in the Business Cycle," Working Papers 187, Barcelona Graduate School of Economics.
    10. Alexiadis, Stilianos & Eleftheriou, Konstantinos & Nijkamp, Peter, 2013. "Technology adoption within a search model: Evidence from OECD countries," Economic Modelling, Elsevier, vol. 33(C), pages 137-148.
    11. Selgin, George & Beckworth, David & Bahadir, Berrak, 2015. "The productivity gap: Monetary policy, the subprime boom, and the post-2001 productivity surge," Journal of Policy Modeling, Elsevier, vol. 37(2), pages 189-207.

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models


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