Data, Code, and Algorithm for: "How Do You Say Your Name? Difficult-To-Pronounce Names and Labor Market Outcomes"
Principal Investigator(s): View help for Principal Investigator(s) Qi Ge, Vassar College; Stephen Wu, Hamilton College
Version: View help for Version V1
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Project Citation:
Ge, Qi, and Wu, Stephen. Data, Code, and Algorithm for: “How Do You Say Your Name? Difficult-To-Pronounce Names and Labor Market Outcomes.” Nashville, TN: American Economic Association [publisher], 2024. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-10-22. https://doi.org/10.3886/E188001V1
Project Description
Summary:
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We test for labor market discrimination based on an understudied characteristic: name fluency. Analysis of recent economics PhD job candidates indicates that name difficulty is negatively related to the probability of landing an academic or tenure track position and research productivity of initial institutional placement. Discrimination due to name fluency is also found using experimental data from prior audit studies. Within samples of African-Americans (Bertrand and Mullainathan 2004) and ethnic immigrants (Oreopoulos 2011), job applicants with less fluent names experience lower callback rates, and name complexity explains roughly between 10 and 50 percent of ethnic name penalties. The results are primarily driven by candidates with weaker resumes, suggesting that cognitive biases may contribute to the penalty of having a difficult-to-pronounce name.
Scope of Project
JEL Classification:
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A11 Role of Economics; Role of Economists; Market for Economists
J44 Professional Labor Markets; Occupational Licensing
A11 Role of Economics; Role of Economists; Market for Economists
J44 Professional Labor Markets; Occupational Licensing
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