Overcoming the Forecasting Limitations of Forward-Looking Theory Based Models
AbstractTheory-consistent models have to be kept small to be tractable. If they are to forecast well, they have to condition on data that are unmodelled, noisy, patchy and about the future. Agents can also use these data to form their own expectations. In this paper we illustrate a scheme for jointly conditioning the forecasts and internal expectations of linearised forward-looking DSGE models on data through a Kalman Filter fixed-interval smoother. We also trial some diagnostics of this approach, in particulardecompositions that reveal when a forecast conditioned on one set of variables implies estimates of other variables which are inconsistent with economic priors.
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Bibliographic InfoArticle provided by BANCO DE LA REPÚBLICA - ESPE in its journal ENSAYOS SOBRE POLÍTICA ECONÓMICA.
Volume (Year): (2011)
Issue (Month): ()
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Conditional forecast; DSGE; Kalman filterfilter.;
Find related papers by JEL classification:
- F47 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Forecasting and Simulation: Models and Applications
- E01 - Macroeconomics and Monetary Economics - - General - - - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
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