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Economics Letters 100 (2008) 351 – 354
www.elsevier.com/locate/econbase
Fund-raising success and a solicitor's beauty capital: Do blondes
raise more funds? ☆
Michael K. Price ⁎
Department of Resource Economics, Mail Stop 204, University of Nevada-Reno, Reno, NV, 89557, United States
Received 3 November 2006; received in revised form 4 February 2008; accepted 26 February 2008
Available online 5 March 2008
Abstract
This study uses a door-to-door fund-raising field experiment to explore the returns to physical appearance on fund-raising success.
Interestingly, blonde females earn more on average than brunette counterparts. However, the returns to physical appearance depend critically on
the race of a potential donor.
© 2008 Elsevier B.V. All rights reserved.
Keywords: Public goods; Beauty; Productivity
JEL classification: H41; J10; L3
1. Introduction
The role of physical appearance on economic outcomes has
been illustrated in a variety of contexts. In a seminal work,
Hamermesh and Biddle (1994) examine the impact of physical
attractiveness on labor market earnings and illustrate the presence
of both a beauty premium and a plainness penalty. Subsequent
studies highlight the robustness of this result across a variety of
occupations and cultures (see, e.g., Biddle and Hamermesh, 1998;
Harper, 2000; Pfann et al., 2000; Mobius and Rosenblatt, 2006).
While the beauty/productivity relationship has garnered
increasing attention in the literature (see, e.g., Pfann et al., 2000;
Mobius and Rosenblatt, 2006), the impact of more cosmetic
attributes on economic outcomes has remained largely un-
explored.1 This study uses panel-data from Landry et al. (2006)
to examine whether returns to physical appearance are correlated with a solicitor's hair color. Several interesting insights
emerge.
The returns to physical appearance are approximately 71.6 to
76.0% greater for a blonde female than a brunette (minority)
counterpart. Interestingly, the returns to beauty for blonde females are driven entirely by Caucasian households. In fact,
blondes receive significantly lower donations at non-Caucasian
households. Yet there is no discernable difference across household types for both brunette and minority females.
2. Experimental design
This study uses data from a natural field experiment on fundraising reported in Landry et al. (2006). Households in predetermined neighborhood blocks in Pitt County, North Carolina,
were approached in one of four treatments – a VCM with and
☆
The editor Eric Maskin and an anonymous reviewer provided remarks that
significantly improved the study. Jonathan Alevy, Omar Al-Ubaydli, Craig
Landry, Andreas Lange, John List, and Klaus Moeltner, provided excellent
comments during the discovery phase.
⁎ Tel.: +1 775 784 1679; fax: +1 775 784 1342.
E-mail address: [email protected].
0165-1765/$ - see front matter © 2008 Elsevier B.V. All rights reserved.
doi:10.1016/j.econlet.2008.02.028
1
A notable exception is a paper by Hamermesh et al. (2002) which combines
information on labor market outcomes with data on household expenditures to
examine the effects of clothing and cosmetics purchases on the wages of a
sample of women in Shanghai, China.
Author's personal copy
352
M.K. Price / Economics Letters 100 (2008) 351–354
Table 1
Summary statistics by solicitor type
All data pooled
Households visited
All treatments
VCM
Seed money
Single-prize lottery
Multiple-prize lottery
Percent donating
All treatments
VCM
Seed money
Single-prize lottery
Multiple-prize lottery
Average donation
All treatments
VCM
Seed money
Single-prize lottery
Multiple-prize lottery
Mean beauty rating
% of Caucasian households
% of minority households
Caucasian blonde female
Caucasian brunette female
Minority female
148
66
82
.
.
475
121
98
119
137
332
59
59
77
137
29.1%
36.3%
23.2%
.
.
30.7%
33.1%
16.3%
39.5%
31.4%
34.3%
25.4%
11.9%
48.1%
40.1%
$2.32 (5.96)
$1.89 (3.57)
$2.67 (7.36)
.
.
