Are Good-Looking People More Employable?
Bradley J. Ruﬄe
Wilfrid Laurier University
forthcoming in Management Science
Abstract: We investigate the role of physical attractiveness in the hiring process. We sent 5312
CVs in pairs to 2656 advertised job openings. In each pair, one CV was without a picture while
the second otherwise almost identical CV contained a picture of either an attractive male/female
or a plain-looking male/female. Employer callbacks to attractive men are signiﬁcantly higher than
to men with no picture and to plain-looking men, nearly doubling the latter group. Strikingly,
attractive women do not enjoy the same beauty premium. In fact, women with no picture have a
signiﬁcantly higher rate of callbacks than attractive or plain-looking women. We explore a number
of explanations for this discrimination against attractive women and provide evidence that female
jealousy and envy are likely reasons.
Keywords: beauty, discrimination, job interview, jealousy, ﬁeld experiment.
Acknowledgements: We thank Dror Brenner, Danny Cohen-Zada, Naomi Feldman, David Genesove,
Gilles Grolleau, Daniel Hamermesh, Ori Heﬀetz, Leah Borovoi, Miana Plesca, Tata Pyatigorsky-Ruﬄe,
Justin Smith, the editor, Uri Gneezy, an associate editor, three anonymous reviewers and participants at
numerous conferences and departmental seminars for helpful comments. Ayala Waichman, Meytal Sasson
and Itai Carmon provided valuable research assistance.
We investigate the role of beauty in the earliest stage of the hiring process. We sent 5312 CVs in six
diﬀerent versions in response to 2656 advertised job postings in Israel. Half of these CVs contained
a picture of an attractive or plain-looking male or female job candidate. Each of these picture CVs
was paired with an otherwise identical control CV with no picture. In Israel, the choice to include
a photograph on one’s job resume is left to the candidate’s discretion. Thus, Israel is an opportune
location to explore not only the eﬀect of the attractiveness of the picture but also whether the
choice itself to include a picture predicts the likelihood of being invited for an interview.1
We ﬁnd that attractive males are signiﬁcantly more likely to be invited for an interview than no-
picture males and more than twice as likely as plain males. Surprisingly, among female candidates,
no-picture females have the highest response rate, 22% higher than plain females and 30% higher
than attractive females. These orderings are largely robust to a number of job characteristics such
as whether the job requires previous work experience and even whether the job involves face-to-face
dealings with the public. This discrimination against attractive women is puzzling when contrasted
with the observed beauty premium in a number of empirical and laboratory labor-market studies.
Our design strategy of sending paired CVs (i.e., one picture CV and one identical no-picture
CV) allows us to eliminate job selection as a possible explanation for these diﬀerences. Who does
the hiring furnishes a ﬁrst clue as to the source of the lower callback rates to attractive women:
when employment agencies are responsible, fair females fare no worse than plain females and are
penalized only modestly compared to no-picture females. By contrast, when companies directly
hire candidates, attractive females are singled out for penalization, with a response rate of nearly
half that of plain and no-picture women. Numerous explanations are possible, some of which are
discussed in section 6. Several more related to both statistical and taste-based discrimination are
addressed in section 5 with the help of additional analyses and a post-experiment survey on over
200 companies in our sample. Female jealousy and envy ﬁnd support in the data and can explain
why attractive females are penalized, especially by the companies that hire directly. Jealousy and
envy, however, cannot explain why attractive male candidates beneﬁt from a higher callback rate
from employment agencies in particular. To account for this and other diﬀerences and similarities in
1In Turkey, Scandinavia and the Baltic countries, whether to embed a picture in one’s CV is also optional. In
most continental European and South American countries, Japan and Cambodia, picture CVs are the social norm.
In China, picture CVs are required and regulated by law, whereas they are frowned upon in Anglo-Saxon countries
such as the U.S., Canada, the U.K. and Australia with the exception of the arts and entertainment industries in
which picture CVs are increasingly commonplace.
callback rates, we introduce a “photo-sensitive” hypothesis which reasons that employment agencies
are more likely than the companies themselves to be inﬂuenced by CV pictures.
2 Related Literature
2.1 Perceptions of Physically Attractive People
Decades of beauty research in psychology reveal that individuals attribute a spate of positive and
negative traits to physically attractive people. Beginning with Dion et al.’s (1972) pioneering study,
attractive people are believed to possess socially desirable traits (such as sensitivity, kindness, poise,
modesty and outgoingness), to be better spouses, have better career prospects and to lead happier
lives. In fact, the paper’s title summarizes the results, “What is beautiful is good”. Feingold’s
(1992) meta-analysis of this literature demonstrates a robust association for both men and women
between physical attractiveness and numerous personality traits, social skills, mental health and
intelligence. Hamermesh’s (2011) book “Beauty Pays” discusses the advantages of beautiful people
in the labor, loans and marriage markets, in sales and in happiness. Regarding attractive females,
however, a dissenting view has emerged in parallel beginning with Dermer and Thiel’s (1975) study
“When beauty may fall”. These authors ﬁnd that the more attractive the female being evaluated,
the more likely female subjects perceived her to divorce, have an extramarital aﬀair and to be vain,
egotistical, materialistic, snobbish and unsympathetic.2
Using several well-known laboratory games, researchers have found that physical beauty elicits
altruistic, trusting and cooperative behavior. For instance, Solnick and Schweitzer (1999) show
that although ultimatum-game oﬀers of attractive and unattractive subjects do not diﬀer from one
another, attractive respondents receive signiﬁcantly higher oﬀers than unattractive ones. In the
trust game, Wilson and Eckel (2006) demonstrate that attractive subjects are trusted more and are
also expected to trust more. Also in the trust game, Eckel and Petrie (2011) ﬁnd that trusters and
trustees are both willing to pay to see a photograph of their partner. They then use this photo to
discriminate between individuals in their choices. Andreoni and Petrie (2008) ﬁnd that attractive
players in public goods games earn more not because they contribute less to the public good but
because the presence of an attractive group member induces others to contribute more.
Berggren et al.’s (2010) study of political elections in Finland shows that a one-standard devia-
2Hatﬁeld and Sprecher (1986, ch. 10) survey the early social psychology literature that demonstrates the downside
of good looks. Agthe et al. (2010, 2011) summarize the more recent literature that demonstrates negative biases
against highly attractive same-sex individuals.
tion in beauty increases the average non-incumbent candidate’s votes by 20%. It seems that voters
make positive inferences based on attractiveness only when they are unfamiliar with the candidates
as no signiﬁcant beauty eﬀect is found for incumbent candidates.
2.2 Beauty in the Labor Market
A number of laboratory experiments concern the role of beauty in the labor market. In Heilman
and Saruwatari’s (1979) early study, 45 undergraduates participated in a decision-making scenario
in which they were asked to evaluate diﬀerent job packets for potential managerial and clerical
positions. The job packets contained relevant materials including a picture of an attractive or
unattractive male or female candidate. The authors ﬁnd that while attractiveness is advantageous
for men in both types of jobs, attractive women are favored over unattractive women for clerical
jobs and discriminated against for managerial positions.
More recently, Luxen and van de Vijver (2006) conduct three decision-making scenarios in which
participants read a job description and rate the likelihood that they would hire each of a series
of mock applicants based on their photos. Attractive candidates are rated higher on average than
unattractive candidates, but when females assess female applicants they rate unattractive women
more highly. In their second study, the authors distinguish between jobs in which the degree of
contact between the hired applicant and the assessor is high or low and ﬁnd that the female bias
against attractive women is restricted to the high-contact condition. The authors replicate their
second study on 51 human resource professionals and ﬁnd that female assessors in the high-contact
condition give low scores to female applicants regardless of their attractiveness. The authors invoke
sexual selection theory and intrasexual competition to explain their ﬁndings. Agthe et al. (2010)
present subjects with one of two decision-making tasks: rating candidates for a scholarship or
for a job. When the subject and the candidate are of the same sex, the attractive candidates
are rated lower than the moderately attractive candidates by male assessors and lower than both
the moderately attractive and unattractive candidates when rated by female assessors. Agthe et
al. (2011) extend this negative response toward attractive same-sex applicants to two additional
job-search tasks as well as to a university-admission scenario.
