Economics Letters 108 (2010) 10–12
Contents lists available at ScienceDirect
Economics Letters
j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e c o l e t
Physical appearance and wages: Do blondes have more fun?
David W. Johnston ⁎
Queensland University of Technology, School of Economics and Finance, Australia
a r t i c l e
i n f o
Article history:
Received 8 February 2009
Received in revised form 23 March 2010
Accepted 26 March 2010
Available online 31 March 2010
a b s t r a c t
This study contributes to the economics literature that links physical characteristics to labour market
outcomes, by investigating the influence of hair colour on women's own wages and also their spouse's
wages. Using U.S. panel data, we find that blonde women receive large wage premiums.
© 2010 Elsevier B.V. All rights reserved.
Keywords:
Beauty
Wages
Discrimination
JEL classification:
J71
J10
1. Introduction
A growing economics literature links physical characteristics to
labour market outcomes, especially wages. For example, Hamermesh
and Biddle (1994), Harper (2000) and Mobius and Rosenblatt (2006)
examine the labour market effects of beauty; Cawley (2004) and
Averett and Korenman (1996) the effects of obesity; and Persico et al.
(2004) and Case and Paxson (2008) the effects of height. We
contribute to this literature by investigating the influence of an iconic
physical characteristic – blonde hair – on women's own wages and
also their spouse's wages.
The media often depicts blonde women as being more attractive
than other women, but also less intelligent. These depictions seem to
reflect public perceptions. For example, Price (2008) reports higher
mean beauty ratings for Caucasian blonde females than for Caucasian
brunette females or minority females. Moreover, Rich and Cash
(1993) find a substantial over-representation of blonde females in the
media, and conclude that female blondeness is associated with beauty
and sexuality. With respect to the low intelligence perception, Kyle
and Mahler (1996) find that people rate blondes as less capable than
brunettes, based purely on photographs. To the extent that these
perceptions also hold true in the labour and marriage markets,
blondeness could positively or negatively affect wages: positively if
the beauty perception dominates, negatively if the low intelligence
perception dominates.
⁎ Corresponding author. Queensland University of Technology, School of Economics
and Finance, Level 8, Z Block, Gardens Point Campus, Brisbane, Queensland, 4001,
Australia. Tel.: +61 7 31386789.
E-mail address: [email protected].
0165-1765/$ – see front matter © 2010 Elsevier B.V. All rights reserved.
doi:10.1016/j.econlet.2010.03.015
Using U.S. panel data, we find that blonde women receive a large
wage premium. In fact, the blonde wage premium is similar in size to
the return from an extra year of schooling. We also find that the
spouses of blonde women receive higher wages. These results broadly
agree with the findings in Price (2008), which show that blonde
Caucasian females have greater fund raising success than their
brunette counterparts.1
2. Data
Our data source is the 1979 cohort of the National Longitudinal
Survey of Youth (NLSY79). This panel data set is based on a sample of
12,686 Americans residing in 8770 unique households who were 14–
21 years old in January 1979. Respondents were first interviewed in
1979 and were re-interviewed annually from 1979 to 1994, and
biennially from 1994 to 2006.
We limit our sample to Caucasian women aged 25 and over.2 The
Caucasian restriction is imposed because race influences both hair
colour and labour market outcomes. The age restriction is imposed
because we want to control for differences in the life-cycle earnings
profile. Differences in the earnings profile may arise, for example,
from differences in highest educational attainment or occupation,
which may be associated with appearance.
1
We've focused on women in this paper because hair colour is associated with
certain stereotypes for women that do not exist for men. In accordance with this
difference between genders, we find no significant hair colour effects for men.
2
Caucasian respondents are those that both describe themselves as neither black
nor Hispanic nor Asian, and are described as white by the interviewer.
D.W. Johnston / Economics Letters 108 (2010) 10–12
11
Hair colour is measured by responses to a question in the 1985
survey: “What is your natural hair colour”. Women in our sample
responded with the following: light blonde (1.6%), blonde (19.0%),
light brown (21.8%), brown (51.2%), black (2.4%) and red (4.0%).3
Women are classified as blonde if they answered light blonde or
blonde.
