Whose Advantage
Do Minimum Wages Reduce Job Opportunities for Blacks?
David Neumark & Jyotsana Kala
NBER Working Paper, November 2024
Abstract:
We provide a comprehensive analysis of the effects of minimum wages on blacks, and on the relative impacts on blacks vs. whites. We study not only teenagers – the focus of much of the minimum wage-employment literature – but also other low-skill groups. We focus primarily on employment, which has been the prime concern with the minimum wage research literature. We find evidence that job loss effects from higher minimum wages are much more evident for blacks, and in contrast not very detectable for whites, and are often large enough to generate adverse effects on earnings. We supplement this work with additional analysis that distinguishes between effects of an individual’s race and the race composition of where they live. The extensive residential segregation by race in the United States raises the question of whether the more adverse effects of minimum wages on blacks are attributable to more adverse effects on black individuals, or more adverse effects on neighborhoods with large black populations. We find relatively little evidence of heterogeneity in effects across areas defined by the share black among residents.
Think Manager-Think Male Re-Examined: Race as a Moderator
Fiona Adjei Boateng & Madeline Heilman
Sex Roles, December 2024, Pages 1717-1734
Abstract:
Two studies examined the effects of race on the think manager-think male effect, which has shown men in general to be viewed more similarly to successful managers than women in general. The first study directly manipulated the race of the male or female target in the think manager-think-male framework and examined the effects on two key measures of agency -- competence and assertiveness -- as well as on communality. Results indicated that the differences in agency characterizations between men and successful managers and women and successful managers that are emblematic of the think-manager-think-male effect were not always evident. While the think manager-think male effect was observed for men and women “in general” as well as for men and women designated as White, it did not hold for Black and Asian targets, whose characterizations were influenced not only by gender stereotypes but also by racial stereotypes. Additionally, a potential “think manager-think female” effect, as indicated by greater overlap in communality ratings between women in general and successful managers than between men in general and successful managers held for targets who were White and Black, but not for those who were Asian. A follow-up study focused on potential implications of the findings from the first study and indicated that competence was believed to be more important than either communality or assertiveness, while communality was believed to be more important than assertiveness in determining managerial success. These results raise questions about the universality of the think-manager-think-male effect and the scope of its generalizability. These findings also add to the growing concern about the precision and application of gender bias research findings when attention is not paid to crucial intersecting identities such as race.
Automated speech recognition bias in personnel selection: The case of automatically scored job interviews
Louis Hickman et al.
Journal of Applied Psychology, forthcoming
Abstract:
Organizations, researchers, and software increasingly use automatic speech recognition (ASR) to transcribe speech to text. However, ASR can be less accurate for (i.e., biased against) certain demographic subgroups. This is concerning, given that the machine-learning (ML) models used to automatically score video interviews use ASR transcriptions of interviewee responses as inputs. To address these concerns, we investigate the extent of ASR bias and its effects in automatically scored interviews. Specifically, we compare the accuracy of ASR transcription for English as a second language (ESL) versus non-ESL interviewees, people of color (and Black interviewees separately) versus White interviewees, and male versus female interviewees. Then, we test whether ASR bias causes bias in ML model scores -- both in terms of differential convergent correlations (i.e., subgroup differences in correlations between observed and ML scores) and differential means (i.e., shifts in subgroup differences from observed to ML scores). To do so, we apply one human and four ASR transcription methods to two samples of mock video interviews (Ns = 1,014 and 414), and then we train and test models using these different transcripts to score multiple constructs. We observed significant bias in the commercial ASR services across nearly all comparisons, with the magnitude of bias differing across the ASR services. However, the transcription bias did not translate into meaningful measurement bias for the ML interview scores -- whether in terms of differential convergent correlations or means. We discuss what these results mean for the nature of bias, fairness, and validity of ML models for scoring verbal open-ended responses.
The Effects of Gender Integration on Men: Evidence from the U.S. Military
Kyle Greenberg, Melanie Wasserman & Anna Weber
NBER Working Paper, December 2024
Abstract:
Do men negatively respond when women first enter an occupation? We answer this question by studying the end of one of the final explicit occupational barriers to women in the U.S.: in 2016, the U.S. military opened all positions to women, including historically male-only combat occupations. We exploit the staggered integration of women into combat units to estimate the causal effects of the introduction of female colleagues on men’s job performance, behavior, and perceptions of workplace quality, using monthly administrative personnel records and rich survey responses. We find that integrating women into previously all-male units does not negatively affect men’s performance or behavioral outcomes, including retention, promotions, demotions, separations for misconduct, criminal charges, and medical conditions. Most of our results are precise enough to rule out small, detrimental effects. However, there is a wedge between men's perceptions and performance. The integration of women causes a negative shift in male soldiers' perceptions of workplace quality, with the effects driven by units integrated with a woman in a position of authority. We discuss how these findings shed light on the roots of occupational segregation by gender.