0.29 (0.44)
89.2%
10.8%
$1.41 (3.85)
$1.24 (2.18)
$1.33 (4.02)
$1.52 (4.87)
$1.52 (3.92)
0.24 (0.69)
88.0%
12.0%
$1.28 (2.95)
$0.66 (1.65)
$0.69 (2.14)
$1.56 (2.56)
$1.63 (3.73)
0.04 (0.66)
84.9%
15.1%
Note: Cell entries represent summary statistics for various solicitor types considered in the analysis.
without seed money, a single-prize lottery, and a multiple-prize
lottery – and asked to contribute to the Center for Natural
Hazards Mitigation Research at East Carolina University.2 In
total, forty-four solicitors spoke with 1755 potential donors and
elicited contributions from 522 households. For purposes of the
current study, the data are restricted to 955 of these households
that were approached by one of twenty-three female solicitors
employed in the Landry et al. (2006) study.
In the spirit of Biddle and Hamermesh (1998), digital photos
of each solicitor were taken to derive measures of physical
attractiveness. Photographs were randomly allocated into files
that contained the pictures of three other solicitors and evaluated
by 152 different observers — undergraduate students in a large
introductory economics course at the University of Maryland,
College Park. Each observer evaluated twelve photographs and
was asked to place each on a scale of (1) homely, extremely
unattractive, to (10) “model” beautiful or handsome. Each
rater's scores were normalized to yield a standardized scale
distributed standard normal. To generate the final personal
attractiveness measure, standardized ratings for each solicitor
were averaged over all evaluators.
3. Experimental results
Table 1 presents summary statistics for three solicitor types –
blonde, brunette, and minority females – across the four experimental treatments. One clear data pattern highlighted in Table 1
is that blonde females induce more households to contribute and
elicit higher donations per contact. For example, blonde solicitors in the VCM treatment induce contributions from approx2
I refer the interested reader to Landry et al. (2006) for a more detailed
description of the experimental design.
imately 3.2% (10.9%) more households and elicit average
contributions that are $0.65 ($1.23) greater than brunette
(minority) female counterparts.
To complement these unconditional insights, I estimate a
series of linear regression models of the amount contributed
(including zeros) by each household. Specifically, I follow
Landry et al. (2006) and estimate models of the form:
Lij ¼ Dij d þ Xij b þ Zij g þ eij
ð1Þ
where Lij is the contribution level of the jth household elicited
by the ith solicitor, D is a vector of indicators for the experimental treatments, X is a vector of solicitor characteristics –
including physical appearance and female hair color – and Z is
a vector of household specific covariates. Standard errors are
clustered by solicitor to control for unobserved heterogeneity.3
Empirical results in column 4 of Table 2 provide insights
consistent with the unconditional results: households contributed $1.38 more on average to a blonde female than to a brunette
female of equal physical appearance with this difference statistically significant at the p b 0.05 level. Including the interaction
of physical appearance with indicators for blonde and brunette
females highlights an interesting asymmetry: the estimated returns to a one standard deviation increase in personal attractiveness are approximately 82.3% greater for blonde females.
To gain further insights on the structure of these returns, I
estimate a linear probability model of the contribution decision
of households that answered the door:
Cij ¼ Dij d þ Xij b þ Zij g þ eij
ð2Þ
3
All empirical results are robust to the use of empirical models that account
for potential selection effects and control for unobserved heterogeneity using
solicitor random effects.
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M.K. Price / Economics Letters 100 (2008) 351–354
353
Table 2
Decomposing the female beauty effect
Baseline — minority female in VCM
Indicator for seed money treatment
Indicator for single-prize lottery treatment
Indicator for multiple-prize lottery treatment
Indicator for a blonde female
Indicator for a Caucasian brunette
Solicitor beauty rating
Model A
Model B
Model C
Model A
Model B
Model C
Pr(Cit = 1)
Pr(Cit = 1)
Pr(Cit = 1)
$'s given
$'s given
$'s given
0.59 ⁎⁎
(0.07)
− 0.22 ⁎⁎
(0.05)
0.14 ⁎
(0.06)
0.19 ⁎⁎
(0.05)
0.13 ⁎
(0.05)
− 0.10 ⁎⁎
(0.03)
0.13 ⁎⁎
(0.03)
0.40 ⁎⁎
