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What does a technology shock do? A VAR analysis with model-based sign restrictions

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  • Luca Dedola

    ()

    (European Central Bank, Research Department)

  • Stefano Neri

    ()

    (Bank of Italy, Research Department)

Abstract

This paper estimates the effects of technology shocks in VAR models of the U.S., identified by imposing restrictions on the sign of impulse responses. These restrictions are consistent with the implications of a popular class of DSGE models, with both real and nominal frictions, and with sufficiently wide ranges for their parameters. This identification strategy thus substitutes theoretically-motivated restrictions for the atheoretical assumptions on the time-series properties of the data that are key to long-run restrictions. Stochastic technology improvements persistently increase real wages, consumption, investment and output in the data; hours worked are very likely to increase, displaying a hump-shaped pattern. Contrary to most of the related VAR evidence, results are not sensitive to a number of specification assumptions, including those on the stationarity properties of variables.

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Paper provided by Bank of Italy, Economic Research and International Relations Area in its series Temi di discussione (Economic working papers) with number 607.

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Date of creation: Dec 2006
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Handle: RePEc:bdi:wptemi:td_607_06
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Keywords: technology shocks; DSGE models; bayesian VAR methods; identification;

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Find related papers by JEL classification:
  • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
  • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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  1. 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.
  2. Jesus Fernandez-Villaverde & Juan F. Rubio-Ramirez, 2004. "Estimating Dynamic Equilibrium Economies: Linear versus Nonlinear Likelihood," PIER Working Paper Archive 04-005, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
  3. Mark Bils & Peter J. Klenow, 2004. "Some Evidence on the Importance of Sticky Prices," Journal of Political Economy, University of Chicago Press, vol. 112(5), pages 947-985, October.
  4. Lawrence J. Christiano & Martin Eichenbaum & Charles Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Working Paper 0107, Federal Reserve Bank of Cleveland.
  5. Robert J. Vigfusson, 2004. "The delayed response to a technology shock: a flexible price explanation," International Finance Discussion Papers 810, Board of Governors of the Federal Reserve System (U.S.).
  6. Poirier, Dale J, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends: A Comment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 381-86, Oct.-Dec..
  7. Marvin J. Barth III & Valerie A. Ramey, 2000. "The Cost Channel of Monetary Transmission," NBER Working Papers 7675, National Bureau of Economic Research, Inc.
  8. 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.).
  9. Susanto Basu & John Fernald & Miles Kimball, 2004. "Are technology improvements contractionary?," Working Paper Series WP-04-20, Federal Reserve Bank of Chicago.
  10. Canova, Fabio, 2002. "Validating Monetary DSGE Models through VARs," CEPR Discussion Papers 3442, C.E.P.R. Discussion Papers.
  11. Phillips, P C B, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 333-64, Oct.-Dec..
  12. Luca Dedola & Stefano Neri, 2006. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Temi di discussione (Economic working papers) 607, Bank of Italy, Economic Research and International Relations Area.
  13. Clarida, R. & Gali, J. & Gertler, M., 1998. "Monetary Policy Rules and Macroeconomic Stability: Evidence and some Theory," Working Papers 98-01, C.V. Starr Center for Applied Economics, New York University.
  14. Christopher J. Erceg & Luca Guerrieri & Christopher Gust, 2005. "Can Long-Run Restrictions Identify Technology Shocks?," Journal of the European Economic Association, MIT Press, vol. 3(6), pages 1237-1278, December.
  15. Leamer, Edward E, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends: Comment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 371-73, Oct.-Dec..
  16. John Bailey Jones, 1999. "Has Fiscal Policy Helped Stabilize the Postwar U.S. Economy?," Discussion Papers 99-03, University at Albany, SUNY, Department of Economics.
  17. Robert G. King & Sergio T. Rebelo, 2000. "Resuscitating Real Business Cycles," RCER Working Papers 467, University of Rochester - Center for Economic Research (RCER).
  18. Galí, Jordi & Rabanal, Pau, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBC Model Fit Post-War US Data?," CEPR Discussion Papers 4522, C.E.P.R. Discussion Papers.
  19. Koop, Gary & Steel, Mark F J, 1991. "To Criticize the Critics: An Objective Bayesian Analysis of Stochastic Trends: A Comment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 365-70, Oct.-Dec..
