1 Introduction
How labor markets reward education, work experience, and other forms of human
capital is of fundamental interest in labor economics and the economic s of education
(e.g., Autor and Houseman [2010], Pallais [2014]). Similarly, the role of di scr i mi n a-
tion in labor markets is a key concern for both policy makers and economists (e.g.,
Altonji and Bl ank [1999], Lang and Lehmann [2012]). Correspondence audit stu d-
ies, including resume audit studies, have b ec om e powerful tools to answer questions
in both domains.
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These s t ud i es have generated a rich set of findings on discrim-
ination in employment (e.g., Bertrand and Mullainathan [2004]), real estate and
housing (e.g., Hanson and Hawley [2011], Ewens et al. [2014]), retail (e.g., Pope and
Sydnor [2011], Zussman [2013]), and other settings (see Bertrand and Duflo [2016]).
More recently, resume audit studies have been used to inves t igat e how employers
respond to other characteristics of job candidates, including unemployment spells
[Kroft et al., 2013, Eriksson and Rooth, 2014, Nunley et al., 2017], for-profit college
credentials [Darolia et al., 2015, De mi ng et al., 2016], college selectivity [Gaddis,
2015], and military service [Kleykamp, 2009].
Despite the strengths of this workhorse methodology, however , resume audit
studies are subject to two major concerns. First, they use deception, generally
considered problematic within economics [Ortmann and Hertwig, 2002, Hamermesh,
2012]. Employers in resume audit studies waste time evaluating fake resumes and
pursuing non-existent candidat es . If fake resumes system at ic al ly di↵er from real
resumes, employers could become wary of ce r tai n types of resumes sent out by
researchers, harming both the validity of future research and real job seekers whose
resumes are similar to those sent by researchers. These concerns about deception
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Resume audit studies send otherwise identical resumes, with only minor di↵erences a ssociated
with a treatment (e.g., di↵erent names associated with di↵erent races), to prospective employers and
measure the rate at which candidates are called back by t h o se employers (henceforth the “callback
rate”). These studies were brought into the mainstream of economics literature by Bertrand and
Mullainathan [2004]. By co mp a ri n g callback rates across groups (e.g., those with white names
to those w it h minority names), researchers can identify the existence of discrimination. Resume
audit stu d i es were designed to improve upon traditional audit studies of the labor market, which
involved sending matched p a irs of candidates (e.g., otherwise similar study c o n fed era t es of di↵erent
races) to apply for the same job and measure whether the callback rate di↵ered by race. These
traditional audit studies were challenged on empirical grounds for not being double-bli n d [Turner
et al., 19 91] and for an inability to match candidate characteristics beyond race perfectly [Heckman
and Siegelman, 1992, Heckman, 1998].
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