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How to Evaluate the Forecasting Performance of a Macroeconomic Model

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Author Info

  • Hukkinen, Juhana

    ()
    (Bank of Finland)

  • Viren, Matti

    ()
    (Bank of Finland Research)

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    Abstract

    This paper provides an answer to the question of how to improve the forecasting performance of a macro model to better account for economic developments and how to evaluate the forecasting uncertainty. The main tool in this assessment is stochastic simulation. Stochastic simulations in this paper involve both endogenous and exogenous variables. These simulations also allow us to assess the linearity of the model. Alternative dynamic simulations may, in turn, give some idea of the stability of the model. Finally, the forecasts may be improved by comparing the outcomes from the macro model and from a leading indicators' model. This kind of exercise is particularly useful in assessing the developments in the short run, in which case the macro models typically perform rather poorly.

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    File URL: http://www.suomenpankki.fi/en/julkaisut/tutkimukset/keskustelualoitteet/Documents/DP_05_1998.pdf
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    Bibliographic Info

    Paper provided by Bank of Finland in its series Research Discussion Papers with number 5/1998.

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    Length: 29 pages
    Date of creation: 14 Apr 1998
    Date of revision:
    Handle: RePEc:hhs:bofrdp:1998_005

    Contact details of provider:
    Postal: Bank of Finland, P.O. Box 160, FI-00101 Helsinki, Finland
    Web page: http://www.suomenpankki.fi/en/
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    Related research

    Keywords: forecasting; macro models; simulation;

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    References

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    1. Pagan, Adrian, 1989. "On the role of simulation in the statistical evaluation of econometric models," Journal of Econometrics, Elsevier, vol. 40(1), pages 125-139, January.
    2. Ray C. Fair, 1989. "Does Monetary Policy Matter? Narrative Versus Structural Approaches," NBER Working Papers 3045, National Bureau of Economic Research, Inc.
    3. Brayton, Flint & Levin, Andrew & Lyon, Ralph & Williams, John C., 1997. "The evolution of macro models at the Federal Reserve Board," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 47(1), pages 43-81, December.
    4. Fair, Ray C & Taylor, John B, 1983. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 51(4), pages 1169-85, July.
    5. Palle S. Andersen, 1997. "Forecast errors and financial developments," BIS Working Papers 51, Bank for International Settlements.
    6. Rudger Dornbusch & Ilan Goldfajn & Rodrigo O. Valdés, 1995. "Currency Crises and Collapses," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 26(2), pages 219-294.
    7. Brown, Bryan W & Mariano, Roberto S, 1984. "Residual-Based Procedures for Prediction and Estimation in a Nonlinear Simultaneous System," Econometrica, Econometric Society, vol. 52(2), pages 321-43, March.
    8. Preston J. Miller & Daniel M. Chin, 1996. "Using monthly data to improve quarterly model forecasts," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Spr, pages 16-33.
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    Cited by:
    1. David Mayes & Matti Virén, 2000. "The exchange rate and monetary conditions in the Euro area," Review of World Economics (Weltwirtschaftliches Archiv), Springer, vol. 136(2), pages 199-231, June.

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