{"title":"Words matter: Experimental evidence from job applications","authors":"","doi":"10.1016/j.jebo.2024.06.013","DOIUrl":null,"url":null,"abstract":"<div><p>If women are more sensitive to listed qualifications in job ads, does lowering the bar draw in relatively more women and increase diversity in the applicant pool? We examine this question by randomizing 60,000 viewers into one of two job ad versions for over 600 corporate jobs at Uber, where the treatment removed optional and superfluous qualifications. There are two main findings. First, job seekers of both genders respond to qualifications: applications increase by 7%, owing to similar increases in the number of applications from men and women. Second, reducing the qualifications impacts the type of individual who chooses to apply differently by gender. Reducing the qualifications draws in less skilled women and causes an outflow of some highly skilled women. Conversely, the treatment draws in men from across the skill distribution, including the upper end. We find gender differences in application behavior and explore potential mechanisms in a separate, large-scale survey using the RAND American Life Panel. These results highlight that sensitivity to listed requirements is complex, and simply lowering the qualifications in job postings is not guaranteed to increase applicant diversity.</p></div>","PeriodicalId":48409,"journal":{"name":"Journal of Economic Behavior & Organization","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0167268124002312/pdfft?md5=e873dab8749072cf5d33ab8de3eba383&pid=1-s2.0-S0167268124002312-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economic Behavior & Organization","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167268124002312","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
If women are more sensitive to listed qualifications in job ads, does lowering the bar draw in relatively more women and increase diversity in the applicant pool? We examine this question by randomizing 60,000 viewers into one of two job ad versions for over 600 corporate jobs at Uber, where the treatment removed optional and superfluous qualifications. There are two main findings. First, job seekers of both genders respond to qualifications: applications increase by 7%, owing to similar increases in the number of applications from men and women. Second, reducing the qualifications impacts the type of individual who chooses to apply differently by gender. Reducing the qualifications draws in less skilled women and causes an outflow of some highly skilled women. Conversely, the treatment draws in men from across the skill distribution, including the upper end. We find gender differences in application behavior and explore potential mechanisms in a separate, large-scale survey using the RAND American Life Panel. These results highlight that sensitivity to listed requirements is complex, and simply lowering the qualifications in job postings is not guaranteed to increase applicant diversity.
期刊介绍:
The Journal of Economic Behavior and Organization is devoted to theoretical and empirical research concerning economic decision, organization and behavior and to economic change in all its aspects. Its specific purposes are to foster an improved understanding of how human cognitive, computational and informational characteristics influence the working of economic organizations and market economies and how an economy structural features lead to various types of micro and macro behavior, to changing patterns of development and to institutional evolution. Research with these purposes that explore the interrelations of economics with other disciplines such as biology, psychology, law, anthropology, sociology and mathematics is particularly welcome.