Working Paper: CEPR ID: DP8604
Authors: Raffaella Giacomini; Giuseppe Ragusa
Abstract: We propose a method for modifying a given density forecast in a way that incorporates the information contained in theory-based moment conditions. An example is "improving" the forecasts from atheoretical econometric models, such as factor models or Bayesian VARs, by ensuring that they satisfy theoretical restrictions given for example by Euler equations or Taylor rules. The method yields a new density (and thus point-) forecast which has a simple and convenient analytical expression and which by construction satisfies the theoretical restrictions. The method is flexible and can be used in the realistic situation in which economic theory does not specify a likelihood for the variables of interest, and thus cannot be readily used for forecasting.
Keywords: Bayesian VAR; Euler conditions; Exponential tilting; Forecast comparisons
JEL Codes: C53
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| initial density forecasts (C53) | new density forecast (C53) |
| theoretical restrictions (C60) | new density forecast (C53) |
| new density forecast (C53) | forecast accuracy (C53) |
| theoretical restrictions (C60) | forecast accuracy (C53) |