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We design and implement a large-scale field experiment - a resume correspondence study - to address a number of potential limitations of existing field experiments testing for age discrimination, which may bias their results. One limitation that may bias these studies towards finding discrimination is the practice of giving older and younger applicants similar experience in the job to which they are applying, to make them "otherwise comparable." The second limitation arises because greater unobserved differences in human capital investment of older applicants may bias existing field experiments against finding age discrimination. We also study ages closer to retirement than in past studies, and use a richer set of job profiles for older workers to test for differences associated with transitions to less demanding jobs ("bridge jobs") at older ages. Based on evidence from over 40,000 job applications, we find robust evidence of age discrimination in hiring against older women. But we find that there is considerably less evidence of age discrimination against men after correcting for the potential biases this study addresses.
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We provide evidence from a field experiment in all 50 states on age discrimination in hiring for retail sales jobs. We relate measured age discrimination - the difference in callback rates between old and young applicants - to state variation in anti-discrimination laws protecting older workers. Anti-discrimination laws could boost hiring, although they could have the unintended consequence of deterring hiring if their main effect is to increase termination costs. We find some evidence that there is less discrimination against older men and women in states where age discrimination law allows larger damages, and some evidence that there is lower discrimination against older women in states where disability discrimination law allows larger damages. But this evidence is not robust to all of the estimations we consider. However, we reach a robust conclusion that stronger or broader laws protecting older workers from discrimination do not have the unintended consequence of deterring their hiring.
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We provide evidence from a field experiment in all 50 states on age discrimination in hiring for retail sales jobs. We relate measured age discrimination - the difference in callback rates between old and young applicants - to state variation in anti-discrimination laws protecting older workers. Anti-discrimination laws could boost hiring, although they could have the unintended consequence of deterring hiring if their main effect is to increase termination costs. We find some evidence that there is less discrimination against older men and women in states where age discrimination law allows larger damages, and some evidence that there is lower discrimination against older women in states where disability discrimination law allows larger damages. But this evidence is not robust to all of the estimations we consider. However, we reach a robust conclusion that stronger or broader laws protecting older workers from discrimination do not have the unintended consequence of deterring their hiring.
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We design and implement a large-scale field experiment - a resume correspondence study - to address a number of potential limitations of existing field experiments testing for age discrimination, which may bias their results. One limitation that may bias these studies towards finding discrimination is the practice of giving older and younger applicants similar experience in the job to which they are applying, making them "otherwise comparable." The second limitation arises because greater unobserved differences in human capital investment of older applicants may bias existing field experiments against finding age discrimination. We also study ages closer to retirement than in past studies, and use a richer set of job profiles for older workers to test for differences associated with transitions to less demanding jobs ("bridge jobs") at older ages. Based on evidence from over 40,000 job applications, we find robust evidence of age discrimination in hiring against older women, especially those near retirement age. But we find that there is considerably less evidence of age discrimination against men after correcting for the potential biases this study addresses.
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We provide an overview of research that indicates that older women face unique challenges and opportunities with respect to work, retirement, Social Security, and age discrimination law. We present estimates of poverty by age and sex, showing that poverty increases with age for women due to older women often outliving their spouses and becoming widowed. We discuss research that shows that women benefit more than men from working longer. We then note that older women face intersectional discrimination that can unfortunately be a barrier to older women working longer. We detail how older women often "fall between the cracks" of the Age Discrimination in Employment Act and Title VII of the Civil Rights Act and are thus not well protected against this intersectional discrimination. As a final example of how women face different circumstances, we summarize research on how older women were differentially negatively impacted by the elimination of Social Security's Retirement Earnings.
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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 (Neumark, Burn, and Button, 2019). Our analysis uses methods from computational linguistics and machine learning to directly identify, in a field-experiment setting, ageist stereotypes that underlie age discrimination in hiring. The methods we develop provide a framework for applied researchers analyzing textual data, highlighting the usefulness of various computer science techniques for empirical economics research. 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.
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