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Business cycle measurement with some theory

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  • Canova, Fabio
  • Paustian, Matthias

Abstract

A method to evaluate cyclical models which does not require knowledge of the DGP and the exact specification of the aggregate decision rules is proposed. We derive robust restrictions in a class of models; use some to identify structural shocks in the data and others to evaluate the class or contrast sub-models. The approach has good properties, even in small samples, and when the class of models is misspecified. We show how to sort out the relevance of a certain friction (the presence of rule-of-thumb consumers) in a standard class of models.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 8364.

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Date of creation: Apr 2011
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Handle: RePEc:cpr:ceprdp:8364

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Keywords: misspecification; model validation; shock identification; sign restrictions;

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References

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  1. 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.
  2. Juan F. Rubio-Ramírez & Daniel F.Waggoner & Tao Zha, 2008. "Structural vector autoregressions: theory of identification and algorithms for inference," Working Paper 2008-18, Federal Reserve Bank of Atlanta.
  3. Uhlig, H.F.H.V.S., 1999. "What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure," Discussion Paper 1999-28, Tilburg University, Center for Economic Research.
  4. 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.
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  6. Lutz Kilian & Daniel P. Murphy, 2012. "Why Agnostic Sign Restrictions Are Not Enough: Understanding The Dynamics Of Oil Market Var Models," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1166-1188, October.
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  13. 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, 08.
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  15. Martin Fukac & Adrian Pagan, 2010. "Limited information estimation and evaluation of DSGE models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 55-70.
  16. 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.
  17. Roberto Perotti, 2008. "In Search of the Transmission Mechanism of Fiscal Policy," NBER Chapters, in: NBER Macroeconomics Annual 2007, Volume 22, pages 169-226 National Bureau of Economic Research, Inc.
  18. Ravi Bansal & Amir Yaron, 2004. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," Journal of Finance, American Finance Association, vol. 59(4), pages 1481-1509, 08.
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  27. Canova, Fabio & Gambetti, Luca, 2009. "Do expectations matter? The Great Moderation revisited," CEPR Discussion Papers 7597, C.E.P.R. Discussion Papers.
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  30. Evi Pappa, 2009. "The Effects Of Fiscal Shocks On Employment And The Real Wage," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 50(1), pages 217-244, 02.
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Citations

RePEc Biblio mentions

As found on the RePEc Biblio, the curated bibliography for Economics:
  1. > Econometrics > Time Series Models > VAR Models > Sign Restrictions
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Cited by:
  1. Cantore, Cristiano & León-Ledesma, Miguel A. & McAdam, Peter & Willman, Alpo, 2010. "Shocking stuff: technology, hours, and factor substitution," Working Paper Series 1278, European Central Bank.
  2. Amir-Ahmadi, Pooyan & Matthes, Christian & Wang, Mu-Chun, 2014. "Drifts, Volatilities, and Impulse Responses Over the Last Century," Working Paper 14-10, Federal Reserve Bank of Richmond.
  3. G. C. Lim & Paul D. McNelis, 2014. "Income Inequality, Trade and Financial Openness," Melbourne Institute Working Paper Series wp2014n07, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  4. Fabio Canova & Fernando J. P�rez Forero, 2012. "Estimating Overidentified, Nonrecursive Time-Varying Coefficients Structural VARs," Working Papers 637, Barcelona Graduate School of Economics.
  5. Nikolay Hristov & Oliver Hülsewig & Timo Wollmershäuser, 2011. "Loan Supply Shocks during the Financial Crisis: Evidence for the Euro Area," CESifo Working Paper Series 3395, CESifo Group Munich.
  6. Francesco Furlanetto & Francesco Ravazzolo & Samad Sarferaz, 2014. "Identification of financial factors in economic fluctuations," Working Paper 2014/09, Norges Bank.
  7. Pitschner, Stefan, 2013. "Using Financial Markets To Estimate the Macro Effects of Monetary Policy:," Working Paper Series 267, Sveriges Riksbank (Central Bank of Sweden).
  8. Haroon Mumtaz & Gabor Pinter & Konstantinos Theodoridis, 2014. "What do VARs Tell Us about the Impact of a Credit Supply Shock? An Empirical Analysis," Working Papers 716, Queen Mary, University of London, School of Economics and Finance.
  9. Christiane Baumeister & Luca Benati, 2012. "Unconventional Monetary Policy and the Great Recession: Estimating the Macroeconomic Effects of a Spread Compression at the Zero Lower Bound," Working Papers 12-21, Bank of Canada.
  10. Eddie Gerba & Klemens Hauzenberger, 2013. "Estimating US Fiscal and Monetary Interactions in a Time Varying VAR," Studies in Economics 1303, Department of Economics, University of Kent.
  11. Fornari, Fabio & Stracca, Livio, 2013. "What does a financial shock do? First international evidence," Working Paper Series 1522, European Central Bank.

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