Wage inequality trends and explanations
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  • 1. Wage Inequality trends and explanations Economics 380
  • 2. The U.S. wage distribution (2002)
    • The wage distribution is positively skewed (long right tail)
    • A small percent of workers earn disproportionately large shares of the rewards for work
  • 3. Just the facts
    • Full-Time, Year-Round Workers, 1963-2003, Gini Coefficient
  • 4. Facts cont’d
    • Full-Time, Year-Round Workers, 1963-2003, 90-10 Wage Gap
  • 5. Facts cont’d
    • Full-Time, Year-Round Workers, 1963-2003, 50-10 Wage Gap
  • 6. In real wage terms
  • 7. Extending backwards
    • It is harder to get data per 1960. There is some census data back to 1940 (very noisy) that gives us some idea. Previous to that we can speculatively get the share of the richest 10%.
  • 8. Further back
  • 9. Compared to other countries
  • 10. Between groups inequality
    • The rise in relative wage inequality in the United States, beginning in the late 1970s, seems to match the pattern on the rise in the college premium (or rise in the return to education). This rapid increase in the college premium is widely interpreted as evidence that labor market forces were driving up the price of skills.
    Wage Differential Between College Graduates and High School Graduates, 1963-2001
  • 11. Model
  • 12. Results
    • Assume we are in a competitive equilibrium (to a first approximation)
    • This implies all factors are paid their marginal product. This leads to the following prediction about the wage ratio’s between high and low “skill (here education)
  • 13. Predictions
    • Given the model what could we expect to explain the changes?
      • Relative supply has changed?
      • Relative demand has changed?
      • Substitutability has changed?
      • Something outside the model has changed. This is usually thought of as some group of institutions (i.e. decline of unions).
  • 14.  
  • 15. Immigration?
    • Decline in immigrant human capital by cohort (Borjas)
    • He claims 25% can be explained – probably more like 15%.
    • Explains much more of the tail fall in low skilled wages than the rise in high skilled
  • 16. Relative supply insourcing (Trade)
    • In the U.S., for example, the value of trade (an average of imports and exports) was 6.1% of GDP in 1913, but only 4.1% in 1970, rising to 8.8% in 1980.
    • Much of the increase is trade with Less Developed countries (LDC’s) – 40% of all imports by 1996.
    • The timing of the recent increase is coincident with rise in earnings inequality in many countries.
    • These facts raise the logical question of whether international trade is responsible for the growth in the relative earnings of skilled workers during the 1980s.
  • 17. Demand Side
    • Given the failure of supply side explanations, most economists came to believe that a majority of the change in inequality was due to factors that increased the relative demand for skilled (by which they meant educated) workers.
    • This makes intuitive sense, since supply of skilled workers has risen and their wages have risen demand must be rising also.
    Relative Wage of Skilled Workers Relative Employment of Skilled Workers A S 1 S 0 D 0 D 1 B C p 0 p 1 r 0 r 1
  • 18. What is SBTC?
    • Why? Well, the most likely demand shock would be due to technology, thus the theory of Skill Biased Technological Change (SBTC).
    • There are various SBTC formulations but at their heart they all contain two similar elements.
      • Technology increases the productivity of college grads more than high school grads (In our model the skilled θ increases in relative terms). Usually this is because educated labor and capital are complements, also frequently capital and low educated labor are viewed as substitutes.
      • Some “new” type of technology caused this skill bias to accelerate in the mid to late 1970’s. After looking at technological adoption during that time, the consensus suspect is Information Technology as embodied by computer microprocessors and their offspring technologies.
  • 19. Evidence against
    • This predicts that college workers should on average become more productive, especially in the late 70’s early 1980’s. Not born out by productivity data.
    • Timing problems, most computerization of industries is late 80’s-90’s, while inequality was increasing long before that.
    • Industries investing more in computers during the 1980s were already experiencing more skill upgrading during the 1960s, before the arrival of computers.
    • It’s a black box – no direct measure of skills.
  • 20. Aside: do computers raise wages?
    • Krueger (1993) – Yes by a lot
      • He regresses wage on controls and the binary “do you use a computer at work”
      • What might be wrong with this causal inference?
    • Dinardo & Pischke (1997) the binary “do you use a pencil at work”
  • 21. A new generation – putting the skill back in SBTC
    • Many of these issues stem from the education=skill oversimplification. In fact wage inequality within education groups increased sharply in the late 1970’s-80’s, suggesting education may be a poor proxy for skill.
    • The response “occupation biased technological change”
  • 22. Skills in the labor market
    • Consider a continuum of jobs circa 1960 in the labor market, indexed by wage.
      • At the low wage end you have jobs like custodial, manual labor, truck driving.
      • In the middle you have high paying blue collar jobs, auto worker, steel worker, and clerical professions like secretaries.
      • At the top you have professionals like doctors, writers, professors, etc.
    Wages rise Middle: blue collar, clerical High: doctors Low: manual labor, custodial
  • 23. Skills in the labor market 2
    • What skills do these jobs require:
    • Low – manual dexterity, sensory perception
    • Middle – ability to follow complicated rules, reliability
    • High – Abstract thought, communication
    Computers role in this: Can’t do these “skills” neither a substitute nor complement Good at following rules and reliability, substitutes Bad at abstract thought, but good at managing data to aid – likely complements.
  • 24. So what happens
    • Many of the middle wage jobs vanish – replaced by computers or automation more generally.
    • Their occupants don’t have the skills for high wage jobs, so they go into low wage retail, etc. Increase supply and thus lower wages there
    • High wage jobs see complementarities from computing and wages rise.
    • Evidence is this is exactly what happened and it explains a large portion of inequality increase.
  • 25. Evidence
  • 26. One more possibility - institutions
    • Unions – as unions get weaker (24 percent of workers in 1973 – 13 percent in 2002) the wages of low skilled are pushed down.
      • Could explain at most 8-10% of the change.
    • Minimum wage – probably not an important factor as it only effects the very bottom of the distribution where a majority of the action is at the top.
  • 27. The meaning
    • Is income inequality the right measure?
      • Consumption
      • Lifespan
      • Enjoyment
    • Is wage income really the useful measure
      • Not a life cycle measure
      • Government transfers
  • 28. Keeping it real