We study race in the labor market by sending fictitious resumes to help-wanted ads in Boston and Chicago newspapers. To manipulate perceived race, resumes are randomly assigned African-American- or White-sounding names. White names receive 50 percent more callbacks for interviews. Callbacks are also more responsive to resume quality for White names than for African-American ones. The racial gap is uniform across occupation, industry, and employer size. We also find little evidence that employers are inferring social class from the names. Differential treatment by race still appears to still be prominent in the U. S. labor market.
Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination
Related Resources
-
Implications of Cryptocurrency Energy Usage on Climate Change
Zhang, Dongna, Xihui Haviour Chen, Chi Keung Lau, and Bing Xu. 2023. “Implications of Cryptocurrency Energy Usage on Climate Change.” Technological Forecasting and Social Change 187: 122219.
- Authors with Diverse Backgrounds
-
How Much Does Racial Bias Affect Mortgage Lending? Evidence from Human and Algorithmic Credit Decisions
Bhutta, Neil and Hizmo, Aurel and Ringo, Daniel. 2022. “How Much Does Racial Bias Affect Mortgage Lending? Evidence from Human and Algorithmic Credit Decisions.” FEDS Working Paper No. 2022-67, SSRN
- Open Source Results
- Authors with Diverse Backgrounds