Seminars

David Neumark 교수님의 세미나가 있을 예정입니다. 

* 주관: 서울대학교 경제학부, 경제연구소 한국경제혁신센터, SSK, BK21

* 본 세미나는 졸업요건(2022-2학기) 및 BK21+(2022-2학기) 세미나 참석으로 인정됩니다.

- 세미나 참석인정을 원하는 학생은 세미나 종료 후 참석자 명단을 작성해주시기 바랍니다.

Abstract: Correspondence studies have found evidence of age discrimination in callback rates for older workers, but less is known about whether job advertisements can themselves shape the age composition of the applicant pool. We construct job ads for administrative assistant, retail, and security guard jobs, using language from real job ads collected in a prior large-scale correspondence study (Neumark et al., 2019a). We modify the job-ad language to randomly vary whether or not the job ad includes ageist language regarding age-related stereotypes. Our main analysis relies on machine learning methods to design job ads based on the semantic similarity between phrases in job ads and age-related stereotypes. In contrast to a correspondence study in which job searchers are artificial and researchers study the responses of real employers, in our
research the job ads are artificial and we study the responses of real job searchers. 
We find that job-ad language related to ageist stereotypes, even when the language is not blatantly or specifically age-related, deters older workers from applying for jobs. The change in the age distribution of applicants is large, with significant declines in the average and median age, the 75th percentile of the age distribution, and the share of applicants over 40. Based on these estimates and those from the correspondence study, and the fact that we use real-world ageist jobad language, we conclude that job-ad language that deters older workers from applying for jobs can have roughly as large an impact on hiring of older workers as direct age discrimination in hiring.


* 주관: 서울대학교 경제학부, 경제연구소 한국경제혁신센터, SSK, BK21