Despite mounting evidence in social and organizational psychology that individuals tend to
evaluate negatively attractive people of the same sex, not a trace of evidence can be found of such a
result in the economics or management literature on the role of beauty in the labor market. Using
broad household surveys in the U.S. and Canada on labor-market and demographic characteristics
in which the interviewer rated the respondent’s physical appearance, Hamermesh and Biddle (1994)
show that plain-looking individuals earn less than average-looking ones who earn less than those
who are good-looking. Moreover, the plainness penalty is slightly larger than the beauty premium,
and both are higher for men than women. Our paper complements theirs by focusing on beauty
discrimination with respect to job-search opportunities rather than diﬀerential salaries.
Biddle and Hamermesh (1998) track the earnings of graduates from a prestigious law school.
Based on photographs of matriculants in entering classes, they ﬁnd a weakly positive, but insignif-
icant, relationship between beauty and ﬁrst-year lawyers’ earnings. This beauty premium becomes
signiﬁcant ﬁve years after graduation and increases over the 15 years graduates were surveyed.
Mobius and Rosenblat (2006) design a laboratory labor market in which employers pay wages
to workers who perform a maze-solving task. Physically attractive workers are no better at solving
mazes than less attractive ones. Notwithstanding, attractive workers, both males and females alike,
are oﬀered higher wages. Parrett (2013) ﬁnds that attractive waitresses (but not waiters) receive
higher tips, even after controlling for server productivity diﬀerences.
Numerous studies have employed the method of sending written job applications or, more
recently, CVs of ﬁctitious candidates to examine discrimination based on race (e.g., Jowell and
Prescott-Clarke 1970, Riach and Rich 1991, Bertrand and Mullainathan 2004), gender (e.g., Firth
1982, Riach and Rich 1987) and sexual orientation (e.g., Weichselbaumer 2003).3In the Israeli
context, Ben Hador et al. (2005) explore discrimination based on age, gender, immigrant-status,
marital-status and ethnicity by sending between 94 and 384 CVs for each discrimination category.
Closer in topic to ours, Rooth (2009) sent ﬁctitious CVs of average-weight applicants as well as CVs
with the same photos digitally manipulated to make the applicant obese. Obese men and women
receive callback rates six and eight percentage points lower, respectively, than their normal-weight
counterparts. None of the candidates in our research are obese or even overweight and none could
be mistaken as such from their headshots.
In a contemporaneous paper closely related to ours, L´opez B´oo et al. (2013) sent ﬁctitious
CVs with pictures in response to job openings in Buenos Aires, Argentina. They used digitally
manipulated images constructed to match or deviate substantially from two golden ratios of fa-
cial proportions that had been previously veriﬁed as necessary conditions for attractiveness. The
authors ﬁnd that the faces that correspond to the golden ratio generate 36% more callbacks than
those that deviate from it. In the Discussion section, we compare their results with ours.
3See Riach and Rich (2002) for a history of this methodology.
3 Experimental Design and Procedures
3.1 Selection of Job Candidates’ Photographs
The ﬁrst step in the experimental design was to collect photographs in order to choose pictures of
attractive and plain-looking males and females to be included in CVs sent to employers. For this,
we solicited headshots from the general student population at Ben-Gurion University. Students
whose pictures were selected were paid 50 NIS (about $14 USD) and signed a standard photograph
release form, which assured them that the pictures would be anonymous, include no identifying
information and used for research purposes only.
Hundreds of pictures were submitted. After eliminating blurry, group or otherwise inappropriate
photos, there remained over 300 pictures.4Both (male) authors along with two female assistants
went over the remaining photos and, only in cases of unanimous agreement, further eliminated
photos of students whose ethnicity could be readily identiﬁed (see below) or who clearly ﬁt neither
extreme of attractive or plain-looking. This left us with 161 photos (78 males and 83 females)
from which to choose. We formed a panel of eight judges (four male and four female) ranging in
age from 28 to 49 with various professional backgrounds that include sculptor, hair stylist, public
relations specialist and economist. The judges were asked to rate on a 1-to-9 scale each of the
161 pictures along all of the three following dimensions: physical attractiveness, intelligence and
likely ethnicity (where 1 equals “deﬁnitely Sephardic”, 9 equals “deﬁnitely Ashkenazi” and 5 is
“uncertain”).5While attractiveness is our focus, the ethnicity rating is also important because
considerable evidence exposes discrimination against Jews of North African and Middle Eastern
origin (i.e., Sephardic Jews) compared to Jews of European origin (i.e., Ashkenazi Jews).6
After excluding photographed subjects strongly identiﬁed as Ashkenazi or Sephardic (mean eth-
nic rating below 3 or above 7, respectively), we selected the four male and four female photographs
with the highest mean attractiveness ratings as our attractive male and attractive female candi-
dates, respectively. Similarly, the four male and four female photographs with the lowest mean
4To minimize possible confounds and diﬀerences unrelated to beauty, we deemed as inappropriate and therefore
excluded photos of individuals that failed to meet one or more of the following criteria: pleasant expression, presentable
dress, brown or black hair color and not ostensibly overweight.
5So as not to burden some of the judges with too many tedious rankings, we replaced two of them (one male and
one female) midway through the rating process with two diﬀerent judges (one male and one female). Thus, most
photos were rated by six judges, with a few rated by all eight.
6Fershtman and Gneezy (2001) provide laboratory evidence that Ashkenazi and Sephardic Jews alike are less
trusting of Sephardic males than Ashkenazi males (identiﬁed by their family name). Rubinstein and Brenner (2014)
examine the earnings of native Israelis born of interethnic marriage. They ﬁnd that males born to Ashkenazi mothers
and Sephardic fathers (and thus bear a Sephardic family name) earn signiﬁcantly less than males born to Sephardic
mothers and Ashkenazi fathers (and thus have an Ashkenazi family name).
attractiveness ratings constituted our plain-looking male and female candidates, respectively.7
The ﬁrst row of Table 1 displays the panel of judges’ mean attractiveness rating over all four
photographs for each beauty category. With mean ratings of 6.48 and 8.00, our attractive males
(AM) and attractive females (AF) are rated more than three points and almost ﬁve points higher
on average than the respective plain-looking males (PM) and females (PF).8
To conﬁrm the attractive-plain distinction on a much larger sample, we recruited 443 student
subjects. Each student rated the attractiveness, intelligence and ethnicity of 10 or 20 photographs
from our sample. Consequently, all 16 of the photos we used in the experiment as well as numerous
other “competitors” (i.e., photos in our sample with similarly high or low mean judge ratings)
received over 100 student ratings.
The second row of Table 1 displays the students’ mean attractiveness ratings. They are similar
and not statistically diﬀerent from those of the judges for three of the four beauty categories (p-
values range from .42 to .71). The mean student rating of 7.01 for AF is a full point below that of
the judges (p<.01). Notwithstanding, the students rate the attractive females nearly four points
higher than the plain females. At the individual-photo level, the means range from 6.04 to 6.89 for
AM, from 2.31 to 4.55 for PM, from 7.63 to 8.83 for AF, and from 2.18 to 4.14 for PF.9Hence, even
the least beautiful attractive candidate is rated substantially higher than the most beautiful plain
candidate, for both males and females. In short, our attractive candidates are all unmistakably
better looking than our plain candidates.
3.2 Creating Candidates’ Identity
Each job candidate was given a ﬁctitious identity that included: ﬁrst and last name, telephone
number and email address. The ﬁrst names were chosen from a list of popular Jewish Israeli
names. To sidestep the issue of ethnic discrimination, we employed the two most common Israeli
family names (Cohen and Levi) in all of our CVs. These family names date back to Biblical times,
thereby predating the Ashkenazi-Sephardic distinction and are not associated with either ethnicity.
7Our choice of four photographs per beauty category is robust to ﬁrst standardizing each judge’s rating (i.e.,
subtracting the judge’s mean rating and dividing by his standard deviation) and then computing each photograph’s
mean of the standardized ratings.
8T-tests of means and non-parametric, rank-order Mann-Whitney tests of the distributions of ratings both conﬁrm
that these diﬀerences are highly signiﬁcant (p < .01 in all cases).
9Our ﬁndings that AF are rated higher than AM and PF lower than PM are consistent with the beauty literature,
which shows that women’s appearances evoke stronger reactions, both positive and negative, than men’s. The result
is that more women than men are rated as exceptionally attractive and more women than men are rated as plain
(see, e.g., Hamermesh 2011, pp. 28-30.)
