Table of Links

Abstract

Background

Data

Methodology

Results

Discussion and Conclusion, and References

A Appendix Tables and Figures

5 Discussion and Conclusion

In this paper, we examine whether the gender of the coach and artist matters when it comes to selecting the performance in the blind audition stage in the Voice TV show. Results provide strong evidence that gender matters and I show that coaches choose other gender artists 12 percent more when they hear similar performances in the audition. The results are robust with many variations, such as coach and artistspecific covariates. Under the interpretation of opposite-gender bias, the results would be due to male and/or female coaches being either too lenient to opposite-gender artists, being too tough on own-gender artists, or both.

Relatedly, a potential mechanism through which opposite-gender interaction cause statistically significant gender bias could be employers hiring for female-dominated occupations showing a preference for male applicants (Weichselbaumer, 2004; Protsch, 2021). However, Weichselbaumer (2004) and Protsch (2021)’s research also found that employers preferred male applicants in male-dominated occupations. Still, because of data limitations, they do not observe the gender of the recruiter. Others who do not observe what I observe in my work found that employers prefer male applicants in male-dominated occupations and female applicants in female-dominated occupations (Campero and Fernandez, 2018; Benard and Correll, 2010; Glick et al., 1988; Ridgeway and Correll, 2004). These works provide robust evidence of gender bias in hiring. Still, we cannot distinguish whether it is an opposite-gender or own-gender bias hiring since the gender of the decision-makers is unobservable or decisions are made collectively. In my setting, I observe the gender of the coach and the coach’s individual choice in selecting the artists. Therefore I incorporate this gender composition feature into my setting to address whether the coach changes their behavior based on the gender composition in the team. For example, If one coach’s team is dominated by one gender, would the coach shift behavior during the audition and select an artist from another gender, a minority gender?

I conduct a heterogeneity analysis assessing the effect of different gender compositions in the team on the likelihood of being selected. To do so, I took advantage of the fact that the sample I used includes both selection of male and female coaches in the blind audition stages and if the artist ended up being in the team of the selected coach. Additionally, the other advantage of the sample is substantial variations in gender composition in each team, including both male-dominated and female-dominated settings. Typically, we observe only one type of setting, where the firm is femaledominated or male-dominated. Leveraging this variation in the gender composition, I estimate the heterogeneous effect of gender bias for male and female coaches. I found that male artists have an advantage over female artists in a male-dominated team when the coach is male. Likewise, women have an advantage over men in a female-dominated team. When the coach is female, we can see opposite scenarios. Female coaches tend to choose women over men in male-dominated teams and men over women in the female-dominated team. This difference is partially statistically significant, but the magnitude remains consistent.

The literature provides robust support for a hypothesis on group formation dynamics, which is different for male and female leaders. One study of bias in other contexts suggests that men might not respond favorably to the presence of gender diversity, particularly in domains that men have historically dominated. Also, genderrelated issues were most likely to be raised in groups where women are a minority or where the female is a leader (Crocker and McGraw, 1984). In addition, there is substantial evidence that women in team formation care about equality, men care about efficiency, and men consider male or female dominance in the team as more efficient. More directly, Kuhn and Villeval (2014) found that women respond differently to alternative rules for team formation in a manner consistent with advantageous inequity aversion. In contrast, men show greater responsiveness to efficiency gains associated with team production, meaning that when forming a team, men make their selections based on who will be the most efficient rather than on the grounds of gender equality. Overall, our findings indicate that gender composition and the gender of the decisionmaker are important determinants in the hiring process. While it is difficult to know if these findings extend to other industries, these results corroborate the debate over gender discrimination in the hiring process.

In conclusion, the results add evidence to a growing literature testing own or opposite gender bias in decision-making. This finding provides insights into the extent to which situational factors work to mitigate or exacerbate gender disparities in the hiring process. I show strong evidence of the heterogeneity in gender bias from gender composition in the team. This evidence suggests that the selection process is primarily rooted in the female and male recruiters’ behavioral preferences of inequality or efficiency. In addition, the findings offer a new perspective to enrich past research on gender discrimination, shedding light on the instances of gender bias variation by the gender of the decision maker and team gender composition.

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