IDEAS home Printed from
   My bibliography  Save this paper

Indeterminacy and Forecastability


  • Ippei Fujiwara
  • Yasuo Hirose


Recent studies document the deteriorating performance of forecasting models during the Great Moderation, which conversely implies that forecastability was higher in the preceding era when the economy was unexpectedly volatile. We explain this phenomenon in the context of equilibrium indeterminacy in dynamic stochastic general equilibrium (DSGE) models. We first analytically show that a model under indeterminacy exhibits richer dynamics that can improve forecastability. Then, using a sticky-price DSGE model, we numerically demonstrate that indeterminacy arising from passive monetary policy generates persistent dynamics that lead to superior forecastability. We also point out the possibility that forecastability under indeterminacy deteriorates when the degree of uncertainty about sunspot fluctuations is large.

Suggested Citation

  • Ippei Fujiwara & Yasuo Hirose, 2012. "Indeterminacy and Forecastability," CAMA Working Papers 2012-48, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Handle: RePEc:een:camaaa:2012-48

    Download full text from publisher

    File URL:
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    1. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    2. Yasuo Hirose, 2008. "Monetary Policy and Sunspot Fluctuation in the U.S. and the Euro Area," Bank of Japan Working Paper Series 08-E-7, Bank of Japan.
    3. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, Oxford University Press, vol. 115(1), pages 147-180.
    4. Thomas A. Lubik & Frank Schorfheide, 2004. "Testing for Indeterminacy: An Application to U.S. Monetary Policy," American Economic Review, American Economic Association, vol. 94(1), pages 190-217, March.
    5. 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, August.
    6. Antonello D'Agostino & Domenico Giannone & Paolo Surico, 2005. "(Un)Predictability and Macroeconomic Stability," Macroeconomics 0510024, EconWPA.
    7. 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, September.
    8. Carl E. Walsh, 2010. "Monetary Theory and Policy, Third Edition," MIT Press Books, The MIT Press, edition 3, volume 1, number 0262013770, January.
    9. Hirose, Yasuo, 2007. "Sunspot fluctuations ulnder zero nominal interest rates," Economics Letters, Elsevier, vol. 97(1), pages 39-45, October.
    10. 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.
    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. Arturo Estrella, 2005. "Why Does the Yield Curve Predict Output and Inflation?," Economic Journal, Royal Economic Society, vol. 115(505), pages 722-744, July.
    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. Rochelle M. Edge & Refet S. Gurkaynak, 2010. "How Useful Are Estimated DSGE Model Forecasts for Central Bankers?," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 41(2 (Fall)), pages 209-259.
    15. Jeffrey C. Fuhrer & Giovanni P. Olivei & Geoffrey M. B. Tootell, 2009. "Empirical estimates of changing inflation dynamics," Working Papers 09-4, Federal Reserve Bank of Boston.
    16. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Benjamin Wong, 2015. "Do Inflation Expectations Propagate the Inflationary Impact of Real Oil Price Shocks?: Evidence from the Michigan Survey," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(8), pages 1673-1689, December.
    2. Qazi Haque, 2017. "Monetary Policy, Target Inflation and the Great Moderation: An Empirical Investigation," School of Economics Working Papers 2017-10, University of Adelaide, School of Economics.
    3. Anna Florio, 2016. "The central bank as shaper and observer of events: The case of the yield spread," Canadian Journal of Economics, Canadian Economics Association, vol. 49(1), pages 320-346, February.
    4. Luca Fanelli & Marco M. Sorge, 2015. "Indeterminacy, Misspecification and Forecastability: Good Luck in Bad Policy?," CSEF Working Papers 402, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    5. repec:eee:jmacro:v:53:y:2017:i:c:p:57-70 is not listed on IDEAS

    More about this item


    Forecasting; Indeterminacy; Monetary policy;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:een:camaaa:2012-48. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Cama Admin). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.