Table 1 presents sample means of log hourly wages, spouse's log
hourly wages and selected covariates. These statistics show that
blonde women have higher log wages than other women, and that
their spouse's have higher log wages than the spouse's of other
women. There are, however, few clear differences between women in
their characteristics. Blonde women are lighter than brunette women,
but there are no systematic differences in education, Armed Forces
Qualification Test (AFQT) scores, immigrant status or marital status.
From these raw statistics it appears that differences in wages by hair
colour are not driven by differences in productivity related
characteristics.
Table 1
Sample means of wages and selected characteristics by hair colour.
3. Empirical results
Note: Figures in parentheses are robust standard errors. * and ** represent significant
difference from blonde haired women at 0.05 and 0.01 level, respectively.
We further examine the effect of hair colour on earnings by
estimating a traditional log wage equation
ln ðwit Þ = β0 + β1 HCi + β2 Xit + εit
ð1Þ
where wit is the real hourly wage of individual i in period t, HCi is a
vector representing natural hair colour, Xit is a vector of control
variables and εit is a random error term. The control variables include
standard demographic characteristics that have been shown to
influence wages (age, age squared, education, marital status, and
immigrant status) and measures of physical appearance that may be
correlated with hair colour (eye colour, height, and weight).
An advantage of estimating the effect of natural hair colour
compared with other physical characteristics, such as subjectively
rated beauty, weight or height, is that individual or family attributes
(e.g. productivity, income, and nutrition) cannot alter natural hair
colour. Thus, the estimates of β1 in Eq. (1) are less likely to suffer from
omitted variable bias or reverse causality. A possibility, however, is
that blonde hair is more common in certain ethnicities (e.g. Nordic)
and that these ethnicities are favoured in the labour market (e.g.
because of a high cultural work ethic). Fortunately, the NLSY contains
detailed information on ethnicity and so we include in each
specification indictors of whether the individual classifies themselves
as English, French, German, Irish, Italian, Polish, Scottish or American.
Another possibility is that blonde hair is correlated with unobserved
physical characteristics, such as fair skin. This implies that if fair skin,
for example, positively affects wages then the estimated blonde wage
effect will be upwards biased. We do not see this as a major drawback,
however, as the estimate would still reflect the influence of having a
blonde appearance.
An additional methodological issue is that women's current hair
colour may not be their natural hair colour. For example, some
naturally brunette women may look blonde. Such misclassification
introduces measurement error into our hair colour indicators and so
our estimated effects may suffer from attenuation bias. In other
words, the true effects may in fact be larger than our estimates.
Column 1 in Table 2 presents random effects estimates of Eq. (1).
The estimates suggest that blonde women earn 7% more than
brunette women (the omitted hair colour category).4 Surprisingly,
this wage premium is as large as the return to an extra year of
3
Forty-six women do not have a recorded hair colour. We include a dummy
variable in all regressions to control for this missing information.
4
If OLS is used we find that blonde women earn eight percent more than brunette
women. A random effects approach is preferred to OLS because it more adequately
captures the panel structure of the data. Of course, a fixed effects approach is not
possible because hair colour is time-invariant.
Log hourly wage
Spouse's log hourly wage
Height (in.)
Weight (lb)
Education (years)
AFQT percentile
Immigrant
Married
Sample size
Blonde
Light Brown
Brown
All others
2.641
(0.011)
3.056
(0.012)
65.00
(0.039)
146.0
(0.560)
13.89
(0.035)
0.587
(0.004)
0.020
(0.002)
0.633
(0.007)
4288
2.576
(0.010)
2.950**
(0.012)
64.68
(0.038)
143.6
(0.544)
13.90
(0.034)
0.602
(0.004)
0.022
(0.002)
0.637
(0.007)
4573
2.527**
(0.007)
2.983*
(0.008)
64.82
(0.025)
150.4*
(0.363)
13.61
(0.022)
0.565
(0.003)
0.019
(0.001)
0.673
(0.005)
10,373
2.539*
(0.017)
2.991
(0.019)
64.39*
(0.065)
150.2
(0.925)
13.66
(0.057)
0.566
(0.007)
0.030
(0.004)
0.676
(0.012)
1606
education. No other hair colour influences wages — light brown, red
and black are individually and jointly insignificant (p-value equals
0.94 in the RE model).5 Therefore, it seems that the association
between blonde women and beauty dominates any perception that
blonde women have low intelligence, and so consequently our results
are most readily explained by appealing to the economics of beauty
literature. Mobius and Rosenblatt (2006) find that the beauty
premium exists because attractive workers are more confident, have
greater communication and social skills, and are wrongly considered
by employers to be more productive.