We set up a telephone number with a voicemail box for each of the six beauty categories.
To avoid any unwanted (e.g., voice) inﬂuences on employers, we used the default recorded voice
message, which plays the same message for all candidates and avoids mention of the candidate’s
name. This latter feature allowed us to employ the same voicemail box for all of the pictures
within the same beauty category. For employers who prefer to respond by email, we created a
Gmail account for each of the candidate categories and included this email address on the CV.
3.3 Preparing the Content of the CVs
The next stage in the experimental design was to prepare the CVs’ content. We sent CVs in
response to advertised jobs in 10 diﬀerent ﬁelds of employment: banking, budgeting, chartered
accountancy, ﬁnance, accounts management, industrial engineering, computer programming, senior
sales, junior sales, and customer service. The ﬁrst six ﬁelds were chosen because they are suitable
for university graduates in economics and accounting, ﬁelds for which we felt conﬁdent crafting
compelling resumes on our own. The last four ﬁelds were chosen because they advertise a relatively
large number of job openings. For these, we hired an expert to help design the CVs. Notice that
beauty might be relevant and contribute to worker productivity in some of these ﬁelds such as sales,
customer service and some banking jobs like bank tellers, whereas beauty plays no obvious role in
accounts management, budgeting, industrial engineering and computer programming.
In an eﬀort to elicit as many responses as possible from employers (our dependent measure),
we took several measures to create appealing CVs in all candidate categories and job ﬁelds. For
example, each candidate had two years work experience at a large company in the relevant ﬁeld.
Moreover, all candidates in the ﬁrst eight ﬁelds had completed their B.A. “with excellence” (com-
parable to “magna cum laude” in the U.S.) in the relevant ﬁeld at Ben-Gurion University or in
human resources at a nearby aﬃliated college for the senior sales positions. For the two last ﬁelds
(junior sales and customer service), the candidates held only a high school degree to avoid being
perceived as over-qualiﬁed.
All CVs contained additional positive attributes. For example, all candidates had graduated
from well-known, nationally recognized high schools in the north Tel Aviv region. All possessed
native and native-like language skills in Hebrew and English, respectively. Furthermore, all had
completed their required military service and three years of volunteer experience. Finally, on the
basis of the ﬁeld of employment, the CVs in that ﬁeld were tailored to include any additional skills
expected of suitable candidates, such as computer skills and programming languages.
Overall, we created six versions of the same CV for each ﬁeld. Four versions contain a picture:
attractive male, plain male, attractive female, plain female. Two additional versions have no
picture: no-picture male, no-picture female. Except for the picture, the CVs were otherwise almost
identical within each ﬁeld.10
3.4 Responding to Job Ads
We adopted a “paired CV” strategy for responding to job ads. Speciﬁcally, exactly two CVs were
sent to each job ad, one with a picture and, as a control, the other same gender CV without a
picture. To the extent that we ﬁnd diﬀerences in response rates between picture CVs, our paired
CV strategy allows us to determine whether job selection can account for these diﬀerences. To
illustrate, if the CVs of attractive and plain-looking males were sent to similar distributions of
jobs, then we would expect the response rates of the corresponding paired no-picture male CVs
not to diﬀer signiﬁcantly from one another. More basically, this paired CV methodology allows us
to compare cleanly the response rate of any picture CV to the otherwise equivalent no-picture CV
because the two CVs were always sent to the same jobs.
In Israel, job-search websites are used to submit CVs in response to advertised positions. Ac-
cordingly, all of our CVs were sent between July 2008 and January 2010 using three large websites.
During this period, we scrutinized regularly the job postings in our 10 ﬁelds of interest on these
websites, noting all job postings in a given ﬁeld and randomly assigning each one (without replace-
ment) to one of the four picture CVs. We continued this random assignment until all of the new
postings (up to a multiple of four) had been exhausted. This method ensured that at every point
in time of the data collection process the number of CVs sent of each picture CV was exactly equal.
Also, the sending of the paired CVs to a job ad was staggered by a number of hours or even by as
much as a day to minimize the likelihood that the employer would notice that the two CVs were
eﬀectively identical.11 Whether the picture or no-picture version was sent ﬁrst was randomized
across CV pairs.
From the text of each job ad to which we responded, we recorded a number of job characteristics
(ﬁeld of employment, oﬃce job or job dealing with the public, any experience required) and company
10 The word “almost” refers to necessary negligible diﬀerences between versions – such as fonts, content order and
the company at which the candidate had worked for two years – all of which were randomized across CV versions.
11 In fact, we settled on sending two CVs to each job ad rather than more or all six versions for fear that sending
more would exponentially increase the risk of employer detection. It seems reasonable that any company spotting the
two CVs’ likeness will simply ignore both of them. The extent to which this occurs reduces the chances of obtaining
signiﬁcant diﬀerences between CV types.
characteristics (location, whether the company itself or an employment agency does the hiring).
None of the job ads requested or required a picture CV.
In total, 5312 CVs were sent in response to 2656 job postings. The left panel of Table 2
presents summary statistics about the job candidates, as well as the advertised job and company
characteristics in our database. The table shows that an equal number (2656) of male and female
CVs and an equal number (1328) of attractive and plain-looking CVs were sent, half as many as
the no-picture CVs. The distribution of CVs sent according to ﬁeld of employment reveals that no
ﬁeld received more than 18% of the total CVs sent, with ﬁve ﬁelds receiving 10% or more. Also,
27% of the jobs involve dealing with the public, while the remaining 73% are deﬁned as oﬃce jobs
because they entail little or no interaction with the public. Finally, 41% of the jobs required no
previous job experience and three-quarters of the job ads are placed by employment agencies with
only one-quarter placed by the company itself.
4.1 Main Results
We begin by asking, “What is the eﬀect of a picture on a CV?” Column (1) in Table 3 reports the
estimates from a linear probability model where the dependent variable equals one if the employer
called or emailed the candidate requesting an interview and 0 if not.12 The standard errors cluster
on the job advertisement to which applicants responded.13 Regression (1) shows that the inclusion
of a picture has a small, negative and only marginally signiﬁcant eﬀect. The callback rate to picture
CVs was 1.4 percentage points (hereafter “p.p.”) lower than to no-picture CVs (p=.07).
This ﬁnding masks considerable variation in the response rates across picture types. The last
row in the right panel of Table 2 displays the average response rate by CV type and points to
a sizeable beauty premium for males: CVs of attractive males elicit a 19.7% response rate on
average, nearly 50% higher than the 13.7% response rate of no-picture males and more than twice
the 9.2% response rate of plain-looking males. Put diﬀerently, an attractive male needs to send on
average ﬁve CVs in order to obtain one response, whereas a plain-looking male requires 11 CVs for
one response. This ordering among males is intuitive and could be reasonably anticipated from the
12 Overall, the response rate was 14.5%. Because in this and all subsequent regressions the linear probability and
probit models yield qualitatively identical results, we report the former for ease of interpretation.
13 Since some employers posted multiple ads, employment agencies in particular, we also clustered on the employer.
All of our qualitative results are robust to the choice of cluster cell.
beauty literature. Moreover, it is highly robust to occupation, as seen by the callback rates for each
beauty category broken down by ﬁeld of employment in Table 2. In seven of the 10 occupations,
attractive males are rewarded relative to no-picture males, while plain males are penalized.
The ordering among females is unexpected: no-picture CVs elicit the highest response rate at
16.6% followed by plain females at 13.6% and attractive females at 12.8%. In fact, Table 2 reveals
that no-picture females garnered the highest response rate in six of the 10 occupations. Attractive
females simultaneously received the lowest callback rate in ﬁve of these six occupations as well as
in customer service.
The linear probability model in (2) of Table 3 includes a dummy variable for each of the beauty
categories with no-picture females excluded. Thus, the highly signiﬁcant coeﬃcient of −.029 on the
male dummy implies that a no-picture CV from a male is 2.9 p.p. less likely to generate a callback
than the equivalent CV from a female (p=.035).14
The remaining marginal eﬀects compare the response rate of the indicated beauty category to
that of the same-sex no-picture CV. For instance, attractive males enjoy a 6 p.p. beauty premium
compared to no-picture males who are called back 4.5 p.p more often plain males (both p<.01).
