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How do Canadian hours worked respond to a technology shock?

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Author Info

  • Lawrence J Christiano
  • Martin Eichenbaum
  • Robert Vigfusson

Abstract

This paper investigates the response of hours worked to a permanent technology shock. Based on annual data from Canada, we argue that hours worked rise after a positive technology shock. We obtain a similar result using annual data from the United States. These results contradict a large literature that claims that a positive technology shock causes hours worked to fall. We find that the different results are due to the literature making a specification error in the statistical model of per capital hours worked. Finally, we present results that Canadian monetary policy has accommodated technology shocks.

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File URL: http://www.federalreserve.gov/pubs/ifdp/2003/774/default.htm
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File URL: http://www.federalreserve.gov/pubs/ifdp/2003/774/ifdp774.pdf
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Bibliographic Info

Paper provided by Board of Governors of the Federal Reserve System (U.S.) in its series International Finance Discussion Papers with number 774.

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Date of creation: 2003
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Handle: RePEc:fip:fedgif:774

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Related research

Keywords: Productivity ; Technology;

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  1. Graham Elliott & Michael Jansson, . "Testing for Unit Roots with Stationary Covariates," Economics Working Papers 2000-6, School of Economics and Management, University of Aarhus.
  2. Jordi Gali & J. David Lopez-Salido & Javier Valles, 2002. "Technology Shocks and Monetary Policy: Assessing the Fed's Performance," NBER Working Papers 8768, National Bureau of Economic Research, Inc.
  3. Martin Eichenbaum & Kenneth I. Singleton, 1986. "Do Equilibrium Real Business Cycle Theories Explain Postwar U.S. Business Cycles?," NBER Chapters, in: NBER Macroeconomics Annual 1986, Volume 1, pages 91-146 National Bureau of Economic Research, Inc.
  4. Sims, Christopher A & Stock, James H & Watson, Mark W, 1990. "Inference in Linear Time Series Models with Some Unit Roots," Econometrica, Econometric Society, vol. 58(1), pages 113-44, January.
  5. 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.
  6. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
  7. Galí, Jordi, 1996. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," CEPR Discussion Papers 1499, C.E.P.R. Discussion Papers.
  8. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  9. Hansen, Bruce E., 1995. "Rethinking the Univariate Approach to Unit Root Testing: Using Covariates to Increase Power," Econometric Theory, Cambridge University Press, vol. 11(05), pages 1148-1171, October.
  10. Kwiatkowski, D. & Phillips, P.C.B. & Schmidt, P., 1990. "Testing the Null Hypothesis of Stationarity Against the Alternative of Unit Root : How Sure are we that Economic Time Series have a Unit Root?," Papers 8905, Michigan State - Econometrics and Economic Theory.
  11. Jonas Fisher, 2004. "Technology Shocks Matter," Econometric Society 2004 North American Winter Meetings 14, Econometric Society.
  12. Neville Francis & Valerie A. Ramey, 2002. "Is the Technology-Driven Real Business Cycle Hypothesis Dead?," NBER Working Papers 8726, National Bureau of Economic Research, Inc.
  13. Lawrence J. Christiano & Lars Ljungqvist, 1987. "Money does Granger-cause output in the bivariate output-money relation," Staff Report 108, Federal Reserve Bank of Minneapolis.
  14. repec:cup:etheor:v:11:y:1995:i:5:p:1148-71 is not listed on IDEAS
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