To better understand the causes of the blonde wage premium, we
examine whether it arises from general employer discrimination in
favour of blonde haired women or from occupation-specific productivity effects. If the wage premium is related to attractiveness, blonde
women may have a productivity advantage in occupations that
involve interactions with customers or co-workers.6 We test this
proposition by augmenting our log wage equation with occupation
terms and occupation–blondeness interaction terms7:
ln ðwit Þ = β0 + β1 HCi + β2 Xit + β3 OCCit
ð2Þ
+ β4 ðOCCit × HCi Þ + νi + εit
We estimate Eq. (2) and find that all interaction terms are highly
insignificant (test of joint significance has a p-value equal to 0.82).
This result suggests that the blondeness premium is not occupationspecific; however, the analysis is limited by the lack of a firm
determination of occupations in which looks are likely to enhance
productivity (for a discussion see Hamermesh and Biddle, 1994).
It seems plausible that blondeness may also improve women's
fortunes in the marriage market, as blonde women would have an
advantage through their higher attractiveness ratings and wages
(Becker, 1973). Marriage market research demonstrates that men's
traditional role as a financial provider makes males with high wages
more desirable marriage and dating partners. Thus, we'd expect
5
It's possible that hair colour directly affects some of the included controls, such as
education and marriage, and consequently we may be suppressing a portion of the
effect. A random effects model including only physical appearance and ethnicity
variables produces a blondeness coefficient equal to 0.075, which is similar to the
coefficient in the expanded model. All other hair colour coefficients are again
insignificantly different from zero.
6
Results from a multinomial logit model of occupational choice suggest that blonde
women are marginally less likely to be employed in sales and administration jobs than
brunette women; however, the effects are significant only at the 0.10 level.
7
We follow Harper (2000) and include broad occupation categories: professional,
technical, sales, clerical, service, manual.
12
D.W. Johnston / Economics Letters 108 (2010) 10–12
Table 2
Estimated effects of hair colour on log wages.
Blonde hair
Light brown hair
Black hair
Red hair
Blue eyes
Green eyes
Hazel eyes
Height (in.)
Weight (lb/100)
Age
Age squared/100
Education (years)
AFQT percentile
Immigrant
Married
Sample size
Own wage
Spouse's wage
0.072**
(0.027)
− 0.002
(0.026)
− 0.001
(0.069)
− 0.033
(0.057)
0.032
(0.027)
0.067*
(0.030)
0.041
(0.030)
0.008**
(0.002)
− 0.044*
(0.021)
0.033**
(0.010)
− 0.036**
(0.013)
0.071**
(0.006)
0.485**
(0.049)
− 0.021
(0.065)
0.003
(0.013)
20,840
0.064*
(0.032)
− 0.017
(0.030)
0.084
(0.078)
− 0.078
(0.056)
0.004
(0.030)
− 0.026
(0.033)
0.025
(0.034)
0.002
(0.002)
− 0.096**
(0.025)
0.071**
(0.010)
− 0.070**
(0.013)
0.031**
(0.006)
0.331**
(0.054)
0.126+
(0.075)
15,538
Note: Robust standard errors shown in parentheses. * and ** represent significance at
0.05 and 0.01 level, respectively. Controls for a small number of missings on hair and
eye colour, weight and AFQT are included in each regression, but not shown. Also
included but not shown are a time trend and detailed controls for ethnicity. Omitted
dummy variable categories are: brown hair, brown eyes, USA born and not married.
blonde women to form matches with higher socioeconomic status
men. In column 2, we present the estimated effect of blonde hair on
spouse's log earnings. Indeed, we do find large significant effects from
having blonde hair. Spouses of blonde women are estimated to earn
around 6% more than the spouses of other women. As for women's
own wages, other hair colours are individually and jointly
insignificant.
4. Conclusions
This study investigates the influence of hair colour, in particular
blonde hair, on women's own wages and also their spouse's wages
using a large U.S. data set. Regression results indicate that blonde
women receive a wage premium equivalent in size to the return for an
extra year of schooling. A significant blondeness effect is also evident
in the marriage market. Blonde women are no more or less likely to be
married; but, their spouse's wages are around 6% higher than the
wages of other spouse's.
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