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Discrimination

Discrimination. Theory and Measurement. Original Theories. Marxist: Discrimination a Smoke Screen Capitalists want to divide proletariat Do so by Race, Sex, Ethnicity Could be anything (earlobes?) Keeps workers at each others’ throats And away from their own Psychological: A mistake

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Discrimination

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  1. Discrimination Theory and Measurement

  2. Original Theories • Marxist: Discrimination a Smoke Screen • Capitalists want to divide proletariat • Do so by Race, Sex, Ethnicity • Could be anything (earlobes?) • Keeps workers at each others’ throats • And away from their own • Psychological: A mistake • People don’t know truth about others • Just have to educate them

  3. Neoclassical Theory • Basis of what we shall do • What’s your favorite flavor of ice cream? • Why? • Can we make you change your mind? • Prejudice is a taste • Discrimination is indulging that taste • Comes at a cost

  4. Suppose I am Prejudiced w • I don’t like blondes! • Employing them brings a psychiccost • As if paying them more • wB=(1+d)w0 • Demand falls • D’ feels like D • Let’s act this out wB D w0 D’ QB

  5. Impact on Market • How do blondes respond? • Offer to work for less • Wage falls • What do employers do? • Restrict choice of employees • Productivity of favored workers may fall • Forced to employ less productive workers • Wages of favored workers driven up • Supply of qualified workers artificially restricted

  6. Who Gains and Who Loses? • Blonde workers lose • Fewer employed • Wages lower • Other workers win • More employed • Perhaps less qualified • Wages higher • Employers?

  7. What About Employers? • Trade off profit & distaste for blondes • U=U(p,B) • Indifference Curve • p higher if hire blondes • Lower pay • Better Workers • Sacrifice profit to indulge taste for discrimination p Blondes

  8. Another Beneficiary • Non/Less discriminatory employers • Hire more qualified employees for less • What happens as more of them enter? • Wage of blondes driven up • Perfect competition eliminates discrimination

  9. Application to Sports • What of 1964 Alabama football team? • Very good – and very white • But ‘Bama started losing to integrated teams • Sam “Bam” Cunningham of USC scores 5 TD’s against them on national TV • Cost became too great • Sports became most integrated part of UA • Bob Gibson and his (black) landlady • Spring housing segregated in early 1960s • Hated her for charging high rent • Why does discrimination persist?

  10. Monopoly Power • Baseball has legal cartel • Policed by commissioner • Teams tried to cheat: Cubans & Indians • Bill Veeck foiled in 1943 • Jackie Robinson reintegrated baseball • Moses “Fleetwood” Walker in A.A. in 1880s • Integrated teams tended to dominate • Dodgers, Giants, Indians, & Braves • Red Sox & Phillies last to integrate • Great Celtic teams built on integration

  11. Employee Discrimination • Workers don’t like to work with blondes • Feel psychic cost: w = (1-d)w0 • Demand higher pay to work with blondes • What would employer do? • Segregation vs Discrimination • Dodgers protested Robinson’s presence • Got Al Gionfriddo partly to take next locker

  12. Customer Discrimination • Separates discrimination from prejudice • Employer punished for tolerance • George Preston Marshall & NFL’s Redskins • Last NFL team to integrate: 1962 • “Burgundy, Gold, and Caucasian” • Forced by U.S. government • Facility on government land • One key to intransigence: Southern audience

  13. Statistical Discrimination • Also separates from prejudice • Reminiscent of psychological approach • May feel that blondes less productive • Why different from saying dropouts worse? • “Flashy Frenchmen” in the NHL • Felt that Francophones not tough • Europeans & Flyers

  14. bMeasuring Discrimination • Motivating question: • How can blacks in NBA be victims when • 80% of NBA black • Make 20% more • All else not equal • How to hold all else equal? • Key technique: Multiple regression • S=b0 + b1X1 + b2X2 + …+ bnXn +e

  15. Regression and Discrimination • Coefficient: impact of Xi with all other X’s constant • Corresponds to economic definition of discrimination • Holds all else equal • What would X’s be for NBA? • How to explain that blacks make more? • True impact of race unclear

  16. Sexual Discrimination • Harder to measure • Men & Women seldom in same venue • Often don’t play same sport • Even same sport may vary • Tennis, figure skating, & “women’s basketball” • Direct competition?: Jockeys & auto racing • Women not always victims • Gymnasts and figure skaters

  17. Title IX • Part of 1972 Education Amendments • Mandated equal access & opportunities for women in federally funded education programs • 3 ways to comply • Funding proportional to enrollment • Show history of expansion • Interests of students accommodated • Few programs in compliance • But NCAA certifies all

  18. Impacts of Title IX • Good • Spurred rapid growth in women’s sports • Though most of growth early on • Gave grounds to seek remediation (TU!) • Bad • What happened to women coaches? • Was ~80% of women’s programs - now ~ 44% • Women’s programs lose money • Can meet in many ways – • Cut men’s programs rather than expanding women’s

  19. A Problem • Bernie Williams • Star player for Yankees • What is he? • Hometown: San Juan • How to classify? • Ask player? • Ask owner? • Ask fans?

  20. Puzzling Numbers From Track • Asians ~ 57% of world’s population • Only impact in marathon • Blacks ~ 12% of world’s population • 95% of best 100m times of West African ancestry • ~8% of world’s population • All 32 finalists in last 4 Olympics • North Africa dominates middle distance • East Africa dominates distance

  21. Astonishing Kenya • More than half of top 100 5K & 10K times • Top 60 times in steeplechase • Won every World Cross Country Championship since 1986 • 38 Olympic track medals since 1964 • 13 golds in men’s races • Only U.S. (with 10X as many people) has more

  22. More on Kenya • 75% of Kenya’s runners from Kalenjin • Highlands near Lake Victoria • 50% of these from Nandi district • 1.8% of Kenya’s population • 20% of winners of major distance runs • Not due to better facilities • Other nations also have altitude

  23. Discomfort with Genetics • Intelligence as subtext • Demeans accomplishments? • “Natural” black v. “hardworking” white • Demeans blacks in other fields? • “Naturally” better in some areas => worse in others? • Some get brains – others brawn

  24. An Alternative Explanation • Hoberman: Darwin’s Athletes • Blacks once considered ill-suited for athletics • Analog to women? • Opposite stereotype of today • Considered physically fragile & weak-willed • Now see athletics the best route to success • Survey: More black youths optimistic about chances at athletics than in professions • Only ethnic group to think so

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