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A critique of structural VARs using real business cycle theory

  • V. V. Chari
  • Patrick J. Kehoe
  • Ellen R. McGrattan

The main substantive finding of the recent structural vector autoregression literature with a differenced specification of hours (DSVAR) is that technology shocks lead to a fall in hours. Researchers have used these results to argue that business cycle models in which technology shocks lead to a rise in hours should be discarded. We evaluate the DSVAR approach by asking, is the specification derived from this approach misspecified when the data are generated by the very model the literature is trying to discard? We find that it is misspecified. Moreover, this misspecification is so great that it leads to mistaken inferences that are quantitatively large. We show that the other popular specification that uses the level of hours (LSVAR) is also misspecified. We argue that alternative state space approaches, including the business cycle accounting approach, are more fruitful techniques for guiding the development of business cycle theory.> > Replaced by Staff Report No. 364

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Paper provided by Federal Reserve Bank of Minneapolis in its series Working Papers with number 631.

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Date of creation: 2005
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Handle: RePEc:fip:fedmwp:631
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  1. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What happens after a technology shock?," International Finance Discussion Papers 768, Board of Governors of the Federal Reserve System (U.S.).
  2. 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.
  3. Lars Peter Hansen & Thomas J. Sargent, 1979. "Formulating and estimating dynamic linear rational expectations models," Working Papers 127, Federal Reserve Bank of Minneapolis.
  4. V. V. Chari & Patrick Kehoe & Ellen McGrattan, 2004. "Business Cycle Accounting," Levine's Bibliography 122247000000000560, UCLA Department of Economics.
  5. Christopher Erceg & Luca Guerrieri & Christopher Gust, 2004. "Can long-run restrictions identify technology shocks?," International Finance Discussion Papers 792, Board of Governors of the Federal Reserve System (U.S.).
  6. 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.
  7. Alan C. Stockman & Linda L. Tesar, 1991. "Tastes and technology in a two-country model of the business cycle: explaining international co-movements," Working Paper 9019, Federal Reserve Bank of Cleveland.
  8. Lars Peter Hansen & Ellen R. McGrattan & Thomas J. Sargent, 1994. "Mechanics of forming and estimating dynamic linear economies," Staff Report 182, Federal Reserve Bank of Minneapolis.
  9. Cooley, Thomas F & Hansen, Gary D, 1989. "The Inflation Tax in a Real Business Cycle Model," American Economic Review, American Economic Association, vol. 79(4), pages 733-48, September.
  10. 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.
  11. Gali, Jordi, 1992. "How Well Does the IS-LM Model Fit Postwar U.S. Data," The Quarterly Journal of Economics, MIT Press, vol. 107(2), pages 709-38, May.
  12. Hansen, Gary D., 1985. "Indivisible labor and the business cycle," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 309-327, November.
  13. Faust, Jon, 1996. "Near Observational Equivalence and Theoretical size Problems with Unit Root Tests," Econometric Theory, Cambridge University Press, vol. 12(04), pages 724-731, October.
  14. Lawrence J. Christiano & Martin Eichenbaum & Charles L. Evans, 2001. "Nominal rigidities and the dynamic effects of a shock to monetary policy," Working Paper Series WP-01-08, Federal Reserve Bank of Chicago.
  15. Jordi Gali & J. David Lopez-Salido & Javier Valles, 2002. "Technology Shocks and Monetary Policy: Assessing the Fed's Performance," NBER Working Papers 8768, National Bureau of Economic Research, Inc.
  16. Cogley, Timothy & Nason, James M, 1995. "Output Dynamics in Real-Business-Cycle Models," American Economic Review, American Economic Association, vol. 85(3), pages 492-511, June.
  17. Ben Bernanke & Mark Gertler & Simon Gilchrist, 1998. "The Financial Accelerator in a Quantitative Business Cycle Framework," NBER Working Papers 6455, National Bureau of Economic Research, Inc.
  18. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, March.
  19. Blanchard, Olivier Jean & Quah, Danny, 1993. "The Dynamic Effects of Aggregate Demand and Supply Disturbances: Reply," American Economic Review, American Economic Association, vol. 83(3), pages 653-58, June.
  20. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," NBER Working Papers 2589, National Bureau of Economic Research, Inc.
  21. Julio J. Rotemberg & Michael Woodford, 1989. "Oligopolistic Pricing and the Effects of Aggregate Demand on Economic Activity," NBER Working Papers 3206, National Bureau of Economic Research, Inc.
  22. Burmeister, Edwin & Wall, Kent D & Hamilton, James D, 1986. "Estimation of Unobserved Expected Monthly Inflation Using Kalman Filtering," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(2), pages 147-60, April.
  23. Anton Braun, R., 1994. "Tax disturbances and real economic activity in the postwar United States," Journal of Monetary Economics, Elsevier, vol. 33(3), pages 441-462, June.
  24. Robert E. Hall, 1997. "Macroeconomic Fluctuations and the Allocation of Time," NBER Working Papers 5933, National Bureau of Economic Research, Inc.
  25. Greenwood, Jeremy & Hercowitz, Zvi, 1991. "The Allocation of Capital and Time over the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 99(6), pages 1188-214, December.
  26. Uhlig, Harald, 1999. "What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure," CEPR Discussion Papers 2137, C.E.P.R. Discussion Papers.
  27. Jon Faust & Eric M. Leeper, 1994. "When do long-run identifying restrictions give reliable results?," International Finance Discussion Papers 462, Board of Governors of the Federal Reserve System (U.S.).
  28. Quah, D., 1989. "Permanent And Transitory Movements In Labor Income: An Explanation For "Excess Smoothness" In Consumption," Working papers 535, Massachusetts Institute of Technology (MIT), Department of Economics.
  29. 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.
  30. Marco Lippi & Lucrezia Reichlin, 1993. "The dynamic effects of aggregate demand and supply disturbances: comment," ULB Institutional Repository 2013/10159, ULB -- Universite Libre de Bruxelles.
  31. McGrattan, Ellen R., 1994. "The macroeconomic effects of distortionary taxation," Journal of Monetary Economics, Elsevier, vol. 33(3), pages 573-601, June.
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  34. repec:cup:etheor:v:12:y:1996:i:4:p:724-31 is not listed on IDEAS
  35. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
  36. Bencivenga, Valerie R, 1992. "An Econometric Study of Hours and Output Variation with Preference Shocks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(2), pages 449-71, May.
  37. 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.
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