Modeling Judgment in Macroeconomic Forecasts

Abstract

AbstractMany macroeconomic forecasts are the outcome of a judgmental adjustment to a forecast from an econometric model. The size, direction, and motivation of the adjustment are often unknown as usually only the final forecast is available. This is problematic in case an analyst wishes to learn from forecast errors, which could lead to improving the model, the judgment or both. This paper therefore proposes a formal method to include judgment, which makes the combined forecast reproducible. As an illustration, a forecast from a benchmark simple time series model is only modified when the value of a factor, estimated from a multitude of variables, exceeds a user-specified threshold. Simulations and empirical results for forecasting annual real GDP growth in 52 African countries provide an illustration.