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Great Moderation debate: should we be worry about using approximated policy functions?

  • Arturo Ormeno

    (Universitat Pompeu Fabra)

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    Is the evidence favouring a change in the monetary policy rule during the early 80’s biased by the omission of relevant terms in the approximated policy function? Can we use Bayesian estimation of Dynamic Stochastic General Equilibrium (DSGE) models to provide evidence supporting the “good luck” or “good policy” hypotheses as competing explanations of the Great Moderation? In this paper I shed light on the magnitude of the bias generated by the omission of second order terms in the approximated policy functions used in Bayesian econometrics. The results of this study show that this bias is not important for high volatility periods such as the one experimented between the 60’s and 70’s.

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    Paper provided by Society for Economic Dynamics in its series 2008 Meeting Papers with number 659.

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    Date of creation: 2008
    Date of revision:
    Handle: RePEc:red:sed008:659
    Contact details of provider: Postal: Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA
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    1. Galí, Jordi & Gambetti, Luca, 2008. "On the Sources of the Great Moderation," CEPR Discussion Papers 6632, C.E.P.R. Discussion Papers.
    2. Olivier Blanchard & John Simon, 2001. "The Long and Large Decline in U.S. Output Volatility," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 32(1), pages 135-174.
    3. Stephen G Cecchetti & Alfonso Flores-Lagunes & Stefan Krause, 2005. "Assessing the Sources of Changes in the Volatility of Real Growth," RBA Annual Conference Volume, in: Christopher Kent & David Norman (ed.), The Changing Nature of the Business Cycle Reserve Bank of Australia.
    4. Canova, Fabio & Gambetti, Luca, 2006. "Structural Changes in the US Economy: Bad Luck or Bad Policy?," CEPR Discussion Papers 5457, C.E.P.R. Discussion Papers.
    5. Dynan, Karen E. & Elmendorf, Douglas W. & Sichel, Daniel E., 2006. "Can financial innovation help to explain the reduced volatility of economic activity?," Journal of Monetary Economics, Elsevier, vol. 53(1), pages 123-150, January.
    6. Rabanal, Pau & Rubio-Ramirez, Juan F., 2005. "Comparing New Keynesian models of the business cycle: A Bayesian approach," Journal of Monetary Economics, Elsevier, vol. 52(6), pages 1151-1166, September.
    7. Chang-Jin Kim & Charles R. Nelson, 1999. "Has The U.S. Economy Become More Stable? A Bayesian Approach Based On A Markov-Switching Model Of The Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 608-616, November.
    8. Uhlig, H.F.H.V.S., 1995. "A toolkit for analyzing nonlinear dynamic stochastic models easily," Discussion Paper 1995-97, Tilburg University, Center for Economic Research.
    9. Fabio Canova & Luca Gambetti & Evi Pappa, 2006. "The structural dynamics of output growth and inflation: some international evidence," Economics Working Papers 971, Department of Economics and Business, Universitat Pompeu Fabra, revised Aug 2006.
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