Callbacks to attractive and plain females, respectively, are 3.8 p.p. and 3.1 p.p. lower than to no-
picture females. Both diﬀerences are highly signiﬁcant. However, the response rates for attractive
and plain females do not diﬀer signiﬁcantly from one another (t-test p=.69).
Our paired CV methodology also allows us to analyze responses at the job-advertisement level.
To each employment ad, a picture and otherwise equivalent no-picture CV were sent. Table 4
displays the percentages of instances in which the employer called back only the picture CV (“Pic-
ture Favored”), only the no-picture CV (“No Picture Favored”) and in which the paired CVs were
treated equally. This latter category is further broken down into cases in which neither candidate
was called (“No Callback”) and those in which both were called back (“Callback to Both”).
Focusing on outcomes in which the paired CVs received diﬀerential treatment, attractive males
are preferred to no-picture males nearly twice as often as the other way around (11.3% versus 6.2%).
However, this relationship reverses for plain-looking males: no-picture males are preferred to plain
males 7.8% of the time compared to the opposite preference for only 3.8% of total outcomes. A
chi-square test of proportions conﬁrms the diﬀerential treatment of attractive and plain male CVs
14 Although not the focus of the paper, this result suggests signiﬁcant discrimination against male candidates,
which is also present to varying degrees of signiﬁcance in subsequent regressions. In presenting the results, we will
not discuss this eﬀect since this research and the balance in the experimental design focus on beauty discrimination.
Ben Hador et al. (2005) also ﬁnd a preference for females over males in the Israeli labor market in their audit study.
when paired with no-picture male CVs (χ2(2)=27.3, p<.001). Among females, a higher percentage
of employers prefer the no-picture CVs both when paired with attractive and with plain-looking
females. For both comparisons, the no-picture female CV is favored about 50% more often than
the picture version. Yet, consistent with the regression results, a chi-square test shows that the
distributions of outcomes (“Picture Favored”, “No Picture Favored” and “Equal Treatment”) are
not signiﬁcantly diﬀerent from one another (χ2(2)=1.7, p=.43).
Any unobservable diﬀerences in the distributions of job ads to which we sent diﬀerent versions
of CVs ought to show up in diﬀerential response rates between the identical no-picture CVs as a
function of the picture CV with which they were paired. Table 5 provides this data. The 14.6%
response rate to no-picture male CVs paired with attractive male CVs is not signiﬁcantly diﬀerent
from the 12.8% response rate to no-picture male CVs paired with plain males (χ2(1)=0.9, p=.34).
For no-picture female CVs, the response rates are identical (16.6%, χ2(1)=0, p= 1) regardless
of whether they were paired with attractive or plain females. Thus, job selection cannot account
for the observed male beauty premium nor the attractive- and plain-female penalties compared to
4.2 The Role of Required Job Experience
Fifty-nine percent of the job openings to which we applied required some previous job experience,
while the remaining 41% did not. How might jobs requiring work experience relate to the beauty
premium? One hypothesis is that such jobs are, on average, more senior positions in which the
employee has more authority and responsibilities, and thus a greater impact on the company’s
bottom line. Employers can thus ill aﬀord to discriminate on the basis of factors not related to
productivity for these more senior posts. On the other hand, we know from previous research on
beauty that physical attractiveness is associated with a host of positive traits. For more competitive
positions where multiple candidates appear equally able, employers might, consciously or not, invoke
a candidate’s physical appearance and the associations that it engenders as a source of additional
information. Put diﬀerently, beauty may serve as a tie-breaker when employers face a diﬃcult
decision involving similarly qualiﬁed candidates. To the extent that jobs demanding experience are
also more competitive, this line of reasoning suggests that the observed male beauty premium will
be augmented and the female beauty penalty lessened.
Table 6 addresses the interaction between required job experience and the candidate’s looks.
The highly signiﬁcant coeﬃcient of −.056 on the experience variable implies that identical no-picture
candidates are nearly 6 p.p. more likely to receive a callback from a job that requires no previous
experience than one that does. Jobs requiring experience indeed appear to be more competitive. As
such, and in line with the above reasoning, attractive males beneﬁt primarily from jobs requiring
experience: they are 9.2 p.p. more likely to be called back than no-picture males and 12.2 p.p. more
likely than plain males (both p<.01), whereas for jobs requiring no experience, the marginal eﬀect
of attractive males is positive but not signiﬁcant.
Although attractive females receive 4.6 p.p. and 2.4 p.p. fewer responses than no-picture fe-
males for jobs requiring experience and no experience, respectively, only the former diﬀerence is
signiﬁcantly diﬀerent from zero (p < .01). Similarly, plain females are signiﬁcantly penalized for
jobs requiring experience only.
In summary, the ordering between beauty categories continues to hold for jobs requiring and
not requiring experience alike. However, jobs with previous work experience as a requisite are more
competitive and appear to accentuate the hitherto observed eﬀects of beauty.
4.3 The Role of Oﬃce Jobs and Jobs Dealing with the Public
If a beauty premium in hiring is to appear at all, it would be easiest to justify for jobs in which
the employee deals face-to-face with the public. Attractive employees who interact in person with
their customers may contribute to the company’s proﬁtability through increased sales or to the
customer’s utility through a more enjoyable interaction, which may ultimately increase sales. Both
outcomes justify a preference for attractive employees.
Based on the occupation and information included in the job advertisement, we classiﬁed all
job openings according to whether the position involves face-to-face contact with the public. In our
sample, 27% of the jobs require the employee to work with the customer in person (abbreviated
henceforth as “public”), while the remaining 73% are oﬃce jobs or positions that otherwise involve
no regular in-person contact with the customer.
Regression (4) in Table 7 reveals that the response rates for public and oﬃce jobs do not diﬀer
signiﬁcantly from one another. Moreover, the same preference ordering of attractive males over
no-picture males over plain males persists and remains signiﬁcant for both public and oﬃce jobs.
By comparison, plain females are signiﬁcantly penalized compared to no-picture females for public
jobs only, whereas the female beauty penalty is operative and signiﬁcant for both public jobs (5.7
p.p. less than no-picture females, p=.01) and oﬃce jobs (3.1 p.p. less, p=.06).
4.4 Who Does the Hiring?
Employment agencies posted 75% of the jobs in our sample, while the companies at which the
employee will work (henceforth abbreviated as “company”) posted the remaining 25%. Do these
diﬀerent hiring sources respond diﬀerently to beauty?15 Companies know better than employment
agencies the set of qualiﬁcations they seek in their employees. Consequently, one hypothesis to be
subsequently referred to as the “photo-sensitive” hypothesis is that companies will focus on these
qualiﬁcations in screening candidates and be less susceptible to the inﬂuence of the CV photographs.
Employment agencies, on the other hand, court the repeat business of their clients, namely, the
companies that outsourced hiring to them. To the extent that the employment agencies are not fully
informed about candidates’ potential ﬁt with the company, they will aim to put forth candidates
who will make a good impression on the company through their physical attractiveness, among
other traits. In summary, the photo-sensitive hypothesis predicts that the companies themselves
will ignore the CV pictures and treat all beauty categories equally, while the employment agencies
will favor the attractive candidates over the no-picture candidates who are preferred to the plain
The right panel in Table 2 reveals considerable support for the photo-sensitive-inﬂuence hy-
pothesis. For the companies, callback rates to males are conﬁned to the range of 12% (PM) to
17% (AM), while the response rates to plain females (15.1%) and no-picture females (15.7%) diﬀer
by less than one p.p. Attractive females stand out as the outlier with a meager 9.2% response
rate, about six p.p. lower than those of PF and no-picture females. At the same time, employment
agencies appear to rely on beauty as a means to discriminate among males, with attractive males
garnering a 20.7% callback rate, seven p.p. higher than no-picture males and 12 p.p. higher than
PM. The hypothesis is also consistent with employment agencies’ clear preference for no-picture fe-
males (16.9% response rate) over plain females (13.1%), but cannot explain why attractive females
garner a similarly low 13.9% response rate.
