Yesterday, on Thursday May 11th, I have attended the New England Study Group seminar hosted by the Federal Reserve Bank of Boston's Research Department. Laura Gee from Tufts University presented her research with the title "The More You Know: Information Effects on Job Application Rates in a Large Field Experiment".
At her research, Laura uses LinkedIn to conduct a large scale field experiment with about 2.3 million real world job seekers. The results of this experiment show that providing information about the number of previous applicants causes more people to apply to a job posting and that this effect is greater for female applicants. These findings are especially relevant for firms looking to increase the number of female applicants. In short, this paper illustrates a low cost, light touch intervention to reduce the occupation gender gap. Specifically Laura finds that showing a job seeker the number of previous applicants for a job posting increases the likelihood of application by 0.6-1.9%. Since millions of job seekers view job postings each week on websites like LinkedIn, this translates to an increase in the number of applications of at least a thousand per day. Laura also finds that the relative number of previous applicants shown does not lead to an increase or decrease in the applications when the relative number shown is high. She interprets this finding as evidence that the dominant effect applicants exhibit is neither competition avoidance nor herding behavior. She thus concludes that the overall positive treatment effect can be explained by models of ambiguity aversion, especially the larger effect observed for female job seekers. Overall, the results indicate that this intervention should not be welfare dis-enhancing since it increases the thickness of the female applicant pool to jobs that particularly need more female applicants.
At her research, Laura uses LinkedIn to conduct a large scale field experiment with about 2.3 million real world job seekers. The results of this experiment show that providing information about the number of previous applicants causes more people to apply to a job posting and that this effect is greater for female applicants. These findings are especially relevant for firms looking to increase the number of female applicants. In short, this paper illustrates a low cost, light touch intervention to reduce the occupation gender gap. Specifically Laura finds that showing a job seeker the number of previous applicants for a job posting increases the likelihood of application by 0.6-1.9%. Since millions of job seekers view job postings each week on websites like LinkedIn, this translates to an increase in the number of applications of at least a thousand per day. Laura also finds that the relative number of previous applicants shown does not lead to an increase or decrease in the applications when the relative number shown is high. She interprets this finding as evidence that the dominant effect applicants exhibit is neither competition avoidance nor herding behavior. She thus concludes that the overall positive treatment effect can be explained by models of ambiguity aversion, especially the larger effect observed for female job seekers. Overall, the results indicate that this intervention should not be welfare dis-enhancing since it increases the thickness of the female applicant pool to jobs that particularly need more female applicants.
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