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Initial Expectations in New Keynesian Models with Learning

  • James Murray


    (Indiana University Bloomington)

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    This paper examines how the estimation results for a standard New Keynesian model with constant gain least squares learning is sensitive to the stance taken on agents beliefs at the beginning of the sample. The New Keynesian model is estimated under rational expectations and under learning with three different frameworks for how expectations are set at the beginning of the sample. The results show that initial beliefs can have an impact on the predictions of an estimated model; in fact previous literature has exposed this sensitivity to explain the changing volatilities of output and inflation in the post-war United States. The results indicate statistical evidence for adaptive learning, however the rational expectations framework performs at least as well as the learning frameworks, if not better, in in-sample and out-of-sample forecast error criteria. Moreover, learning is not found to better explain time varying macroeconomic volatility any better than rational expectations. Finally, impulse response functions from the estimated models show that the dynamics following a structural shock can depend crucially on how expectations are initialized and what information agents are assumed to have.

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    Paper provided by Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington in its series Caepr Working Papers with number 2008-017.

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    Length: 37 pages
    Date of creation: Jun 2008
    Date of revision:
    Handle: RePEc:inu:caeprp:2008-017
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    1. Athanasios Orphanides & John C. Williams, 2005. "Inflation scares and forecast-based monetary policy," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 498-527, April.
    2. James M. Nason & Gregor W. Smith, 2005. "Identifying the New Keynesian Phillips Curve," Working Papers 1026, Queen's University, Department of Economics.
    3. Giorgio Primiceri, 2005. "Why Inflation Rose and Fell: Policymakers' Beliefs and US Postwar Stabilization Policy," NBER Working Papers 11147, National Bureau of Economic Research, Inc.
    4. Peter N. Ireland, 2004. "Technology Shocks in the New Keynesian Model," NBER Working Papers 10309, National Bureau of Economic Research, Inc.
    5. Preston, Bruce, 2005. "Learning about Monetary Policy Rules when Long-Horizon Expectations Matter," MPRA Paper 830, University Library of Munich, Germany.
    6. Timothy Cogley & Argia M. Sbordone, 2005. "A search for a structural Phillips curve," Staff Reports 203, Federal Reserve Bank of New York.
    7. Marc P. Giannoni & Michael Woodford, 2003. "Optimal Inflation Targeting Rules," NBER Working Papers 9939, National Bureau of Economic Research, Inc.
    8. Raf Wouters & Sergey Slobodyan, 2007. "Learning dynamics in an estimated medium-sized DSGE model," 2007 Meeting Papers 689, Society for Economic Dynamics.
    9. McCallum, Bennett T., 1999. "Issues in the design of monetary policy rules," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 23, pages 1483-1530 Elsevier.
    10. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
    11. Jeffrey C. Fuhrer, 2000. "Habit Formation in Consumption and Its Implications for Monetary-Policy Models," American Economic Review, American Economic Association, vol. 90(3), pages 367-390, June.
    12. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
    13. Marcet, Albert & Sargent, Thomas J, 1989. "Convergence of Least-Squares Learning in Environments with Hidden State Variables and Private Information," Journal of Political Economy, University of Chicago Press, vol. 97(6), pages 1306-22, December.
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