Regression (5) in Table 9 interacts each of the beauty categories with both the companies and
the employment agencies. The regression conﬁrms the lack of discrimination among companies:
15 Table 8 establishes that this question is distinct from those addressed in the previous two subsections. Namely,
the distribution of advertised jobs requiring experience between employment agencies and companies is similar to
the overall sample distribution. The same holds for jobs dealing with the public. Moreover, in none of the 10 ﬁelds
of employment are the job ads posted exclusively by employment agencies or companies. In fact, at the extremes,
the fraction of jobs posted by employment agencies varies from 55% (programming) to 92% (banking) and these two
ﬁelds account for only 14% of our overall dataset. The percentage of employment agencies in the other eight ﬁelds in
our sample remain within 10 p.p. of the overall sample average, ranging more narrowly from 65% to 84%.
the coeﬃcients on attractive-male company,plain-male company and plain-female company are all
small and not signiﬁcantly diﬀerent from zero (p=.33 , p=.32 and p=.80, respectively). Nor are
the companies’ response rates to attractive and plain males signiﬁcantly diﬀerent from one another
(p=.18). Attractive females are the only category of applicant, male or female, that companies
treat diﬀerently: the highly signiﬁcant coeﬃcient of −.066 on attractive-female company indicates
that attractive females are 6.6 p.p. and 5.8 p.p. less likely to be invited for an interview than
no-picture females (p=.01) and plain females (p=.10), respectively.
Employment agencies, by contrast, treat almost all of the beauty categories diﬀerently from
one another. Only the attractive and plain females are treated similarly (p=.70). The callback
rate to attractive males is signiﬁcantly higher than that to no-picture males, which is signiﬁcantly
higher than that to plain males (p < .01 in both cases). The higher response rate to no-picture
females is highly signiﬁcant when compared to plain females (p=.02) and weakly signiﬁcant against
attractive females (p=.06).
In brief, employment agencies and companies diﬀer sharply in their responsiveness to beauty.
Employment agencies strongly prioritize male candidates according to their attractiveness and in
accordance with the ranking of males observed throughout this paper: attractive males followed by
no-picture males followed by plain males. At the same time, these same agencies favor no-picture
females while discriminating modestly against plain and attractive females. In sharp contrast, the
companies themselves treat all same-sex beauty categories equally, with the exception of attractive
females who are penalized relative to plain and no-picture women.
The photo-sensitive hypothesis is consistent with the above diﬀerences and similarities in call-
back rates for all but one of the six beauty categories in both employment agencies and companies.
Only the lower response rate of attractive females, especially by the companies themselves, remains
unexplained. The companies’ singling out of attractive women provides our ﬁrst clue to the source
of their unexpectedly low response rates. For whatever reason, those who would have to work in
the same workplace as the hired candidate don’t want attractive females around. However, when
hiring is outsourced to an employment agency, discrimination against attractive females is lessened
and no diﬀerent from that against plain-looking women.
Our most unexpected result is the penalization of attractive women relative to women who do not
embed a picture in their CV. In this section, we examine possible explanations for this ﬁnding and
reconcile it with L´opez B´oo et al. who ﬁnd that attractive women beneﬁt from a premium compared
to unattractive women.
5.1 Possible Explanations
Why do employers respond to beauty diﬀerently as a function of the job candidate’s sex? What
explains the penalty to attractive women? Our randomized experiment rules out job selection.
To address these questions, we make use of certain features of our experimental design, data
collection process and the data itself. Furthermore, after completing the experiment, we conducted
a telephone survey of a randomly chosen subset of ﬁrms included in our sample from the experiment.
In total, 208 ﬁrms (111 employment agencies and 97 companies) completed the survey (response
rate of 73.8%). With questions about the socio-demographic background of the person who screens
incoming CVs and questions about the perception of picture CVs, our aim is to distinguish further
between competing explanations for our ﬁndings. The survey appears in the Appendix. Table 10
displays summary statistics from the survey to be invoked as needed when discussing some of the
5.1.1 The “Dumb-Blonde” Hypothesis
The “dumb blonde” stereotype is pervasive in Western culture. Its basis is that attractive women,
typiﬁed by blondes, are able to rely on their looks to advance and thus do not make use of their
intelligence. Applied to our results, employers in our sample who hold this stereotype would be
reluctant to invite attractive women for an interview.
Contrary to this hypothesis runs a vast psychology literature (discussed in section 2.1) showing
that individuals attribute a wide array of positive characteristics and dispositions to attractive men
and women alike, the most important one for our purposes being intelligence (see Feingold 1992
for a review). What is more, the photo selection stage of our research makes available judges’ and
subsequently students’ ratings, thereby enabling us to test the dumb-blonde hypothesis directly on
the collection of photos in our sample. Recall from section 3.1 that eight judges and a large sample
of students rated the 161 photos on the dimensions of attractiveness, intelligence and ethnicity,
each on a nine-point scale. Using the ﬁrst two measures, Table 11 reports the marginal coeﬃcients
from OLS regressions on intelligence ratings for this panel of 7480 observations. The standard
errors in parentheses are robust to heteroskedasticity and corrected for possible non-independence
of observations by clustering on each rater’s set of scores.
The coeﬃcient on “beauty” in regression (6) reveals that for every additional point a rater
assigns to a photographed person’s attractiveness, the same person’s intelligence is rated .26 points
higher on average. This result is highly signiﬁcant (p<.01) and contradicts the dumb-blonde
hypothesis. Regression (7) allows us to refute the hypothesis even more directly with the inclusion
of an indicator variable for whether the photographed person is male and an interaction term
between this indicator term and the “beauty” variable. The highly signiﬁcant marginal eﬀect of
.27 on “beauty” suggests that a female subject who is rated one point higher for her beauty is also
perceived to be an extra .27 points more intelligent on average, again contradicting the dumb-blonde
hypothesis and instead supporting the above-mentioned psychology literature. The remaining two
indicator variables reveal that the positive association between intelligence and beauty is even
stronger for photographed males.
This same positive association between beauty and intelligence continues to hold if we restrict
attention to the 16 attractive and plain photographs used in our experiment, as shown in regressions
(8) and (9); namely, the more attractive the rater judges one of the eight photographed females,
the more intelligent the female is presumed to be, all the more so for our eight males, as seen in
In sum, our results reject the dumb-blonde hypothesis as an explanation for the observed female
beauty penalty. Although the dumb-blonde stereotype may occupy a place in popular folklore, it
runs contrary to actual perceptions of attractive people – men and women alike – in both our
sample and the psychology literature on beauty.
5.1.2 Negative Signaling
In a work culture like Israel in which attaching a picture to one’s CV is optional rather than com-
pulsory, the choice to do so may be perceived diﬀerently depending on one’s physical appearance.
For this reasoning to explain our results, an attractive women who attaches a photograph to her CV
must be viewed negatively, whereas an attractive male who attaches a picture must be regarded as
signaling something positive. If women rarely embedded a photograph in their CV, while men did
so more often, the above reasoning could be reconciled with our results. More explicitly, suppose
there existed a cultural norm that frowned upon women including a photograph on their CV. A
woman who nonetheless opted for a picture CV would be less likely to receive a callback.
Our telephone survey reveals that no such norm exists. To begin, the results indicate that about
15-20% of job applicants attach a picture to their CV. More to the point, in response to our question
about which sex more frequently sends a CV with a self-photograph, 47% of the respondents (46%
of employment agencies and 49% of companies) answered that women do, while only 11% (9%
of employment agencies and 14% of companies) indicated that men do. The remaining 41% of
respondents answered that the two sexes do so equally often.16
For each sex separately, we also asked employers whether attractive or unattractive candidates
tend to attach a picture to their CV more often. The results, displayed in Table 10, highlight a
striking contrast between male and female candidates: by far the modal response (for employment
agencies and companies alike) is that there is no diﬀerence in the tendency to attach a picture
between attractive and unattractive males, whereas these same employers overwhelmingly indicate
attractive females are more likely to send a picture CV than unattractive ones. These ﬁndings con-
tradict the negative signaling explanation for they reveal that that women, particularly attractive
women, tend to send picture CVs at least as often as men.
Additional evidence against the negative signaling hypothesis comes from our photo ratings
dataset. The student raters were asked the following question for each photograph they saw:
suppose you looked like the photographed person, would you attach your picture to your CV?
