Gender Diversity and Consensus Forecasts

Abstract

We analyze the benefits of gender diversity among sell-side analysts. Consensus forecast accuracy is higher for firms followed by more diverse analysts, as measured by the number and fraction of female analysts, after controlling for analyst quality. Similarly, increases in gender diversity are followed by reductions in consensus forecast errors. Consensus forecast accuracy improves more when there is a greater disagreement between male and female analysts, indicating that the wisdom of the crowds mechanism underlies the impact of gender diversity on consensus forecast accuracy. Additionally, we find that gender diversity enhances individual analysts' forecast accuracy, which further improves the accuracy of the consensus forecast. Investors do not appear to recognize the greater accuracy of consensus forecasts produced by more diverse analysts, as they do not react more strongly to earnings surprises associated with these forecasts.

Keywords: Diversity, Gender, Analysts, Consensus Forecast JEL: D80, G14, G24, G30, J16, M14

JEL Classification: D80, G14, G24, G30, J16, M14