Why Beauty Matters An Experimental Investigation

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Why Beauty MattersAn Experimental Investigation

• Markus Mobius (Harvard University)
• Tanya Rosenblat (Wesleyan University)
• November 2004

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Is Beauty in the Eye of the Beholder?

• Surprisingly psychologists say No
• Strong agreement on what is considered
  beautiful in facial photograph ratings across
  genders and across cultures
• Therefore beauty can be measured (objectively)!

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Is Beauty in the Eye of the Employer?

• Extensive research on beauty in social psychology
  and human resource management
• In economics, Hamermesh and Biddle (1994) Beauty
  Premium
• Establish that looks matter even after
  controlling for many observable characteristics
  (actual labor market experience, years of tenure
  in a firm, union status, firm size, race,
  geographic location, fathers' occupation,
  childhood background, immigrant status of
  respondents and their parents and grandparents)

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Psychology Literature
I. How are beautiful people perceived by others?

• Attractiveness or Beauty-Is-Good Stereotype
  viewed superior along several dimensions
  personality traits (sociability, dominance,
  sexual warmth, modesty, character), mental
  health, intelligence and academic ability, and
  social skills

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Psychology Literature
II. To what extent is this stereotype true?

• Kernel of Truth Hypothesis
• Attractive people are treated better by others
  throughout their life cycle.
• Physical attractiveness rating does not change
  much throughout life cycle.
• A self-fulfilling prophecy? Become more
  confident and more persuasive

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Experimental Literature

• Physical attractiveness in Experiments
• Ultimatum Game (Solnick and Schweitzer (1999))
• Prisoners Dilemma (Mulford, Orbell, Shatto and
  Stockard (1998), Kahn, Hotes and Davis (1971))
• Public Goods (Andreoni and Petrie (2004))
• Trust Games (Eckel and Wilson (2004))
• Dictator Game

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How does beauty affect wages?
Decompose the effects of beauty

• Becker-type discrimination (employers have a
  taste for good-looking employees)
• Ability Effect - more physically-attractive have
  superior skills at performing a task
• Stereotype, Confidence and Persuasion Effects
  during wage negotiation process

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How does beauty affect wages?
Wage Negotiation

• Worker forms a belief about his own ability
• Confidence Channel raises worker confidence in
  his ability

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How does beauty affect wages?
Wage Negotiation

• Employer forms a belief about workers ability
• Visual Stereotype Channel raises employer
  belief about worker ability directly (because
  beauty is good)
• Oral Stereotype Channel raises employer belief
  indirectly during verbal interaction through
  characteristics correlated with beauty

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Wage Negotiation
Employers belief about workers ability
Workers belief about his ability
Visual Interaction
Oral Interaction
Workers Confidence
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Wage Negotiation
Employers belief about workers ability
Workers belief about his ability
Visual Interaction
Oral Interaction
Workers Confidence
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Wage Negotiation
Employers belief about workers ability
Workers belief about his ability
Visual Interaction
Oral Interaction
Workers Confidence
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Wage Negotiation
Employers belief about workers ability
Workers belief about his ability
Visual Interaction
Oral Interaction
Workers Confidence
Final Wage
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Wage Negotiation
Employers belief about workers ability
Workers belief about his ability
Beauty signals higher ability
Visual Stereotype (directly)
Oral Stereotype (indirectly)
Confidence Channel Beautiful more likely to be
confident
Final Wage
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Experimental Design
Job Description

• Employees were hired to perform a skilled task
  of solving Yahoo! mazes for 15 minutes.
• Before interviews they had a chance to solve a
  practice maze of level Easy
• During employment period they solved mazes one
  level of difficulty higher

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Experimental Design
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Experimental Design
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Experimental Design
Why Mazes?

• We would not expect beauty to be directly
  productive for this task. We can therefore focus
  on worker/employer interaction alone
• The task requires true skill. Gneezy, Niederle
  and Rustichini (2003) have shown that there is
  considerable variation in skill and speed of
  learning for performing this task.

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Experimental Design

• Neither worker nor employer have well defined
  focal points for predicting future performance if
  presented with the practice time.
• There is a significant amount of learning
  possible in performing this task during the
  allocated 15 min time period.
• This allows for overconfidence effects and also
  for true persuasion a confident worker might
  truly believe that she can solve many mazes even
  though she did poorly in the practice round, and
  possibly can convince the employer to believe her.

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Experimental Design

• Playing the main game at the next level of
  difficulty opens room for additional uncertainty
  and thus further over-confidence and persuasion
  effects.

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Experimental Design
Each worker enters her resume information

• College major, name of the degree granting
  institution, matriculation year, hobbies, team
  sports, age, gender, dream job, the number of
  jobs previously held, the number of job
  interviews they have participated in, and whether
  they have internet connection at home (income
  proxy)
• Time it took to complete the practice round

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(No Transcript)
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Experimental Design
In addition,

• Each worker is asked to form an estimate of how
  many mazes she will be able to solve in 15
  minutes
• This information is only provided for the
  experimenter and is not revealed to the
  employers.
• Compensation is structured in an incentive
  compatible manner to induce workers to truthfully
  reveal their estimates.
• Workers and employers complete a control
  questionnaire to make sure they understand how
  payments are calculated.

