Working Paper: CEPR ID: DP6526
Authors: Andrew J. Patton; Allan G. Timmermann
Abstract: We develop a theoretical framework for understanding how agents form expectations about economic variables with a partially predictable component. Our model incorporates the effect of measurement errors and heterogeneity in individual forecasters' prior beliefs and their information signals and also accounts for agents' learning in real time about past, current and future values of economic variables. We use the model to develop insights into the term structure of forecast errors, and test its implications on a data set comprising survey forecasts of annual GDP growth and inflation with horizons ranging from 1 to 24 months. The model is found to closely match the term structure of forecast errors for consensus beliefs and is able to replicate the cross-sectional dispersion in forecasts of GDP growth but not for inflation - the latter appearing to be too high in the data at short horizons. Our analysis also suggests that agents systematically underestimated the persistent component of GDP growth but overestimated it for inflation during most of the 1990s.
Keywords: real time learning; survey forecasts; term structure of forecasts
JEL Codes: C53; E37
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| prior beliefs (D80) | forecast accuracy (C53) |
| measurement errors (C20) | forecast accuracy (C53) |
| agents' learning processes (D83) | forecast accuracy (C53) |
| prior beliefs (D80) | forecast dispersion (C46) |
| differences in prior beliefs (D80) | cross-sectional dispersion in GDP growth forecasts (F62) |
| forecast horizon shortens (G17) | forecast errors (C53) |
| forecast dispersion for GDP growth (F62) | countercyclical component (E32) |
| inflation forecast dispersion (E31) | weakly countercyclical (E32) |