How to Evaluate the Forecasting Performance of a Macroeconomic Model
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.
|Date of creation:||14 Apr 1998|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.suomenpankki.fi/en/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Ray C. Fair, 1989. "Does Monetary Policy Matter? Narrative Versus Structural Approaches," NBER Working Papers 3045, National Bureau of Economic Research, Inc.
- Palle S. Andersen, 1997. "Forecast errors and financial developments," BIS Working Papers 51, Bank for International Settlements.
- 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.
- Ray C. Fair & John B. Taylor, 1980.
"Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models,"
Cowles Foundation Discussion Papers
564, Cowles Foundation for Research in Economics, Yale University.
- 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.
- Ray C. Fair & John B. Taylor, 1980. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear RationalExpectations Models," NBER Technical Working Papers 0005, National Bureau of Economic Research, Inc.
- 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.
- 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.
- 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.
When requesting a correction, please mention this item's handle: RePEc:hhs:bofrdp:1998_005. 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: (Minna Nyman)
If references are entirely missing, you can add them using this form.