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Experimental Design
Each worker participates in 5 treatments in
random order

• Treatment A Resume only without a facial
  photograph.
• Treatment B Resume and facial photograph.
• Treatment C Resume without a photograph and oral
  telephone communication.
• Treatment D Resume with a facial photograph and
  oral telephone communication.
• Treatment E Resume with a facial photograph and
  face-to-face interview.

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Wage Negotiation
Employers belief about workers ability
Workers belief about his ability
Visual Stereotype
Treatments B, D, E
Oral Stereotype
Confidence Channel
Treatments C, D, E
Treatments C, D, E
Final Wage
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Timing

• Stage 1

Workers enter resume info
Workers solve practice maze
Workers form their confidence estimates
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Timing

• Stage 2

Workers interact with employers (C,D,E) or
employers review workers files (A, B) each
employer sees 5 candidates
Employers find out whether their productivity
estimate will be used to pay workers (80 of the
time)
Employers set their estimates of workers
productivity (wages) after having seen all 5
candidates
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Timing
Why is employer wage used only in 80 of the
cases?

• Stage 2

Workers interact with employers (C,D,E) or
employers review workers files (A, B) each
employer sees 5 candidates
Employers find out whether their productivity
estimate will be used to pay workers (80 of the
time)
Employers set their estimates of workers
productivity (wages) after having seen all 5
candidates
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Timing
Why is employer wage used only in 80 of the
cases?

• Stage 2

Workers interact with employers (C,D,E) or
employers review workers files (A, B) each
employer sees 5 candidates
Employers find out whether their productivity
estimate will be used to pay workers (80 of the
time)
Employers set their estimates of workers
productivity (wages) after having seen all 5
candidates
To distinguish between (a) Employers choosing to
transfer some money to workers independent of
their skill and (b) Compensation for perceived
skill
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Experimental Design

• Use this to check for direct taste-based
  discrimination
• Also tests whether subjects are playing a larger
  supergame.
• Note that all workers are hired, but get
  different compensation.
• Wages are paid by the experimenter. The job of
  employers is to determine productivity.

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Timing

• Stage 3

Workers participate in 15 min work period
Compensation is determined for workers and
employers
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Compensation of Workers
Workers get a wage determined by each employer.
(used 80 of the time 20 of the time the wage
is set by the experimenter) all wages are paid
by the experimenter.
40 points are subtracted from workers
compensation for each maze they mispredict (above
or below their estimate). This provides a
marginal incentive of 60 points per maze to
continue solving mazes even after they hit their
estimate.
Workers get a piece rate of 100 points for each
maze they solve during 15 min work period


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Compensation of Workers
How do employers set wages?
Workers get a wage determined by each employer.
(used 80 of the time 20 of the time the wage
is set by the experimenter) all wages are paid
by the experimenter.
40 points are subtracted from workers
compensation for each maze they mispredict (above
or below their estimate). This provides a
marginal incentive of 60 points per maze to
continue solving mazes even after they hit their
estimate.
Workers get a piece rate of 100 points for each
maze they solve during 15 min work period


During the interview and resume review they form
an estimate of how many mazes each candidate can
solve. This number times 100 points becomes
employee wage in 80 of cases experimenter sets
an average wage.
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Compensation of Employers
Regardless of whether employer wage is used or
not 40 points are subtracted from employers
compensation for each maze they mispredict (above
or below their estimate for each employee).
Employers get a fixed fee of 4000 points

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Experimental Design
Beauty Ratings

• By a panel of 50 independent evaluators on a
  scale from 1 to 5
• 1 - homely, far below average in attractiveness
  2 - plain, below average in attractiveness 3 -
  of average beauty 4 - above-average and 5 -
  strikingly handsome or beautiful.
• Standard passport-type photographs were presented
  to evaluators in random order via a website.

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Subjects

• Undergraduate and masters students from Tucuman
  University, Argentina
• instructions in Spanish delivered orally and via
  a computer
• subjects completed a control questionnaire to
  ensure understanding of compensation schemes
• 33 sessions of 5 workers and 5 employers each
  worker being reviewed by 5 employers (825
  observations)

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Subjects

• Subjects were paid 12 pesos for participation
  additional earnings described above
• Average earnings 25 pesos for an experiment of up
  to one and a half hours in length.
• Made sure subjects did not know each other prior
  to the experiment.

