We study the relationships between ageist stereotypes – as reflected in the language used in job ads – and age discrimination in hiring, exploiting the text of job ads and differences in callbacks to older and younger job applicants from a resume (correspondence study) field experiment.
We develop and implement methods to explore the role of stereotypes in hiring discrimination using the text of job ads, and apply this method to evidence on age discrimination. We make three contributions. First, we develop techniques that leverage machine learning and textual analysis to analyze the text data in job ads from a large-scale field experiment on discrimination. Second, we use these techniques to produce evidence on which age-related stereotypes that appear in job ads are associated with an experimental measure of hiring discrimination against older workers – the first evidence we know of that can establish relationships between age-related stereotypes and actual employer behavior. Third, our analysis provides evidence on whether employers with less intent to hire older workers – as captured in our experimental results – use ageist language in their ads.
We find evidence that language related to stereotypes of older workers sometimes predicts discrimination against older workers. For men, our evidence points to age stereotypes about all three categories we consider – health, personality, and skill – predicting age discrimination, and for women, age stereotypes about personality. In general, the evidence is much stronger for men, and our results for men are quite consistent with the industrial psychology literature on age stereotypes.
Chosen excerpts by Job Market Monitor. Read the whole story @ Older Workers Need Not Apply? Ageist Language in Job Ads and Age Discrimination in Hiring | IZA – Institute of Labor Economics