Beauty and the Labor Market

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Beauty and the Labor Market

• Daniel S. Hamermesh and Jeff E. Biddle, American
  Economic Review, Vol. 84, December 1994,
  pp.1174-1194.

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Do Attractive People Earn More Than Less
Attractive People?
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The Model

• Dependent Variable
• Log(Hourly Earnings)
• Explanatory Variables
• Experience
• Marital Status (1 if Married, 0 if Not)
• Education (vector of dummy variables)
• Industry
• Self Reported Health Status
• Race
• Region
• Union Membership

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Dummy Variables

• Intercept Dummy
• YabXcD where D 0 or 1
• Slope Dummy
• YabXcDdDX where D0 or 1

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The Impact of Looks on Employees Earnings QES,
1977
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Does Beauty Matter?

• For Men, coefficient on below average looks is
  statistically significant t3.57.
• For Women, coefficient on below average looks is
  not statistically significant at 5 t1.89.
• Coefficients on above average looks are not
  statistically significant for this data.

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Joint Tests on Several Regression Coefficients

• Set Up the Null and Alternative Hypotheses
• Choose level of significance and critical F value
• Run two regressions and obtain estimated F-value
• Restricted model assumes bs0
• Unrestricted model assumes bs ? 0
• Apply the decision rule

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F Statistic
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Null Hypothesis Looks Do Not Matter
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Do Attractive People Earn More Because They Are
More Productive?
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Three Reasons Why Looks Will Affect Pay

• Consumer Discrimination/Productivity

• Employer Discrimination

• Occupational Crowding

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Sorting, Looks and the Determination of Earnings
QES, 1977
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Important to Remember

• Use of slope dummy variables
• Use of economic analysis to develop testable
  hypotheses that allow one to distinguish among
  competing explanations for the empirical
  observation
• Use of F-test to test joint hypotheses involving
  regression coefficients