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The use of long-run restrictions for the identification of technology shocks

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  • Neville Francis
  • Michael T. Owyang
  • Athena T. Theodorou

Abstract

The authors survey the recent empirical literature using long-run restrictions to identify technology shocks and provide an illustrative walk-through of the long-run restricted vector autoregression (VAR) methodology in a bivariate framework. Additionally, they offer an alternative identification of technology shocks that can be imposed by restrictions on the long-run impulse responses to evaluate the robustness of the conclusions drawn by the structural VAR literature. Their results from this methodology compare favorably with the empirical literature that uses structural VARs to identify technology shocks.

Suggested Citation

  • 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.
  • Handle: RePEc:fip:fedlrv:y:2003:i:nov:p:53-66:n:v.85no.6
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    References listed on IDEAS

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    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.
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    3. Uhlig, Harald, 2005. "What are the effects of monetary policy on output? Results from an agnostic identification procedure," Journal of Monetary Economics, Elsevier, vol. 52(2), pages 381-419, March.
    4. Andrew Mountford & Harald Uhlig, 2009. "What are the effects of fiscal policy shocks?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 960-992.
    5. Faust, Jon, 1998. "The robustness of identified VAR conclusions about money," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 49(1), pages 207-244, December.
    6. 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.
    7. 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.
    8. Evans, Charles L., 1992. "Productivity shocks and real business cycles," Journal of Monetary Economics, Elsevier, vol. 29(2), pages 191-208, April.
    9. King, Robert G. & Plosser, Charles I. & Stock, James H. & Watson, Mark W., 1991. "Stochastic Trends and Economic Fluctuations," American Economic Review, American Economic Association, vol. 81(4), pages 819-840, September.
    10. Michael T. Owyang, 2002. "Modeling Volcker as a non-absorbing state: agnostic identification of a Markov-switching VAR," Working Papers 2002-018, Federal Reserve Bank of St. Louis.
    11. 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.
    12. John Shea, 1999. "What Do Technology Shocks Do?," NBER Chapters,in: NBER Macroeconomics Annual 1998, volume 13, pages 275-322 National Bureau of Economic Research, Inc.
    13. Hall, Robert E, 1988. "The Relation between Price and Marginal Cost in U.S. Industry," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 921-947, October.
    14. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    15. Jon Faust, 1998. "The robustness of identified VAR conclusions about money," International Finance Discussion Papers 610, Board of Governors of the Federal Reserve System (U.S.).
    16. Canova, Fabio & Nicolo, Gianni De, 2002. "Monetary disturbances matter for business fluctuations in the G-7," Journal of Monetary Economics, Elsevier, vol. 49(6), pages 1131-1159, September.
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    Cited by:

    1. Whelan, Karl T., 2009. "Technology shocks and hours worked: Checking for robust conclusions," Journal of Macroeconomics, Elsevier, vol. 31(2), pages 231-239, June.
    2. Cristiano Cantore & Miguel León-Ledesma & Peter McAdam & Alpo Willman, 2014. "Shocking Stuff: Technology, Hours, And Factor Substitution," Journal of the European Economic Association, European Economic Association, vol. 12(1), pages 108-128, February.
    3. Nikolay Gospodinov & Alex Maynard & Elena Pesavento, 2011. "Sensitivity of Impulse Responses to Small Low-Frequency Comovements: Reconciling the Evidence on the Effects of Technology Shocks," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(4), pages 455-467, October.
    4. Gert Peersman & Roland Straub, 2009. "Technology Shocks And Robust Sign Restrictions In A Euro Area Svar," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(3), pages 727-750, August.
    5. Mark Weder, 2006. "A heliocentric journey into Germany's Great Depression," Oxford Economic Papers, Oxford University Press, vol. 58(2), pages 288-316, April.
    6. 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.
    7. Neville R. Francis & Michael T. Owyang & Athena T. Theodorou, 2005. "What Explains the Varying Monetary Response to Technology Shocks in G-7 Countries?," International Journal of Central Banking, International Journal of Central Banking, vol. 1(3), December.
    8. Rodolfo Mendez-Marcano, 2014. "Technology, Employment, and the Oil-Countries Business Cycle," Working Papers 1405, BBVA Bank, Economic Research Department.
    9. Mertens, Elmar, 2010. "Structural shocks and the comovements between output and interest rates," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1171-1186, June.
    10. Neville Francis & Valerie A. Ramey, 2006. "The Source of Historical Economic Fluctuations: An Analysis Using Long-Run Restrictions," NBER Chapters,in: NBER International Seminar on Macroeconomics 2004, pages 17-73 National Bureau of Economic Research, Inc.
    11. Ossama Mikhail, 2005. "What Happens After A Technology Shock? A Bayesian Perspective," Macroeconomics 0510016, University Library of Munich, Germany.
    12. Kim, Sangho & Lim, Hyunjoon & Park, Donghyun, 2010. "Productivity and Employment in a Developing Country: Some Evidence from Korea," World Development, Elsevier, vol. 38(4), pages 514-522, April.
    13. 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.
    14. Roland Straub & Gert Peersman, 2006. "Putting the New Keynesian Model to a Test," IMF Working Papers 06/135, International Monetary Fund.

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    Keywords

    Business cycles ; Technology;

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