  20. Finn E. Kydland, 1993. "Business cycles and aggregate labor-market fluctuations," Working Paper 9312, Federal Reserve Bank of Cleveland.
  21. Bernanke, Ben S. & Mihov, Ilian, 1995. "Measuring Monetary Policy," Economics Series 10, Institute for Advanced Studies.
  22. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
  23. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  24. Greenwood, Jeremy & Hercowitz, Zvi & Krusell, Per, 2000. "The role of investment-specific technological change in the business cycle," European Economic Review, Elsevier, vol. 44(1), pages 91-115, January.
  25. Francis, Neville & Ramey, Valerie A., 2005. "Is the technology-driven real business cycle hypothesis dead? Shocks and aggregate fluctuations revisited," Journal of Monetary Economics, Elsevier, vol. 52(8), pages 1379-1399, November.
  26. Lawrence J. Christiano & Martin Eichenbaum, 1990. "Current real business cycle theories and aggregate labor market fluctuations," Working Paper Series, Macroeconomic Issues 90, Federal Reserve Bank of Chicago.
  27. Michael Dotsey, 1999. "The importance of systematic monetary policy for economic activity," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 41-60.
  28. James H. Stock & Mark W. Watson, 2002. "Has the Business Cycle Changed and Why?," NBER Working Papers 9127, National Bureau of Economic Research, Inc.
  29. Marianne Baxter & Robert G. King, 1995. "Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series," NBER Working Papers 5022, National Bureau of Economic Research, Inc.
  30. G. Peersman & R. Straub, 2005. "Technology Shocks and Robust Sign Restrictions in a Euro Area SVAR," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 05/288, Ghent University, Faculty of Economics and Business Administration.
  31. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2004. "The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology," NBER Working Papers 10254, National Bureau of Economic Research, Inc.
  32. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2008. "Are Structural VARs with Long-Run Restrictions Useful in Developing Business Cycle Theory?," NBER Working Papers 14430, National Bureau of Economic Research, Inc.
  33. Timothy Cogley & Thomas Sargent, . "Drifts and Volatilities: Monetary Policies and Outcomes in the Post WWII US," Working Papers 2133503, Department of Economics, W. P. Carey School of Business, Arizona State University.
  34. Jonas D. M. Fisher, 2006. "The Dynamic Effects of Neutral and Investment-Specific Technology Shocks," Journal of Political Economy, University of Chicago Press, vol. 114(3), pages 413-451, June.
  35. Gali, J., 1996. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," Working Papers 96-28, C.V. Starr Center for Applied Economics, New York University.
  36. 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.
  37. Fabio Canova & Gianni De Nicolo, 2000. "Monetary disturbances matter for business fluctuations in the G-7," International Finance Discussion Papers 660, Board of Governors of the Federal Reserve System (U.S.).
  38. Cooley, Thomas F. & Dwyer, Mark, 1998. "Business cycle analysis without much theory A look at structural VARs," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 57-88.
  39. Thomas Lubik & Frank Schorfheide, 2002. "Testing for Indeterminacy:An Application to U.S. Monetary Policy," Economics Working Paper Archive 480, The Johns Hopkins University,Department of Economics, revised Jun 2003.
  40. Jordi Gali & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBS Model Fit Postwar U.S. Data?," NBER Working Papers 10636, National Bureau of Economic Research, Inc.
  41. Jonas Fisher, 2004. "Technology Shocks Matter," Econometric Society 2004 North American Winter Meetings 14, Econometric Society.
  42. Ellen McGrattan & V. V. Chari & Patrick Kehoe, 2005. "Are Structural VARs Useful Guides for Developing Business Cycle Theories?," 2005 Meeting Papers 664, Society for Economic Dynamics.
  43. Harald Uhlig, 2004. "Do Technology Shocks Lead to a Fall in Total Hours Worked?," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 361-371, 04/05.
  44. Greenwood, Jeremy & Hercowitz, Zvi & Huffman, Gregory W, 1988. "Investment, Capacity Utilization, and the Real Business Cycle," American Economic Review, American Economic Association, vol. 78(3), pages 402-17, June.
  45. Julio J. Rotemberg, 2003. "Stochastic Technical Progress, Smooth Trends, and Nearly Distinct Business Cycles," American Economic Review, American Economic Association, vol. 93(5), pages 1543-1559, December.
  46. Ellen R. McGrattan, 2004. "Comment on Gali and Rabanal's "Technology shocks and aggregate fluctuations: how well does the RBC model fit postwar U.S. data?"," Staff Report 338, Federal Reserve Bank of Minneapolis.
  47. Kydland, Finn E., 1984. "Labor-force heterogeneity and the business cycle," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 21(1), pages 173-208, January.
  48. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
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