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Indeterminacy and forecastability

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  • Ippei Fujiwara
  • Yasuo Hirose

Abstract

Recent studies document the deteriorating performance of forecasting models during the Great Moderation. This conversely implies that forecastability is higher in the preceding era, when the economy was unexpectedly volatile. We offer an explanation for this phenomenon in the context of equilibrium indeterminacy in dynamic stochastic general equilibrium models. First, we analytically show that a model under indeterminacy exhibits richer dynamics that can improve forecastability. Then, using a prototypical New Keynesian model, we numerically demonstrate that indeterminacy due to passive monetary policy can yield superior forecastability as long as the degree of uncertainty about sunspot fluctuations is relatively small.

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Paper provided by Federal Reserve Bank of Dallas in its series Globalization and Monetary Policy Institute Working Paper with number 91.

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Date of creation: 2011
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Handle: RePEc:fip:feddgw:91

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Keywords: Forecasting ; Mathematical models ; Monetary policy;

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  1. Peter Tulip, 2009. "Has the Economy Become More Predictable? Changes in Greenbook Forecast Accuracy," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(6), pages 1217-1231, 09.
  2. Athanasios Orphanides & Simon van Norden, 2003. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," CIRANO Working Papers 2003s-01, CIRANO.
  3. Richard Clarida & Jordi Galí & Mark Gertler, 1997. "Monetary policy rules and macroeconomic stability: Evidence and some theory," Economics Working Papers 350, Department of Economics and Business, Universitat Pompeu Fabra, revised May 1999.
  4. Arturo Estrella, 2005. "Why Does the Yield Curve Predict Output and Inflation?," Economic Journal, Royal Economic Society, vol. 115(505), pages 722-744, 07.
  5. Thomas Lubik & Frank Schorfheide, 2002. "Testing for Indeterminacy:An Application to U.S. Monetary Policy," Economics Working Paper Archive 480, The Johns Hopkins University,Department of Economics, revised Jun 2003.
  6. Edge, Rochelle M & Gürkaynak, Refet S., 2010. "How Useful Are Estimated DSGE Model Forecasts for Central Bankers?," CEPR Discussion Papers 8158, C.E.P.R. Discussion Papers.
  7. Jeff Fuhrer & Giovanni Olivei & Geoffrey M. B. Tootell, 2009. "Empirical estimates of changing inflation dynamics," Working Papers 09-4, Federal Reserve Bank of Boston.
  8. Antonello D'Agostino & Domenico Giannone & Paolo Surico, 2005. "(Un)Predictability and Macroeconomic Stability," Macroeconomics 0510024, EconWPA.
  9. Yasuo Hirose, 2008. "Equilibrium Indeterminacy and Asset Price Fluctuation in Japan: A Bayesian Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(5), pages 967-999, 08.
  10. Hirose, Yasuo, 2007. "Sunspot fluctuations ulnder zero nominal interest rates," Economics Letters, Elsevier, vol. 97(1), pages 39-45, October.
  11. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
  12. Hirose, Yasuo, 2010. "Monetary policy and sunspot fluctuation in the U.S. and the Euro area," MPRA Paper 33693, University Library of Munich, Germany.
  13. Jonas D. M. Fisher & Chin Te Liu & Ruilin Zhou, 2002. "When can we forecast inflation?," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q I, pages 32-44.
  14. Faust, Jon & Wright, Jonathan H., 2009. "Comparing Greenbook and Reduced Form Forecasts Using a Large Realtime Dataset," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 468-479.
  15. Carl E. Walsh, 2010. "Monetary Theory and Policy, Third Edition," MIT Press Books, The MIT Press, edition 3, volume 1, number 0262013770, December.
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