IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/4537.html
   My bibliography  Save this paper

What Does A Technology Shock Do? A VAR Analysis with Model-based Sign Restrictions

Author

Listed:
  • Dedola, Luca
  • Neri, Stefano

Abstract

This Paper estimates the effects of technology shocks in VAR models of the United States, Japan and Germany, identified imposing restrictions on the sign of impulse responses. These restrictions are motivated with priors on the parameters of a class of DSGE models with both real and nominal frictions. Estimated technology shocks lead to substantial and persistent increases in labour productivity, real wages, consumption, investment and output. In contrast with most results in the VAR literature, hours worked are much more likely to increase, displaying a hump-shaped pattern. These results are shown to stem primarily from the identification strategy proposed in the Paper, which substitutes theoretical restrictions for the atheoretical assumptions on the time series properties of the data, that are the hallmark of long-run restrictions.

Suggested Citation

  • Dedola, Luca & Neri, Stefano, 2004. "What Does A Technology Shock Do? A VAR Analysis with Model-based Sign Restrictions," CEPR Discussion Papers 4537, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:4537
    as

    Download full text from publisher

    File URL: http://www.cepr.org/active/publications/discussion_papers/dp.php?dpno=4537
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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 381-386, Oct.-Dec..
    2. 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.
    3. Marvin J. Barth III & Valerie A. Ramey, 2002. "The Cost Channel of Monetary Transmission," NBER Chapters,in: NBER Macroeconomics Annual 2001, Volume 16, pages 199-256 National Bureau of Economic Research, Inc.
    4. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
    5. 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.
    6. 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.
    7. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2004. "The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 381-395, 04/05.
    8. Thomas A. Lubik & Frank Schorfheide, 2004. "Testing for Indeterminacy: An Application to U.S. Monetary Policy," American Economic Review, American Economic Association, vol. 94(1), pages 190-217, March.
    9. 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.
    10. Finn E. Kydland, 1993. "Business cycles and aggregate labor-market fluctuations," Working Paper 9312, Federal Reserve Bank of Cleveland.
    11. Canova, Fabio, 2002. "Validating Monetary DSGE Models through VARs," CEPR Discussion Papers 3442, C.E.P.R. Discussion Papers.
    12. Christiano, Lawrence J & Eichenbaum, Martin, 1992. "Current Real-Business-Cycle Theories and Aggregate Labor-Market Fluctuations," American Economic Review, American Economic Association, vol. 82(3), pages 430-450, June.
    13. Ben S. Bernanke & Ilian Mihov, 1998. "Measuring Monetary Policy," The Quarterly Journal of Economics, Oxford University Press, vol. 113(3), pages 869-902.
    14. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    15. Dedola, Luca & Neri, Stefano, 2007. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 512-549, March.
    16. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2005. "Nominal Rigidities and the Dynamic Effects of a Shock to Monetary Policy," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 1-45, February.
    17. 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.
    18. Juan F. Rubio-Ramirez & Jesus Fernández-Villaverde, 2005. "Estimating dynamic equilibrium economies: linear versus nonlinear likelihood," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 891-910.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. Jones, John Bailey, 2002. "Has fiscal policy helped stabilize the postwar U.S. economy?," Journal of Monetary Economics, Elsevier, vol. 49(4), pages 709-746, May.
    27. 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 333-364, Oct.-Dec..
    28. 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.
    29. 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.
    30. James H. Stock & Mark W. Watson, 2003. "Has the Business Cycle Changed and Why?," NBER Chapters,in: NBER Macroeconomics Annual 2002, Volume 17, pages 159-230 National Bureau of Economic Research, Inc.
    31. 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.).
    32. 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 365-370, Oct.-Dec..
    33. 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 402-417, June.
    34. King, Robert G. & Rebelo, Sergio T., 1999. "Resuscitating real business cycles," Handbook of Macroeconomics,in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 14, pages 927-1007 Elsevier.
    35. 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 371-373, Oct.-Dec..
    36. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-1370, November.
    37. 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.
    38. 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.
    39. 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.
    40. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
    41. 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.).
    42. 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.
    43. Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1337-1352, November.
    44. 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.
    45. Jonas D. M. Fisher, 2002. "Technology shocks matter," Working Paper Series WP-02-14, Federal Reserve Bank of Chicago.
    46. 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.
    47. Michael Dotsey, 1999. "The importance of systematic monetary policy for economic activity," Economic Quarterly, Federal Reserve Bank of Richmond, issue Sum, pages 41-60.
    48. Dedola, Luca & Neri, Stefano, 2007. "What does a technology shock do? A VAR analysis with model-based sign restrictions," Journal of Monetary Economics, Elsevier, vol. 54(2), pages 512-549, March.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Bayesian VAR methods; DSGE models; impulse responses; technology shocks;

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cpr:ceprdp:4537. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.