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

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

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.

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Article provided by Federal Reserve Bank of St. Louis in its journal Review.

Volume (Year): (2003)
Issue (Month): Nov ()
Pages: 53-66

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Handle: RePEc:fip:fedlrv:y:2003:i:nov:p:53-66:n:v.85no.6
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  1. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  2. Charles L. Evans, 1991. "Productivity shocks and real business cycles," Working Paper Series, Macroeconomic Issues 91-22, Federal Reserve Bank of Chicago.
  3. 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.
  4. 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.
  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. Mountford, A.W. & Uhlig, H.F.H.V.S., 2002. "What are the Effects of Fiscal Policy Shocks?," Discussion Paper 2002-31, Tilburg University, Center for Economic Research.
  7. Susanto Basu & John Fernald & Miles Kimball, 2002. "Are Technology Improvements Contractionary?," Harvard Institute of Economic Research Working Papers 1986, Harvard - Institute of Economic Research.
  8. Robert G. King & Charles I. Plosser & James H. Stock & Mark W. Watson, 1987. "Stochastic Trends and Economic Fluctuations," NBER Working Papers 2229, National Bureau of Economic Research, Inc.
  9. 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.
  10. GalĂ­, Jordi, 1996. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," CEPR Discussion Papers 1499, C.E.P.R. Discussion Papers.
  11. 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.
  12. Olivier Jean Blanchard & Danny Quah, 1988. "The Dynamic Effects of Aggregate Demand and Supply Disturbance," Working papers 497, Massachusetts Institute of Technology (MIT), Department of Economics.
  13. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," NBER Working Papers 2589, National Bureau of Economic Research, Inc.
  14. 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 921-47, October.
  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. 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.
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