Do Comparisons of Fictional Applicants Measure Discrimination When Search Externalities are Present? Evidence from Existing Experiments
Bibliographic Data
| ID | 9705862 |
|---|---|
| Authors | David C Phillips (University of Notre Dame, corresponding author) |
| Year | 2019 |
| Publication date | 2019-01-08 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | The Economic Journal (JOURNAL) |
| Journal identifiers | ISSN: 0013-0133 • E-ISSN: 1468-0297 |
| Publisher | Oxford University Press (OUP) (PUBLISHER) |
| DOI | 10.1111/ecoj.12628 |
| OpenAlex | W2883829628 |
| Language | EN |
| Citations received | 15 |
| References cited | 39 |
Researchers commonly measure discrimination by comparing responses to multiple fictional applicants sent to the same vacancy. I find evidence that these applications interact. Using data from several existing experiments, I find that applicants randomly assigned to compete against higher quality applicant pools receive more callbacks. In the presence of such spillovers, many experiments confound discrimination against an individual's characteristics with employers’ responses to the composition of the applicant pool. Under one reasonable set of assumptions, adjusting for applicant pool composition increases measured discrimination by 30% on average. Avoiding experimental designs that stratify treatment assignment by vacancy can eliminate such confounding
Actuarial science · Callback · Confounding · Data mining · Econometrics · Economics · Externality · Measure (data warehouse · Microeconomics · Quality (philosophy · Set (abstract data type · Statistics · Computer Science · Game Theory and Voting Systems · Mathematics · Media Influence and Politics · Names, Identity, and Discrimination Research · Psychology · Social Psychology
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| Unique citing works | 15 |
|---|---|
| Citations per year | 1,88 |
| Citation span | 2018 - 2026 (9) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 14 |