Forecast Combination Based on Multiple Encompassing Tests in a Macroeconomic DSGE System
AbstractWe use data generated by a macroeconomic DSGE model to study the relative benefits of forecast combinations based on forecast-encompassing tests relative to simple uniformly weighted forecast averages across rival models. Assumed rival models are four linear autoregressive specifications, one of them a more sophisticated factor-augmented vector autoregression (FAVAR). The forecaster is assumed not to know the true data-generating DSGE model. The results critically depend on the prediction horizon. While one-step prediction hardly supports test-based combinations, the test-based procedure attains a clear lead at prediction horizons greater than two.
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Bibliographic InfoPaper provided by Institute for Advanced Studies in its series Economics Series with number 251.
Length: 19 pages
Date of creation: May 2010
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Find related papers by JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-05-22 (All new papers)
- NEP-CBA-2010-05-22 (Central Banking)
- NEP-DGE-2010-05-22 (Dynamic General Equilibrium)
- NEP-ECM-2010-05-22 (Econometrics)
- NEP-ETS-2010-05-22 (Econometric Time Series)
- NEP-FOR-2010-05-22 (Forecasting)
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