Cross‐Check of Economic Forecasts

Policymakers cross‐check their projections for multiple variables and forecast horizons with experts' forecasts or satellite models. This paper proposes a set of quantitative metrics that can be used to summarize the overall discrepancy between two forecasting models jointly across variables and forecasting horizons. The methodologies can be applied both when only point forecasts are available and when the full predictive densities are known. They also allow to take into account the policymaker loss function, by assigning different weights to variables or horizons. We illustrate the usefulness of our measures when comparing the forecasts from the Survey of Professional Forecasters, the Tealbook, a medium scale Bayesian VAR, and a medium scale dynamic stochastic general equilibrium (DSGE) model for the US data. We find that the forecasts substantially depart ahead of and during recessions, resulting in our measures spiking.