(0.10)
− 0.13 ⁎
(0.06)
0.14 ⁎
(0.06)
0.15 ⁎
(0.07)
0.40 ⁎⁎
(0.10)
−0.13 ⁎
(0.06)
0.14 ⁎
(0.06)
0.15 ⁎
(0.07)
1.22 ⁎
(0.47)
0.31
(0.21)
1.14 ⁎⁎
(0.41)
0.84 ⁎
(0.29)
1.45 ⁎⁎
(0.36)
0.07
(0.23)
0.54 ⁎
(0.26)
0.88
(0.68)
0.63
(0.49)
0.98 ⁎⁎
(0.35)
0.61
(0.32)
0.87
(0.67)
0.62
(0.48)
0.99 ⁎⁎
(0.35)
0.60
(0.32)
Beauty rating for a blonde female
Beauty rating for a Caucasian brunette
Beauty rating for a minority female
0.15 ⁎
(0.07)
0.14 ⁎
(0.06)
0.08
(0.05)
Blonde beauty and a Caucasian household
Blonde beauty and a minority household
Brunette beauty and a Caucasian household
Brunette beauty and a minority household
Minority beauty and a Caucasian household
Minority beauty and a minority household
Personality controls
Household characteristics
Solicitor effects
# of clusters
Total # of observations
R-squared
Yes
Yes
Cluster SE's
23
955
0.09
Yes
Yes
Cluster SE's
23
955
0.07
0.19 ⁎
(0.08)
−0.13
(0.11)
0.15 ⁎
(0.06)
0.11
(0.12)
0.09
(0.05)
0.07
(0.10)
Yes
Yes
Cluster SE's
23
955
0.08
Yes
Yes
Cluster SE's
23
955
0.02
1.26 ⁎
(0.56)
0.69 ⁎
(0.33)
0.01
(0.35)
Yes
Yes
Cluster SE's
23
955
0.02
1.67 ⁎⁎
(0.56)
− 1.68 ⁎
(0.80)
0.74 ⁎
(0.32)
0.41
(0.58)
− 0.04
(0.45)
0.33
(0.59)
Yes
Yes
Cluster SE's
23
955
0.02
Note: cell entries provide parameter estimates and standard errors (in parentheses). Standard errors have been clustered around individual solicitor effects.
⁎⁎ Denotes statistical significance at the p b 0.01 level.
⁎ Denotes statistical significance at the p b 0.05 level.
where Cij equals unity if solicitor i received a contribution from
household j, and equals zero otherwise. As before, I cluster the
standard errors by solicitor and am careful to follow the basic
specification of Landry et al. (2006).
As noted in column 1 of Table 2, households are approximately 13% more likely to contribute when approached by an
attractive female. Exploring this result a level deeper, I find that
holding beauty constant a blonde female is approximately 23%
more likely to elicit a donation than a brunette counterpart with
this difference significant at the p b 0.05 level. Interestingly, as
noted in column 2, there are no discernable differences in the
returns to physical appearance across solicitor types.
3.1. The role of donor race
Landry et al. (2006) posit that a solicitor's physical appearance impacts contributions through a warm-glow component in
a donor's utility function. To allow feelings of warm-glow to
vary across donor types, I augment the vector X in Eqs. (1) and
(2) to include the interaction of physical appearance with indicators for the race and gender of a potential donor. Empirical
estimates are contained in columns 3 and 6 of Table 2.
As noted in the table, the returns to beauty for blonde solicitors are directly correlated with household race. Ceteris
paribus, a blonde female with normalized beauty rating of one
is approximately 32% more likely to elicit a contribution and is
expected to raise approximately $3.35 from Caucasian households. Both of these differences are statistically significant at the
p b 0.05 level. However, for brunette (and minority) solicitors the
returns to physical appearance are orthogonal to a potential
donor's race. Interestingly, the effect of increasing the beauty of
a blonde female is approximately 125.7% greater (509.7%
lower) than that for a brunette counterpart at households where a
Caucasian (non-Caucasian) answers the door.
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M.K. Price / Economics Letters 100 (2008) 351–354
4. Conclusions
This study examines how a cosmetic attribute – hair color –
impacts productivity in a door-to-door fund-raising experiment.
Empirical results suggest that returns to physical appearance
are, on average, greater for blonde females but depend critically
on characteristics of the potential donor. Further, the returns to
beauty for brunette solicitors accrue largely on the extensive
margin whereas the returns to beauty for blonde solicitors
accrue on the intensive margin.
References
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Hamermesh, Daniel, Biddle, Jeff, 1994. Beauty and the labor market. American
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Harper, Barry, 2000. Beauty, structure and the labour market: a British cohort
study. Oxford Bulletin of Economics and Statistics 62, 771–800.
Landry, Craig, Lange, Andreas, List, John, Price, Michael, Rupp, Nicholas,
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