Prospects for the Minority
Employer Neighborhoods and Racial Discrimination
Amanda Agan & Sonja Starr
NBER Working Paper, November 2020
Abstract:
Using a large field experiment, we show that racial composition of employer neighborhoods predicts employment discrimination patterns in a direction suggesting in-group bias. Our data also show racial disparities in the geographic distribution of job postings. Simulations illustrate how these patterns combine to shape disparities. When jobs are located far from Black neighborhoods, Black applicants are doubly disadvantaged: discrimination patterns disfavor them, and they have fewer nearby opportunities. Finally, building on prior work on Ban-the-Box laws, we show that employers in less Black neighborhoods appear much likelier to stereotype Black applicants as potentially criminal when they lack criminal record information.
The Black-White Gap in Noncognitive Skills among Elementary School Children
Todd Elder & Yuqing Zhou
American Economic Journal: Applied Economics, January 2021, Pages 105-132
Abstract:
Using two nationally representative datasets, we find large differences between Black and White children in teacher-reported measures of noncognitive skills. We show that teacher reports understate true Black-White skill gaps because of reference bias: teachers appear to rate children relative to others in the same school, and Black students have lower-skilled classmates on average than do White students. We pursue three approaches to addressing these reference biases. Each approach nearly doubles the estimated Black-White gaps in noncognitive skills, to roughly 0.9 standard deviations in third grade.
When Does Inequality Grow? A Seasonal Analysis of Racial/Ethnic Disparities in Learning From Kindergarten Through Eighth Grade
Megan Kuhfeld, Dennis Condron & Doug Downey
Educational Researcher, forthcoming
Abstract:
What role does schooling play in the development of racial/ethnic inequalities in academic skills? Seasonal learning studies, which allow researchers to compare the growth of achievement gaps when school is in versus out of session, provide important evidence regarding whether schools reduce, reproduce, or exacerbate educational inequalities. Most studies that have compared the growth of achievement gaps when school is in versus out of session have been restricted to the early grades. In this study, we examine seasonal patterns of racial/ethnic achievement gaps using test scores from over 2.5 million kindergarten to eighth-grade students. Following three different cohorts of students from 2015 to 2018, we find that Black-White achievement gaps widen during school periods and shrink during summers, whereas Asian students generally pull ahead of White students at a faster rate during summers. At the same time, we find that disparities observed among older students are largely in place among kindergartners. Our results imply that although schooling does have disparate impacts on the learning trajectories of students, schools play less of a role in widening racial/ethnic achievement gaps than children’s prekindergarten environments.
Discrimination in the Venture Capital Industry: Evidence from Two Randomized Controlled Trials
Ye Zhang
Columbia University Working Paper, December 2020
Abstract:
This paper examines discrimination based on startup founders’ gender, race, and age by early-stage investors, using two randomized controlled trials with real venture capitalists. The first experiment invites U.S. investors to evaluate multiple randomly generated startup profiles, which they know to be hypothetical, in order to be matched with real, high-quality startups from collaborating incubators. Investors can also donate money to randomly displayed startup teams to show their anonymous support during the COVID-19 pandemic. The second experiment sends hypothetical pitch emails with randomized startups’ information to global venture capitalists and compares their email responses by utilizing a new email technology that tracks investors’ detailed information acquisition behaviors. I find three main results: (i) Investors are biased towards female, Asian, and older founders of relatively low quality startups; while biased against female, Asian, and older founders of relatively high quality startups. (ii) These two experiments identify multiple coexisting sources of bias. Specifically, statistical discrimination is an important reason for “anti-minority” investors’ contact and investment decisions, which was proved by a newly developed consistent decision-based heterogeneous effect estimator. (iii) There was a temporary, stronger bias against Asian founders during the COVID-19 outbreak, which started to fade in April 2020.
Using the shifting standards model of stereotype‐based judgments to examine the impact of race on compensation decisions
Matthew Weeks Kelly Weeks & Emily Watkins
Journal of Applied Social Psychology, forthcoming
Abstract:
The Shifting Standards Model (SSM) of stereotypic judgments is presented as a model of implicit bias that produces a psychological mechanism contributing to continued racial wage disparities. The SSM is used to explain race‐based differences in subjective evaluations of compensation decisions. We report three experimental studies in which research participants made compensation decisions for either a White or Black employee. Across three studies, participants judged a Black employee's raise as subjectively better than a comparably described White employee's raise. Participants who work in Human Resources fields (Study 3) and those with experience making compensation decisions (Study 2) were as likely as other participants to show evidence of the shifting standards effect. The findings are discussed in the context of individual implicit biases contributing to continued wage disparities and potential organizational practices to ameliorate these influences.
Black and White: Access to Capital among Minority-Owned Startups
Robert Fairlie, Alicia Robb & David Robinson
NBER Working Paper, November 2020
Abstract:
We use confidential and restricted-access data from the Kauffman Firm Survey and matched administrative data on credit scores to explore racial disparities in access to capital for new business ventures. The novel results on racial inequality in startup financing indicate that black-owned startups start smaller and stay smaller over the entire first eight years of their existence. Black startups face more difficulty in raising external capital, especially external debt. We find that disparities in credit-worthiness constrain black entreprenuers, but perceptions of treatment by banks also hold them back. Black entrepreneurs apply for loans less often than white entrepreneurs largely because they expect to be denied credit, even when they have a good credit history and in settings where strong local banks favor new business development.
What Explains the Race Gap in Teacher Performance Ratings? Evidence From Chicago Public Schools
Matthew Steinberg & Lauren Sartain
Educational Evaluation and Policy Analysis, forthcoming
Abstract:
Racial gaps in teacher performance ratings have emerged nationwide across newly implemented educator evaluation systems. Using Chicago Public Schools data, we quantify the magnitude of the race gap in teachers’ classroom observation scores, examine its determinants, and describe the potential implications for teacher diversity. Between-school differences explain most of the race gap and within-school classroom-level differences - poverty, incoming achievement, and prior-year misconduct of a teacher’s students - explain the remainder of the race gap. Teachers’ value-added scores explain none of the race gap. Leveraging within-teacher variation in the teacher-evaluator race match, we find that racial mismatch does not influence observation scores. Adjusting observation scores for classroom and school context will generate more equitable ratings of teacher performance and mitigate potential adverse consequences for teacher diversity.
How white is the global elite? An analysis of race, gender and network structure
Kevin Young et al.
Global Networks, forthcoming
Abstract:
Research on elites often utilizes network analysis to describe and analyse the interrelationships among elites and how their prominence varies by demographic characteristics. We examine the diversity of global elites through an analysis of the board members of large corporations, think tanks, international organizations, and transnational policy planning groups. Using new data, we provide the first descriptive picture of global elite networks in terms of race and gender. We also test the ‘core-periphery’ hypothesis, which predicts that as non‐whites and women achieve elite positions they will be marginalized to the periphery of elite networks, while the core remains significantly more white and male. We find consistent evidence for the core-periphery hypothesis across a range of empirical tests, from simple k‐coring to various core-periphery models. Most groups decline in their representation in the core, and this includes white women. White men are the only group that increases in representation in the core compared to the periphery.