Across all pictures and raters, 63.7% of the responses favor attaching the picture.17 Moreover, male
raters’ tendency to include the picture when rating other males (63.3%) does not diﬀer substantially
from females’ tendency when rating females (64.5%). Restricting attention to our 16 attractive and
plain candidates, 85.7% (n= 245) of subjects’ choices were to attach the picture of the attractive
male compared to 76% (n= 241) for the attractive females. Both of these percentages are markedly
higher than those observed for plain males (40.5%, n= 274) and plain females (30.9%, n= 256).18
These ﬁndings reveal that either our unsuspecting subjects are oblivious to the perceptions of
16 A chi-square test shows that employment agencies and companies do not diﬀer signiﬁcantly in their perception
of which sex sends a photographed CV more frequently (χ2(2)=1.6, p=.46).
17 The reader will recall our estimated 15-20% of applicants who actually do attach a photo to their CV. One partial
explanation for the discrepancy is that this percentage is higher among young, educated candidates, our subject pool.
18 Similar percentages hold if we restrict attention to same-sex raters and rated persons. More generally, based
on the entire photo rating dataset, we regressed the subject’s choice whether to attach the candidate’s photo to his
CV as a function of the candidate’s attractiveness. A highly signiﬁcant regression coeﬃcient of .07 on the “beauty”
variable (not shown but available upon request) indicates that for every additional point (on a 1-9 attractiveness
scale) the photographed candidate received, she is seven p.p. more likely to include her picture on her CV. Also, non-
signiﬁcant interaction terms reveal that the positive relationship between the photographed person’s attractiveness
and the expressed likelihood of attaching his picture is not signiﬁcantly diﬀerent for male candidates.
picture CVs by human resource staﬀ or that the reason for the penalization of attractive females
lies elsewhere and is unrelated to the negative signaling hypothesis.
More direct evidence against the negative signaling hypothesis follows from ﬁrms’ responses to
the question, “What message is conveyed by a male candidate who includes a picture on his CV?”
and, as a separate question, by a female candidate who includes her picture. Overall, similarly
high fractions of respondents reacted positively to males’ (64%) and to females’ (63%) inclusion
of a picture. The two most frequently invoked terms to describe males and females alike who
attach a picture to their CV were “self-conﬁdent” and “presentable”. A mere 15% of respondents
expressed negative associations for male photographs compared to 21% for female photographs,
while the remaining fractions verbalized a neutral opinion or no opinion at all. The distributions
of positive, negative and neutral responses to males’ and to females’ inclusion of a photo do not
diﬀer signiﬁcantly (χ2(2)=3.4, p=.18)
Finally, we examine whether negative signaling can explain the diﬀerential treatment of CVs
from female picture CVs by employment agencies and companies. The penalization of both cat-
egories of female picture CVs with respect to female no-picture CVs suggests that employment
agencies perceive negatively any female candidate who attaches a picture to her CV. On the other
hand, that the companies themselves spare plain females and penalize only attractive ones implies
that companies do not generally view negatively any female who includes a photo on her CV. Put
together and applying the logic of negative signaling to our ﬁndings, we would expect employment
agencies to view a female’s inclusion of a photo on her CV more negatively than companies them-
selves. In fact, similar and not signiﬁcantly diﬀerent proportions of employment agencies (20%)
and companies (22%) regard negatively a female picture CV (χ2(1)=0.24, p=.62).
In short, despite numerous tests of the negative signaling hypothesis using both the company
survey and the photo ratings data, none of the test results is consistent with the penalization of
5.1.3 Jealousy and Envy
Threats to one’s status or to interpersonal relationships arouse jealousy. Summarizing a body of
research in evolutionary psychology, Buss and Haselton (2005) write, “women become especially
distressed by threats from physically attractive rivals, whereas men become especially distressed
by rivals with more resources” (p. 506). Applied to our research design, the candidate’s resources
are either not mentioned on the CV (e.g., ﬁnancial resources) or identical across candidates (e.g.,
skills and educational background). On the other hand, the physical attractiveness of a candidate
is conspicuous on all picture CVs. Thus, while the trigger for female jealousy features prominently
on the candidate’s CV, it is absent for male jealousy. Moreover, numerous psychology studies
demonstrate that women are more susceptible to jealousy than men (see, for example, Sagarin et
al. 2003).19 Yet the arousal of jealousy requires that a rival party threaten a (potential) relationship
between the jealous person and another third person. Thus, while jealousy might possibly explain
the companies’ discrimination against attractive females, it cannot account for the employment
agencies’ penalization of attractive women being considered for hire oﬀ-site. Enter envy. Envy
arises “when one person lacks another’s superior quality, achievement, or possession and either
desires it or wishes the other didn’t have it” (Parrott and Smith 1993, p. 906).20 Female staﬀ at
both the companies and employment agencies may experience envy toward young, attractive female
The jealousy and envy explanations seem especially ﬁtting when we consider that 93% of the
respondents in our sample were female.21 As one may be concerned that the respondent is not be
the same person who screened the CVs, we made sure to speak with the CV screener who decides
who to invite for an interview when conducting our post-experiment survey. It turns out that 87.9%
of respondents indicated that the person who screens the CVs (themselves) also makes the phone
call to arrange an interview with the candidate. Broken down by company type, in 100/111 (90%)
of the employment agencies and 90/97 (93%) of the companies that we interviewed, the person
responsible is a female.22 Furthermore, these women are young (with an average age of 33) and
typically single (121/206 or 59%) – qualities more likely to be associated with a jealous response
when confronted with an even younger, attractive competitor in the workplace.
19 Relatedly, Eaves et al. (1989) examine law ﬁrms’ gender (and ethnic) discrimination of UCLA law students
in on-campus job interviews and ﬁnd that female candidates fare worse with female interviewers than with male
interviewers. Anecdotally, in her April 2012 post in England’s Daily Mail that went viral on why women hate her,
Samantha Brick laments being beautiful and the resultant jealousy that she has encountered on the job from female
coworkers and bosses.
20 Parrott and Smith (1993) distinguish envy from jealousy both conceptually and empirically, demonstrating that
the experiences associated with these emotions both coincide (e.g., anger, ill will and pettiness) and diverge (e.g.,
fear and distrust for jealousy versus disapproval and longing for envy).
21 A respondent is an employer who called back one or both of the candidates for an interview. The respondents’
sex was determined by their voice when they left a voicemail message, their name when they sent an email or by a
discreet phone call to the company if there remained any doubt.
22 Binomial tests cannot reject the hypotheses that these fractions are diﬀerent from our observed fraction of 93%
female respondents (p-values are .26 and .84, respectively). To gain a still broader picture of the gender composition
of human resource departments, we also asked each respondent for the number of people in her ﬁrm responsible for
screening CVs and for deciding whether to callback the job candidate, and for the percentage of women among these
staﬀ. Based on respondents’ estimated total human resource staﬀ of 1860 in the employment agencies contacted,
87.8% are female compared to 89.5% female out of the estimated 493 recruiting staﬀ in the companies themselves.
The ﬁnding from section 4.4 that only the companies themselves strongly discriminate against
attractive women and attractive women are the only category of females against which these com-
panies discriminate further buttresses the jealousy explanation. Females in charge of hiring at
the companies themselves may well be jealous (and envious) of prospective female employees who
are attractive and thus may compete with them for mates or at least for the attention of male
coworkers.23 At the same time, we saw that employment agencies do not disadvantage attractive
females relative to plain females and only weakly penalize them with respect to no-picture females.
It follows that when the females entrusted with hiring will not work with the candidates they hire,
jealousy is rendered inoperative. Envy alone remains. Accordingly, employment agencies discrim-
inate against attractive women to a lesser extent than do the companies themselves at which the
forces of both jealousy and envy apply.24
If we consider CV pairs for which at least one of the CVs was called back and thus the sex of the
caller is known, Table 12 displays the distribution of callbacks to CV pairs for female callers only
separately for ads placed by the companies themselves and those placed by employment agencies.
Strikingly, the largest case of within-pair discrimination among companies is directed at attractive
females: no-picture women are preferred to attractive females for 55% of the callbacks compared
to a preference for attractive females for only 17% of callbacks. On the other hand, women in
the companies themselves don’t seem to mind hiring plain-looking women and even favor them
(34.4% to 20.7%) over no-picture women. Plain women pose no threat to these female employers
and therefore do not arouse their jealousy. By contrast, among employment agencies, attractive
females are discriminated against less than any other group: the right panel of Table 12 reveals
a relatively small nine p.p. gap between the preference for no-picture females (36.4%) and the
preference for attractive females (27.1%) – considerably less than any of the other diﬀerences,
including the most closely related 21 p.p. preference for no-picture females over plain females.
