Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?

Professional forecasters can rely on an econometric model to create their forecasts. It is usually unknown to what extent they adjust an econometric model‐based forecast. In this paper we show, while making just two simple assumptions, that it is possible to estimate the persistence and variance of the deviation of their forecasts from forecasts from an econometric model. A key feature of the data that facilitates our estimates is that we have forecast updates for the same forecast target. An illustration to consensus forecasters who give forecasts for GDP growth, inflation and unemployment for a range of countries and years suggests that the more a forecaster deviates from a prediction from an econometric model, the less accurate are the forecasts

Does More Expert Adjustment Associate with Less Accurate Professional Forecasts?

Professional forecasters can rely on an econometric model to create their forecasts. It is usually unknown to what extent they adjust an econometric model‐based forecast. In this paper we show, while making just two simple assumptions, that it is possible to estimate the persistence and variance of the deviation of their forecasts from forecasts from an econometric model. A key feature of the data that facilitates our estimates is that we have forecast updates for the same forecast target. An illustration to consensus forecasters who give forecasts for GDP growth, inflation and unemployment for a range of countries and years suggests that the more a forecaster deviates from a prediction from an econometric model, the less accurate are the forecasts

Evaluating heterogeneous forecasts for vintages of macroeconomic variables

There are various reasons why professional forecasters may disagree in their quotes for macroeconomic variables. One reason is that they target at different vintages of the data. We propose a novel method to test forecast bias in case of such heterogeneity. The method is based on Symbolic Regression, where the variables of interest become interval variables. We associate the interval containing the vintages of data with the intervals of the forecasts. An illustration to 18 years of forecasts for annual USA real GDP growth, given by the Consensus Economics forecasters, shows the relevance of the method