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The Response of Hours to a Technology Shock: A Two-Step Structural VAR Approach

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  • PATRICK FÈVE
  • ALAIN GUAY

Abstract

The response of hours to a technology shock is a controversial issue in macroeconomics. Part of the difficulty lies in that the estimated response is sensitive to the specification of hours in structural vector autoregressions (SVARs). This paper uses a simple two-step approach to consistently estimate the response of hours. The first step considers a SVAR model with a relevant stationary variable, but excluding hours. Given a consistent estimate of technology shocks in the first step, the response of hours to this shock is estimated in a second step. Simulation experiments from an estimated dynamic stochastic general equilibrium (DSGE) model show that this approach outperforms standard SVARs. When applied to U.S. data, the two-step approach predicts a short-run decrease followed by a hump-shaped positive response. This result is robust to other specifications and data. Copyright (c) 2009 The Ohio State University No claim to original US government works.

Suggested Citation

  • Patrick Fève & Alain Guay, 2009. "The Response of Hours to a Technology Shock: A Two-Step Structural VAR Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(5), pages 987-1013, August.
    • Handle: RePEc:mcb:jmoncb:v:41:y:2009:i:5:p:987-1013
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    Cited by:

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    2. Fabrice Collard & Patrick Fève, 2012. "Sur les causes et les effets en macro économie : les Contributions de Sargent et Sims, Prix Nobel d'Economie 2011," Revue d'économie politique, Dalloz, vol. 122(3), pages 335-364.
    3. 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(1), pages 167-188, January.
    4. Andrei Polbin & Sergey Drobyshevsky, 2014. "Developing a Dynamic Stochastic Model of General Equilibrium for the Russian Economy," Research Paper Series, Gaidar Institute for Economic Policy, issue 166P, pages 156-156.
    5. Rujin, Svetlana, 2024. "Labor market institutions and technology-induced labor adjustment along the extensive and intensive margins," Journal of Macroeconomics, Elsevier, vol. 79(C).
    6. Rujin, Svetlana, 2019. "What are the effects of technology shocks on international labor markets?," Ruhr Economic Papers 806, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    7. Bolboaca Maria & Fischer Sarah, 2021. "Unraveling News: Reconciling Conflicting Evidence," The B.E. Journal of Macroeconomics, De Gruyter, vol. 21(2), pages 695-743, June.
    8. Marcos Sanso-Navarro, 2012. "Broken trend stationarity of hours worked," Applied Economics, Taylor & Francis Journals, vol. 44(30), pages 3955-3964, October.
    9. Francesco Furlanetto & Martin Seneca, 2012. "Rule‐of‐Thumb Consumers, Productivity, and Hours," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(2), pages 658-679, June.
    10. Christoph Gortz & Christopher Gunn & Thomas Lubik, 2022. "Split Personalities: The Changing Nature of Technology Shocks," Carleton Economic Papers 22-06, Carleton University, Department of Economics.
    11. Shiu‐Sheng Chen & Tzu‐Yu Lin, 2019. "Do Exchange Rate Shocks Have Asymmetric Effects on Reserve Accumulation? Evidence from Emerging Markets," Scandinavian Journal of Economics, Wiley Blackwell, vol. 121(4), pages 1561-1586, October.

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    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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