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Employee Subject Pool Description

• Subjects from 3 university campuses, 85 from UNT
  
• 56 male
• Average age 22.9 more graduate students
• Majors business and economics (21) science,
  medicine, and information technology (46)
  humanities and arts (33)
• 51 have internet access at home (80 from
  private 41 from public)

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Employee Subject Pool Description

• 61 participated in team sports
• 43 had no previous work experience (out of them
  63 never interviewed for a job)
• Those with work experience worked in education,
  information technology, retail sales, business,
  public sector, arts, food production and service,
  and industry.
• Intensity of interpersonal interaction on a job
• Hobbies in computers, recreation (listening to
  music, reading), creative tasks (writing,
  drawing, composing music), sports

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Average Performance

• The mean number of mazes solved was 9.5 (10.9 for
  men 7.8 for women)
• The average maze during 15 minute trial took 94
  sec the average practice time was 127 sec
• Subjects systematically underestimated their own
  productivity by 24 on average.
• Employers underestimated workers productivity in
  a similar manner (20 on average).

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Variable Transformations
Confidence Measure

• Estimated number of rounds (ln)

Ability Measure

• Actual number of rounds (ln)

Prediction based on extrapolation from the
practice round

• Ln (1560/Practice)

Becker Discrimination

• SETWAGE1 if employer estimate was used to
  determine workers wage

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Beauty Measure
Detrend beauty ratings to get rid of measurement
error

• Measurement error arises because each rater has a
  distinct definition of baseline beauty
• Formally, for each rater we take her average
  beauty rating and subtract it from each raw
  rating for subject in order to define the
  centered rating
• The measure BEAUTY for subject is then defined as
  the mean over all raters centered ratings.

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Procedure for Data Analysis

• 1. Relationship between beauty and ability
• 2. Relationship between beauty and confidence
• 3. Wage regressions without controlling for
  confidence
• 4. Wage regressions with a control for confidence
• 5. Pooled Regression

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Beauty and Ability

• After controlling for all labor market
  characteristics, find no evidence of a
  relationship between actual ability during 15 min
  work period and physical attractiveness.
• There is also no evidence of a relationship
  between projected ability using practice time and
  physical attractiveness.

Therefore, a beauty premium in this setting is
NOT a (maze-solving) skill premium!
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Confidence and Beauty

• There is a strongly significant (at the 1 percent
  level) effect of physical attractiveness on
  confidence. Raising beauty by one standard
  deviation increases confidence about 13.
• This effect is very large if we define a
  beautiful person to be one standard deviation
  above the mean and a plain person to be one
  standard deviation below then the plain subject
  is about 26 less confident than the beautiful
  subject.
• Interestingly, there is no difference in
  confidence between men and women in this setting
  (once we control for actual ability).

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Wage regressions (w/o confidence)

• Regressions of wages on workers characteristics
  including BEAUTY but excluding CONFIDENCE.
  (Separate regression for each treatment).
• First of all, there is a beauty premium in our
  experiment in all treatments except A ranging
  from 12 to 17 with CV controls.
• There is no evidence for direct taste-based
  Becker-type discrimination

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Wage Regressions (w/ Confidence Controls)

• Same as regressions before but with an additional
  control for confidence.
• As expected, confident subjects only do better in
  treatments with oral communication.
• A 1 increase in confidence raises wages by about
  0.18 to 0.33.
• The beauty effects in treatments C to E are
  smaller by about 2 to 4. This decline is
  consistent because we know that one standard
  deviation in beauty increases confidence by about
  13.

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Confidence channel
Wage increases for one standard deviation
increase in beauty
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Pooled Regression

• Visual Stereotype Channel - 7.2 wage gain for
  each standard deviation in beauty
• Oral Stereotype Channel - 10.4 wage gain for
  each standard deviation in beauty
• Confidence Channel - raises wage by .3 for each
  1 increase in confidence. This translates into
  3.6 increase in wage for one standard deviation
  increase in beauty

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Wage Negotiation
Employers belief about workers ability
Workers belief about his ability
7.2 gain for 1 standard deviation increase in
beauty
Visual Stereotype
10.4 gain for 1 standard deviation increase in
beauty
Oral Stereotype
Confidence Channel
3.6 increase in wage for 1 standard deviation
increase in beauty
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Policy Implications

• Job interviews are currently the most common
  method of employee selection.
• Direct discrimination can be minimized by
  reducing face-to-face interactions and relying on
  telephone interviews instead or hard data like
  test scores.
• For example, Goldin and Rouse (2000) have found
  that blind auditions reduce gender discrimination
  in hiring women musicians.
• We find that blind interview procedures (like
  telephone interviews) can reduce beauty premium
  by 40 (due to elimination of direct stereotype
  effects).
• Elimination of oral interaction can eliminate
  beauty premium completely. Too drastic

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What We Dont Know

• Is taste based discrimination present in repeated
  relationships?
• Do students care more about physical
  attractiveness than older human resource
  officers?
• Are employers over-interpreting visual and audio
  stimuli because those can be productive in most
  other environments?
• Can we design an experiment in which
  self-confidence of workers is payoff-relevant for
  employers?
• Is underperformance of females in part due to
  different responses to goal-setting?