Work in Progress:

Please email me at teastmon@ucsd.edu for a copy of my job market paper, as I am currently fielding additional data collection for the project. I have temporarily removed info from my website to preserve the integrity of that data collection.

 

“When Perfect is Detrimental to Diversity: The Hidden Cost of Strict Job Qualification Requirements.” (with Amanda Bonheur)

Abstract: Despite years of policy and revised corporate practice intended to correct inequality in the hiring process, application gaps persist for women and individuals from underrepresented racial minority groups. This study explores whether it is possible to narrow this application gap and promote diversity in the applicant pool by modifying the language around qualification requirements in job ads. We do so using a large-scale, “reverse audit study” field experiment where we randomize the content of job ads and observe job seeker behavior. Specifically, we established a non-profit recruiting firm to act as an intermediary in the job search process. This firm reposts real job ads and collects information from job seekers interested in applying. We randomize whether we encourage people to apply even if they don’t meet all of the listed qualifications and whether we inform them that companies routinely hire individuals who do not have all qualifications. This is a light touch intervention that may change perceptions of the hiring process and nudge more capable people into applying. We hypothesize that wording changes will have larger impacts on women, individuals from underrepresented racial minority groups, and people with non-traditional employment backgrounds. (Pilot results will be available soon.)

 

“Effect Heterogeneity and Optimal Policy: Getting Welfare Added from Teacher Value Added” (with Julian Betts, Nathan Mather, and Michael Ricks)

Abstract: Though ubiquitous in empirical analyses, mean-oriented statistics may not fully inform policy and welfare considerations when programs have heterogeneous effects or when policy makers have distributional objectives. In this paper we formally articulate when estimating heterogeneity is necessary to determine welfare impacts and quantify the importance of heterogeneity in an enormous public service provision problem: the allocation of teachers to elementary school classes. Using data from the San Diego Unified School District we estimate heterogeneity in teacher value added over the student achievement distribution. Because over 68% of teachers have economically meaningful comparative advantage across student types, a social planner can generate achievement gains 70-120% larger through reallocations within (across) schools using information about heterogeneity than with standard value added. Welfare gains from considering heterogeneity are even larger when policymakers prefer to prioritize achievement gains to lower (or higher) achieving students, suggesting that using information about effect heterogeneity might improve a broad range of public programs—both on grounds of average impacts and distributional goals.