Without the possibility to enter employers’ minds, we cannot determine beyond all doubt their
23 Evidence of concern for the attention that attractive females draw in the workplace comes from our survey
question that asks respondents whether they agree with the statement that “an attractive woman receives more
attention from male coworkers at the expense of other women in the workplace”: 77% of the respondents (80% at the
companies themselves) agreed with this statement, as seen in the second-to-last row in Table 10. These percentages
are notably high, particularly when compared to the percentages in agreement with the other statements about
attractive females: attractive women are a distraction in the workplace (47% agreed overall), get hired because of
their looks (42% agreed) and are below-average intelligence (only 6% agreed – yet another blow to the dumb-blonde
24 This result resembles closely the ﬁnding in Luxen and de Vijver (discussed in section 2.2) that females discriminate
against attractive women when the assessors are informed that they will have frequent contact with the hired applicant,
but display no such discriminatory tendency when told they will never meet. A taste-based model of discrimination
in the spirit of Becker (1957) would predict this dichotomy in the treatment of attractive females.
psychological motivations for choosing one identically qualiﬁed job candidate over another. Yet, we
have presented a range of evidence that points to female jealousy and envy as likely sources of the
observed discrimination against attractive females. To begin, about 90% of the staﬀ responsible for
the initial screening of CVs and callbacks to candidates are female. These women are typically young
and single and, when asked, overwhelmingly agree that attractive women receive more attention
from male coworkers at the expense of other women in the workplace. More direct evidence comes
from the source of hiring. When both jealousy and envy are potentially applicable (i.e., hiring done
by the company in which the hired job candidate will work), the mostly female staﬀ discriminates
strongly against attractive women only, treating similarly all other picture and no-picture CVs.
When we control for jealousy, but leave room for envy (i.e., outside employment agencies) attractive
females experience only weakly signiﬁcant discrimination.
5.2 Comparison with the Results of L´opez B´oo et al.
While we and L´opez B´oo et al. both ﬁnd that attractive males elicit more callbacks than unattractive
ones, they also observe this same ordering for females. In an attempt to account for our papers’
seemingly divergent results on attractive females, we asked our original panel of judges to rate the
attractiveness of all of L´opez B´oo et al.’s photos on the same 1-9 scale. Seven of our eight judges
rated all 16 (four in each beauty category) of the ﬁctitious, composite photos that appear in Table
1 of their paper.25 The judges’ mean ratings for the four beauty categories appear in Table 1, row
1 (our photos) and row 3 (theirs). Both in our paper and in theirs, the judges rated the attractive
candidates signiﬁcantly higher than the plain candidates for males and females alike (p<.01 for
all four t-test of means and all four non-parametric Mann-Whitney tests), thereby attesting to the
reasonableness of the choice of attractive and plain photos in both papers.
The most striking diﬀerence between the attractiveness ratings is that our attractive candidates
are rated markedly higher than those in L´opez B´oo et al. At 8.0 out of 9, the mean rating for our
attractive females is nearly twice that of 4.11 for theirs and our attractive males’ mean rating of
6.48 is more than 60% higher than theirs of 4.14 (p<.01 for both t-tests and both Mann-Whitney
tests). In fact, the mean ratings of their attractive candidates are suﬃciently low that they resemble
more, although are still signiﬁcantly diﬀerent from, our plain females (mean = 3.07, t-test p=.025,
Mann-Whitney p=.024) than they do our attractive women. Similarly, their attractive males are
25 Just as the judges were not told why they were asked to rate our photos, we did not inform them of the purpose
of this subsequent photo rating task.
rated only one point higher than our plain males.
Brieﬂy, both papers compare a set of candidates who are attractive when viewed alongside
a second set of less attractive candidates. In absolute terms, however, the mean ratings suggest
that their photos would be more accurately described as average-plus and unattractive, whereas
ours are highly attractive and average-minus.26 This being the case, our plain candidates’ looks
are representative of a sizeable swath of the population, whereas our attractive candidates reﬂect
the looks of only a small percentage. Thus, an open question remains whether our observed male
beauty premium and female beauty penalty also apply to slightly above-average-looking men and
women, respectively. If we put aside potentially important diﬀerences between our paper and L´opez
B´oo et al. (2013) and combine our results with theirs to speculate what might happen if we were
to extend the range of beauty covered in our paper, then we deduce that the beauty premium
for males is likely to hold across the spectrum of male beauty. Quite diﬀerently, a female beauty
premium applies up to average-plus looking women and metamorphoses into a beauty penalty for
highly attractive women.
The ﬁndings from our ﬁeld experiment make clear that attractive and plain job candidates are
not treated equally. Beauty discrimination occurs at the earliest stage of job search, and not only,
as Hamermesh and Biddle (1994) establishes, through diﬀerential salaries. To put our ﬁndings in
perspective, a plain male needs to send over twice as many CVs as an attractive male for an equal
chance at a callback. This result is robust across industries and job and employer characteristics
and ought to encourage highly attractive males to attach a photograph to their resumes in cultures
like Israel in which the inclusion of a picture is left up to the applicant. On the other hand,
attractive and plain women alike are better oﬀ omitting their photographs from their CVs since
their inclusion decreases their chances of a callback by 20% to 30%. Yet if the company at which
the chosen candidate will be employed is also in charge of hiring, plain women are no worse oﬀ
including their photograph, while the penalty for doing so for attractive women swells to 41%.
If our paper ended with these ﬁndings, it would ﬁll a void in the economics and management
literatures on the role of beauty in the labor market. To date, the undisputed consensus in these
26 The two papers’ dissimilar photo selection processes can account for these diﬀerences. L´opez B´oo et al. focus
on maintaining facial ratios previously shown to be necessary – but not suﬃcient – conditions for attractiveness. By
contrast, our invitation to students to submit their photos led to the foreseeable outcome in which truly unattractive
individuals mostly refrain from doing so, while multitudes of unmistakably attractive students volunteer their pictures.
empirical and laboratory labor-market studies is that good looks pay for men and women alike.
Yet, along with a growing psychology literature that points to discrimination against attractive
women, often by women themselves, in hypothetical hiring and other decision scenarios, our paper
challenges this view. To the best of our knowledge, ours is the ﬁrst paper to demonstrate a negative
return for attractive females in an actual labor market.
Additional analyses and a follow-up survey suggest that neither job selection, the dumb-blonde
hypothesis nor the mere attaching of a photo to a CV can account for the penalization of attractive
women, whereas substantial evidence points to female jealousy and envy as part of the explanation.
Other (untested) explanations are possible. For example, human resource personnel voice concern
that attractive women serve as social magnets and lower the productivity of their coworkers.27
Reluctance to hire attractive women may also be rooted in some of the negative qualities associated
with attractive women (see the discussion in section 2.1), such as vanity, egoism, snobbishness and
lack of sympathy – traits particularly detrimental to corporate cultures in which collaboration,
group tasks and mentoring are central. Finally, males may avoid hiring attractive females for fear
of backlash from their spouses and coworkers.
When drawing inferences from our results, keep in mind that our research design focuses on only
two beauty types, highly attractive and slightly below-average-looking candidates, rather than the
entire range of beauty.28 One clear-cut implication of our results is that beauty distorts the hiring
process. A proﬁt-maximizing ﬁrm aims to hire the most qualiﬁed candidate. However, suitably
qualiﬁed attractive women and plain men and women may be eliminated early on from the selection
process. One may retort that even without pictures on their CVs such candidates would eventually
be eliminated, at the interview stage, for example. Not necessarily so. For one, the interviewer
may not be the same person or even of the same sex as the person who screened the CVs. Even if
they are one and the same, the interviewer’s bias against attractive women, for instance, may be
attenuated after having ﬁrst mentally processed the candidate’s CV objectively without knowledge
of her appearance and after meeting her in person.29
One way to reduce discrimination based on physical appearance (and other traits unrelated to
the candidate’s suitability for the job) would be government legislation against, or the emergence
27 As a case in point, Debrahlee Lorenzana ﬁled a sexual harassment suit against Citibank in 2010, claiming that
she was ﬁred because her looks were, in her words, “too distracting for her male colleagues and supervisors to bear.”
