Mixed-gender analyst team and accuracy of earnings forecast: evidence from China

ABSTRACT

We examine the effect of analyst teams’ gender diversity on the accuracy of their earnings forecasts. We find that, compared with single-gender analyst teams, mixed-gender analyst teams generate more accurate earnings forecasts and have less optimism bias. The desirable effect of mixed-gender analyst teams on the accuracy of earnings forecasts is more significant in the highly educated or experienced analyst teams, in smaller brokerages with fewer star analysts, and in firms audited by non-Big -Four accounting firms or with less analyst coverage. Further studies find that, female analysts who work in teams produce more accurate earnings forecasts than they work individually. In addition, when a single-gender analyst team transforms into a mixed-gender analyst team, its reports have more accuracy and less optimism bias than before, and vice versa.

KEYWORDS:

• Analyst team
• gender diversity
• forecast accuracy
• optimism bias

JEL CLASSIFICATION:

• G41
• Z13

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by National Natural Science Foundation of China under Grant 71572189 and 71102163, and Shanghai philosophy and social science project grant 2022BGL009