On the efficacy of the wisdom of crowds to forecast economic indicators

• Published in: The European physical journal. B, Condensed matter physics Vol. 96; no. 1
• Main Authors: Neto, Nilton S. Siqueira, Fontanari, José F.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2023; Springer; Springer Nature B.V
• Subjects: Accuracy; Agglomeration; Analysis; Complex Systems; Condensed Matter Physics; Economic analysis; Economic forecasting; Economic indicators; Errors; Estimates; Federal Reserve banks; Fluid- and Aerodynamics; Forecasts and trends; Indicators; Mean; Median (statistics); Physics; Physics and Astronomy; Regular Article - Statistical and Nonlinear Physics; Solid State Physics; Statistics; Surveys
• ISSN: 1434-6028; 1434-6036
• DOI: 10.1140/epjb/s10051-023-00482-6

The interest in the wisdom of crowds stems mainly from the possibility of combining independent forecasts from experts in the hope that many expert minds are better than a few. Hence the relevant subject of study nowadays is the Vox Expertorum rather than Galton’s original Vox Populi . Here we use the Federal Reserve Bank of Philadelphia’s Survey of Professional Forecasters to analyze 15455 forecasting contests to predict a variety of economic indicators. We find that the median has advantages over the mean as a method to combine the experts’ estimates: the odds that the crowd beats all participants of a forecasting contest is 0.015 when the aggregation is given by the mean and 0.026 when it is given by the median. Both aggregation methods yield a 20% error on the average, which must be contrasted with the expected error of a randomly selected forecaster, which is about 22%. We conclude that selective attention is the most likely explanation for the mysterious high accuracy of the crowd reported in the literature. This conclusion is strengthened by the rebuff of the claim that this high accuracy results from the cancellation of the participants’ errors: we find no meaningful correlation between the asymmetry of the distribution of the individuals’ estimates and the collective error. Graphical abstract