28 In section 5.2, we speculate but cannot conﬁrm how employers would respond to more moderately attractive
and decisively unattractive candidates.
29 Babcock et al. (1995) present evidence of a similar psychological mechanism whereby subjects’ self-serving bias
in a simulated court trial is lessened if they ﬁrst read the case materials without knowing which side they represent.
of a social norm shunning, the inclusion of a photograph with one’s job application and conducting
at least initial interviews by phone rather than in person. Interestingly, several European countries
have recently begun to experiment with anonymous CVs whereby candidates are forbidden to in-
clude their picture, name, age, sex, date and place of birth, nationality and marital status anywhere
in their application.30 A second recommendation that follows from our results is for company man-
agers to pay greater attention to the gender of those responsible for hiring. A mixed-gender hiring
committee would help mitigate the beauty discrimination found herein.31
Agthe, M., M. Sp¨orrle, J. K. Maner. 2010. Don’t hate me because I’m beautiful: Anti-attractiveness
bias in organizational evaluation and decision making. Journal of Experimental Social Psy-
chology 46 1151–1154.
Agthe, M., M. Sp¨orrle, J. K. Maner. 2011. Does being attractive always help? Positive and negative
eﬀects of attractiveness on social decision Making. Personality and Social Psychology Bulletin
Andreoni, J., R. Petrie. 2008. Beauty, gender and stereotypes: evidence from laboratory experi-
ments. Journal of Economic Psychology 29 73–93.
Babcock, L., G. Loewenstein, S. Issacharoﬀ, C. Camerer. 1995. Biased judgements of fairness in
bargaining. American Economic Review 85(5) 1337–1343.
Bagues, M. F., B. Esteve-Volart. 2010. Can gender parity break the glass ceiling? Evidence from
a repeated randomized experiment. Review of Economic Studies 77(4) 1301–1328.
Becker, G. S. 1957. The Economics of Discrimination, Chicago: University of Chicago Press.
30 In Belgium, anonymous CVs are compulsory in the public sector. French President Nicolas Sarkozy commissioned
a pilot project in which 50 French ﬁrms volunteered to accept anonymous CVs only (Le Balch 2010). Sweden and
Germany recently conducted similar pilot studies with anonymous CVs (Donath 2010).
31 Consistent with this recommendation, Eaves et al. (1989) ﬁnd that male interviewers for law ﬁrms prefer female
law students over males more than female interviewers do, but that female interviewees are invited for a second
interview with the highest frequency when the interviewing team includes both genders. Broder (1993) observes that
female reviewers evaluating NSF grant proposals rate female-authored proposals lower than their male counterparts
did. Similarly, Bagues and Esteve-Volart (2010) show that a female candidate is less likely to pass the public exam
for a position in one of four divisions of the Spanish Judiciary whenever she is randomly assigned to a committee
with a relatively high share of female evaluators.
Ben Hador, B., A. Even, E. Apelboum, H. Drieher, D. Sharon, Y. Cohen, G. Mundlak. 2005.
Employment discrimination in Israel: Some evidence from correspondence tests. Labor, Society
and Law 11 381–407 (in Hebrew).
Berggren, N., H. Jordahl, P. Poutvaara. 2010. The looks of a winner: Beauty and electoral success.
Journal of Public Economics 94 8–15.
Bertrand, M., S. Mullainathan. 2004. Are Emily and Greg more employable than Lakisha and
Jamal? A Field experiment on labor market discrimination. American Economic Review 94(4)
Biddle, J. E., D. S. Hamermesh. 1998. Beauty, productivity, and discrimination: Lawyers’ looks
and lucre. Journal of Labor Economics 16(1) 172–201.
Broder, I. E. 1993. Review of NSF economics proposals: Gender and institutional patterns. Amer-
ican Economic Review 83(4) 964-970.
Buss, D. M., M. Haselton. 2005. The evolution of jealousy. Trends in Cognitive Sciences 9(11)
Dermer, M., D. L. Thiel. 1975. When beauty may fall. Journal of Personality and Social Psychology
Dion, K., E. Berscheid, E. Walster. 1972. What is beautiful is good. Journal of Personality and
Social Psychology 24 285–290.
Donath, J. 2010. Anonymous job applications: German pilot project aims to reduce discrimination.
in Spiegel Online, August 25, 2010, link.
Eaves, D., I. P. L. Png, J. M. Ramseyer. 1989. Gender, ethnicity, and grades: Empirical evidence
of discrimination in law-ﬁrm interviews. Law and Inequality Journal 7(2) 189–214.
Eckel, C., R. Petrie. 2011. Face value. American Economic Review 101(4) 1497–1513.
Feingold, A. 1992. Good-looking people are not what we think. Psychological Bulletin 111(2)
Fershtman, C., U. Gneezy. 2001. Discrimination in a segmented society: An Experimental ap-
proach. Quarterly Journal of Economics 116(1) 351–379.
Firth, M. 1982. Sex discrimination in job opportunities for women. Sex Roles 8891–901.
Hamermesh, D. S. 2011. Beauty Pays. Princeton: Princeton University Press.
Hamermesh D. S., J. E. Biddle. 1994. Beauty and the labor market. American Economic Review
Hatﬁeld, E., S. Sprecher. 1986. Mirror, mirror: The importance of looks in everyday life. New
York: SUNY, chapter 10.
Heilman, M. E., Saruwatari, L. R. 1979. When beauty is beastly: The eﬀects of appearance and
sex on evaluations of job applicants for managerial and non-managerial jobs. Organizational
Behavior and Human Performance 23 360–372.
Jowell, R., Prescott-Clarke, P. 1970. Racial discrimination and white-collar workers in Britain.
Race & Class,11(4) 397–417.
Le Balch, B. 2010. Le CV anonyme prend ses marques. L’Express, February 18, 2010, link.
L´opez B´oo, F., M. A. Rosi, S. Urz´ua. 2013. The labor market return to an attractive face: Evidence
from a ﬁeld experiment. Economics Letters 118 170–172.
Luxen, M. F., F. J. R. van de Vijver. 2006. Facial attractiveness, sexual selection, and personnel
selection: When evolved preferences matter. Journal of Organizational Behavior 27 241–255.
Mobius, M. M., T. S. Rosenblat. 2006. Why beauty matters. American Economic Review 96(1)
Parrett, M. 2013. Beauty and the feast: Examining the eﬀect of beauty on earnings using data
from a natural ﬁeld experiment. unpublished manuscript.
Parrott, W. G., Smith, R. H. 1993. Distinguishing the experiences of envy and jealousy. Journal
of Personality and Social Psychology 64(6) 906–920.
Riach, P. A., Rich, J. 1991. Testing for racial discrimination in the labour market. Cambridge
Journal of Economics 15 239–256.
Riach, P. A., Rich, J. 1987. Testing for sexual discrimination in the labour market. Australian
Economic Papers 26(49) 165–178.
Riach, P. A., Rich, J. 2002. Field experiments of discrimination. Economic Journal 112 F480–
Rooth, D.-O. 2009. Obesity, attractiveness, and diﬀerential treatment in hiring. Journal of Human
Resources 44(3) 710–735.
Rubinstein, Y., D. Brenner. 2014. Pride and prejudice: Using ethnic-sounding names and inter-
ethnic marriages to identify labour market discrimination. Review of Economic Studies 81
Sagarin, B., D. V. Becker, R. E. Guadagno, L. D. Nicastle, A. Millevoi. 2003. Sex diﬀerences
(and similarities) in jealousy: The moderating inﬂuence of inﬁdelity experience and sexual
orientation of the inﬁdelity. Evolution and Human Behavior 24 17–23.
Solnick S. J., M. E. Schweitzer. 1999. The inﬂuence of physical attractiveness and gender on
ultimatum game decisions. Organizational Behavior and Human Decision Processes 79 199–
Weichselbaumer, D. 2003. Sexual Orientation Discrimination in Hiring. Labour Economics 10(6)
Wilson, R. K., C. C. Eckel. 2006. Judging a book by its cover: Beauty and expectations in the
trust game. Political Research Quarterly 59(2) 189–202.