Conditional forecasts in DSGE models
AbstractNew-generation DSGE models are sometimes misspecified in dimensions that matter for their forecasting performance. The paper suggests one way to improve the forecasts of a DSGE model using a conditioning information that need not be accurate. The technique presented allows for agents to anticipate the information on the conditioning variables several periods ahead. It also allows the forecaster to apply a continuum of degrees of uncertainty around the mean of the conditioning information, making hard-conditional and unconditional forecasts special cases. An application to a small open-economy DSGE model shows that the benefits of conditioning depend crucially on the ability of the model to capture the correlation between the conditioning information and the variables of interest.
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Bibliographic InfoPaper provided by Norges Bank in its series Working Paper with number 2010/07.
Length: 29 pages
Date of creation: 27 Apr 2010
Date of revision:
Note: First version:
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DSGE model; conditional forecast;
Find related papers by JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-06-04 (All new papers)
- NEP-CBA-2010-06-04 (Central Banking)
- NEP-DGE-2010-06-04 (Dynamic General Equilibrium)
- NEP-FOR-2010-06-04 (Forecasting)
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Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:CitEc Project, subscribe to its RSS feed for this item.
- Andersson, Michael K. & Palmqvist, Stefan & Waggoner, Daniel F., 2010. "Density-Conditional Forecasts in Dynamic Multivariate Models," Working Paper Series 247, Sveriges Riksbank (Central Bank of Sweden).
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