Emphasizing the Communal Demands of a Leader Role Makes Job Interviews Less Stressful for Women But Not More Successful
Christa Nater et al.
Sex Roles, November 2024, Pages 1506-1520
Abstract:
The cultural construal of leadership as masculine impedes women’s attainment of leader roles. This research examined whether adding feminine demands to a leader role relieved the greater stress experienced by women than men in a job interview for a leadership position and considered the processes that mediated women’s less favourable interview outcomes. In a hiring simulation, management students (N = 209; 112 women, 97 men) interviewed for a leader role framed by either stereotypically feminine or masculine role requirements. As shown by the stress biomarker salivary cortisol, the feminine role framing alleviated women’s, but not men’s, physiological stress response during the interview. However, under both masculine and feminine role framing, women, compared with men, reported lesser fit, expected poorer interview performance, appraised greater threat relative to challenge, and evaluated their performance less favourably, as did external raters. An additional vignette study (N = 305; 189 women, 111 men, 5 diverse) found that the feminine role framing increased the leader role’s communal demands but still conveyed strong agentic demands not different from those of the masculine role. In conclusion, although a feminine role framing alleviated women’s physiological stress response, it did not change their less favourable outcomes, as indicated by participants’ self-reports and others’ reports.
Why Aren't There More Minority Entrepreneurs?
Victor Bennett & David Robinson
NBER Working Paper, December 2024
Abstract:
We study racial and gender disparities in entrepreneurial activity through the lens of a Roy model, focusing on the distinction between idea generation and execution. Using nationally representative sur-vey data, we find that Black and Hispanic individuals demonstrate higher entrepreneurial intentions than white respondents. They are much less likely, however, to launch ventures once ideas are conceived. A critical determinant of this gap is differential reliance on social networks, which shapes both the likelihood of launching a business as well as the reasons for stopping. Variation in the strength of local, own-group entrepreneurship reveals that stronger networks enhance the relationship between social engagement and business formation. Also, as predicted by the model, access to social networks also predicts seeking capital. The interconnections between socialization and searching for capital are important for understanding-policies aimed at boosting rates of entrepreneurship in underrepresented groups.
Can Artificial Intelligence Improve Gender Equality? Evidence from a Natural Experiment
Leo Bao, Difang Huang & Chen Lin
Management Science, forthcoming
Abstract:
Gender discrimination in education hinders women’s representation in various fields. How can we create a gender-neutral learning environment when teachers’ gender composition and mindset are slow to change? Recent development in artificial intelligence (AI) provides a way to achieve this goal as engineers can make AI trainers gender neutral and not take gender-related information as input. We use data from a natural experiment in which such AI trainers replace some human teachers for a male-dominated strategic board game to test the effectiveness of AI training. The introduction of AI improves teaching outcomes for boys and girls and reduces the preexisting gender gap. Survey responses indicate that AI’s information advantage, friendly appearance, and interactive features helped students to learn faster, and class recordings suggest that AI trainers’ nondiscriminatory emotional status can explain the improvement in gender equality. We demonstrate AI’s potential in improving learning outcomes and promoting diversity, equity, and inclusion in analogous settings.
Overcoming Racial Gaps in School Preferences: The Effect of Peer Diversity on School Choice
Clemence Idoux & Viola Corradini
NBER Working Paper, November 2024
Abstract:
Differences in school choice by race contribute to school segregation and unequal access to effective schools. Conditional on test score and district of residence, Black and Hispanic families consistently choose schools with fewer white and Asian students, lower average achievement, and lower value-added. This paper combines unique survey data and administrative data from New York City to identify the determinants of racial disparities in school choice and shows that attending a more diverse middle school can mitigate racial choice gaps. Instrumental variable estimates show that middle school students exposed to more diverse peers apply to and enroll in high schools that are also more diverse. These effects particularly benefit Black and Hispanic students who, as a result, enroll in higher value-added high schools. A post-application survey of guardians of high school applicants suggests that most cross-race differences in choice stem from information gaps and homophily in preferences for school demographics. The survey results also reveal that exposure to diverse middle school peers reduces racial differences in choices by addressing these underlying determinants: it increases preferences for peer diversity and broadens the range of known school options.