Modeling Judgment in Macroeconomic Forecasts

Philip Hans Franses

doi:10.1007/s40953-021-00277-5

Abstract

Many 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.

Highlights

Macroeconomic forecasts are a key input to macroeconomic policies issued by governments and central banks
It is common practice to base macroeconomic forecasts on the outcome of an econometric model combined with expert judgment,1 or sometimes even to use no econometric model at all
The following models are considered No change forecast yi,T1+1 = yi,T1 AR(1) yi,T1+1 = i + iyi,T1 AR(1) with Factor, version 1 yi,T1+1 = i + iyi,T1 + iFi,T1 Where the parameters are estimated using ordinary least squares (OLS), and where Fi,t is computed per each country using the growth rates for ten countries with yj,t−1 which have the largest R2 in the lagged regression yi,t = i + iyj,t−1 + vi with j = 1,2, i − 1, i + 1, .., N = 52

Summary

Introduction

Macroeconomic forecasts are a key input to macroeconomic policies issued by governments and central banks. As an example, Franses et al (2011) show that literally all forecasts created by the Netherlands Bureau of Economic Policy Analysis (CPB) are judgmentally adjusted model-based forecasts. This methodology is illustrated for a simple time series model (as “the model”) and the outcome of a factor analysis of a range of

Results

Conclusion