Investigating uncertainty in macroeconomic forecasts by stochastic simulation

This file is part of IDEAS, which uses RePEc data

Investigating uncertainty in macroeconomic forecasts by stochastic simulation

Author Info

Debby Lanser ()
Henk Kranendonk ()

Abstract

Uncertainty is an inherent attribute of any forecast. In this paper, we investigate four sources of uncertainty with CPB’s macroeconomic model SAFFIER: provisional data, exogenous variables, model parameters and residuals of behavioural equations. We apply a Monte Carlo simulation technique to calculate standard errors for the short-term and medium-term horizon for GDP and eight other macroeconomic variables. The results demonstrate that the main contribution to the total variance of a medium-term forecast, emanates from the uncertainty in the exogenous variables. For the short-term forecast both exogenous variables and provisional data are most relevant.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

Publisher Info
Paper provided by CPB Netherlands Bureau for Economic Policy Analysis in its series CPB Discussion Papers with number 112.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: Sep 2008
Date of revision:
Handle: RePEc:cpb:discus:112

Contact details of provider:
Postal: Postbus 80510, 2508 GM Den Haag
Phone: (070) 338 33 80
Fax: (070) 338 33 50
Email:
Web page: http://www.cpb.nl/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: ().

Find related papers by JEL classification:
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
E20 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
E27 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation

This paper has been announced in the following NEP Reports:

NEP-ALL-2008-10-13 (All new papers)
NEP-CBA-2008-10-13 (Central Banking)
NEP-CMP-2008-10-13 (Computational Economics)
NEP-ECM-2008-10-13 (Econometrics)
NEP-FOR-2008-10-13 (Forecasting)
NEP-MAC-2008-10-13 (Macroeconomics)
NEP-ORE-2008-10-13 (Operations Research)

References listed on IDEAS
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.:

George Kapetanios, 2000. "Model Selection Uncertainty and Dynamic Models," NIESR Discussion Papers 165, National Institute of Economic and Social Research. [Downloadable!]
Ray C. Fair, 2001. "Bootstrapping Macroeconometric Models," Cowles Foundation Discussion Papers 1345, Cowles Foundation, Yale University, revised Jun 2003. [Downloadable!]
Other versions:
- Ray C. Fair, 2002. "Bootstrapping Macroeconometric Models," Yale School of Management Working Papers ysm254, Yale School of Management. [Downloadable!]
Alexei Onatski & Noah Williams, 2003. "Modeling Model Uncertainty," NBER Working Papers 9566, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
Other versions:
- Alexei Onatski & Noah Williams, 2002. "Modeling model uncertainty," Discussion Papers 0203-05, Columbia University, Department of Economics. [Downloadable!]
- Alexei Onatski & Noah Williams, 2002. "Modeling model uncertainty," Working Paper Series 169, European Central Bank. [Downloadable!]
- Alexei Onatski & Noah Williams, 2003. "Modeling Model Uncertainty," Journal of the European Economic Association, MIT Press, vol. 1(5), pages 1087-1122, 09. [Downloadable!] (restricted)

Full references

Statistics
Access and download statistics

Did you know? IDEAS also indexes book chapters.

This page was last updated on 2009-11-8.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.