IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this article

Identification of Technology Shocks in Structural Vars

  • Patrick Fève
  • Alain Guay

The usefulness of SVARs for developing empirically plausible models is actually subject to controversies in macroeconomics. We propose a two-step SVARs-based procedure which consistently estimates the effect of permanent technology shocks on aggregate variables. Simulation experiments from a standard business cycle model and a sticky prices model show that our approach outperforms standard SVARs. The two-step procedure, when applied to actual data, predicts a significant short-run decrease of hours after a technology improvement followed by a hump-shaped positive response. Additionally, the rate of inflation and the nominal interest rate displays a significant decrease after this shock. Copyright (C) The Author(s). Journal compilation (C) Royal Economic Society 2009.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1468-0297.2009.02328.x
File Function: link to full text
Download Restriction: Access to full text is restricted to subscribers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Article provided by Royal Economic Society in its journal The Economic Journal.

Volume (Year): 120 (2010)
Issue (Month): 549 (December)
Pages: 1284-1318

as
in new window

Handle: RePEc:ecj:econjl:v:120:y:2010:i:549:p:1284-1318
Contact details of provider: Postal:
Office of the Secretary-General, Rm E35, The Bute Building, Westburn Lane, St Andrews, KY16 9TS, UK

Phone: +44 1334 462479
Web page: http://www.res.org.uk/
Email:


More information through EDIRC

Order Information: Web: http://www.blackwellpublishers.co.uk/asp/journal.asp?ref=0013-0133

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2005. "A critique of structural VARs using real business cycle theory," Working Papers 631, Federal Reserve Bank of Minneapolis.
  2. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Proceedings, Federal Reserve Bank of San Francisco, issue Jun.
  3. Yongsung Chang & Taeyoung Doh & Frank Schorfheide, 2007. "Non-stationary Hours in a DSGE Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(6), pages 1357-1373, 09.
  4. 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.
  5. Craig Burnside & Martin Eichenbaum, 1994. "Factor Hoarding and the Propagation of Business Cycles Shocks," NBER Working Papers 4675, National Bureau of Economic Research, Inc.
  6. Olivier Jean Blanchard & Danny Quah, 1988. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," NBER Working Papers 2737, National Bureau of Economic Research, Inc.
  7. V. V. Chari & Patrick J. Kehoe & Ellen R. McGrattan, 2007. "Business Cycle Accounting," Econometrica, Econometric Society, vol. 75(3), pages 781-836, 05.
  8. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-66, July.
  9. 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.
  10. Cooley, Thomas F. & Leroy, Stephen F., 1985. "Atheoretical macroeconometrics: A critique," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 283-308, November.
  11. Federico Ravenna, 2006. "Vector autoregressions and reduced form representations of DSGE models," Working Papers 0619, Banco de España;Working Papers Homepage.
  12. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  13. Ramey, Valerie A & Francis, Neville, 2002. "Is The Technology-Driven Real Business Cycle Hypothesis Dead? Shocks and Aggregate Fluctuations Revisted," University of California at San Diego, Economics Working Paper Series qt6x80k3nx, Department of Economics, UC San Diego.
  14. Christopher J. Erceg & Luca Guerrieri & Christopher J. Gust, 2004. "Can long-run restrictions identify technology shocks?," International Finance Discussion Papers 792, Board of Governors of the Federal Reserve System (U.S.).
  15. Lewis, Richard & Reinsel, Gregory C., 1985. "Prediction of multivariate time series by autoregressive model fitting," Journal of Multivariate Analysis, Elsevier, vol. 16(3), pages 393-411, June.
  16. Hall, Robert E, 1997. "Macroeconomic Fluctuations and the Allocation of Time," Journal of Labor Economics, University of Chicago Press, vol. 15(1), pages S223-50, January.
  17. Jon Faust & Eric M. Leeper, 1994. "When do long-run identifying restrictions give reliable results?," FRB Atlanta Working Paper 94-2, Federal Reserve Bank of Atlanta.
  18. Pao-Li Chang & Shinichi Sakata, 2007. "Estimation of impulse response functions using long autoregression," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 453-469, 07.
  19. Ireland, Peter N., 2003. "Endogenous money or sticky prices?," Journal of Monetary Economics, Elsevier, vol. 50(8), pages 1623-1648, November.
  20. Elena Pesavento & Barbara Rossi, 2004. "Do Technology Shocks Drive Hours Up or Down? A Little Evidence From an Agnostic Procedure," Econometrics 0411002, EconWPA.
  21. 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 819-40, September.
  22. Gospodinov, Nikolay, 2010. "Inference in Nearly Nonstationary SVAR Models With Long-Run Identifying Restrictions," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 1-12.
  23. Newey, Whitney K., 1984. "A method of moments interpretation of sequential estimators," Economics Letters, Elsevier, vol. 14(2-3), pages 201-206.
  24. 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 430-50, June.
  25. Kenneth D. West & Whitney K. Newey, 1995. "Automatic Lag Selection in Covariance Matrix Estimation," NBER Technical Working Papers 0144, National Bureau of Economic Research, Inc.
  26. Lawrence J. Christiano & Martin Eichenbaum & Robert J. Vigfusson, 2003. "What happens after a technology shock?," International Finance Discussion Papers 768, Board of Governors of the Federal Reserve System (U.S.).
  27. 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.
  28. Neville Francis & Michael T. Owyang & Jennifer E. Roush & Riccardo DiCecio, 2014. "A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks," The Review of Economics and Statistics, MIT Press, vol. 96(4), pages 638-647, October.
  29. John H. Cochrane, 1994. "Permanent and Transitory Components of GNP and Stock Prices," The Quarterly Journal of Economics, Oxford University Press, vol. 109(1), pages 241-265.
  30. 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.).
  31. Neville Francis & Michael T. Owyang & Jennifer E. Roush, 2005. "A flexible finite-horizon identification of technology shocks," International Finance Discussion Papers 832, Board of Governors of the Federal Reserve System (U.S.).
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:ecj:econjl:v:120:y:2010:i:549:p:1284-1318. 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: (Wiley-Blackwell Digital Licensing)

or (Christopher F. Baum)

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.