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CHAPTER 7

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“What makes equality such a difficult business is that we only want it with our superiors.”

-Henry Becque

Some workers earn more than others.

Differences in productive skills

Differences in the rate of return to these skills.

Compensating wage differences.

Discrimination

Unionization

What factors contribute to the shape of the distribution of earned income?

The distribution of earned income is positively skewed; i.e., there is a long right tail in this distribution.

A small percentage of all workers earn a disproportionately large share of the labor-market rewards for working.

Earnings differences across individuals exist due to:

Human capital investments that vary from worker to worker.

Age differences. (Young workers are still accumulating human capital, while older workers are collecting returns from earlier human capital investments.)

There is a positive correlation between ability and human capital investments, which “stretches out” the distribution of earnings in the working population.

Rate of Interest

MRRL

MRRH

MRR*

r

H*

HH

HL

Human Capital

The perfect-equality Lorenz curve is given by the line AB, indicating that each quintile of households gets 20 percent of aggregate income. The actual Lorenz curve describes the actual income distribution. The ratio of the shaded area to the area in the triangle ABC gives the Gini coefficient.

- The Gini coefficient:
- Increases as inequality increases.
- Summarizes the entire income distribution with a single number between 0 (perfect equality) and 1 (perfect inequality).

- Wage gaps are wage ratios between different percentiles in the distribution.
- Calculating Common Wage Gaps
- The 90-10 Wage Gap is the difference in the 90th and 10th percentiles as a percent of the 10th percentile wage, or (w90 – w10)/w10
- The 50-10 Wage Gap is the difference in the 50th and 10th percentiles as a percent of the 10th percentile wage, or (w50 – w10)/w10

The gap between those at the top of the earnings distribution and those at the bottom widened dramatically.

Earnings differentials widened across education groups, experience groups, and age groups.

Earnings differentials widened within demographic and skill groups.

Increasing technological change increased the productivity of skilled workers relative to unskilled workers.

Demand for skilled workers increased relatively more than demand increased for unskilled workers.

Increased international trade: imported goods substitute for domestic production by unskilled workers.

Demand for skilled workers increased relatively more than demand increased for unskilled workers.

Increasing technological change increased the productivity of skilled workers relative to unskilled workers.

A decrease in the supply of skilled workers or an increase in the demand for skilled workers could cause a widening of the wage gap.

Relative Wage of Skilled Workers

S1

S0

r1

C

r0

A

D1

B

D0

p0

p1

Relative Employment of Skilled Workers

The downward-sloping demand curve implies that employers wish to hire relatively fewer skilled workers when the relative wage of skilled workers is high. The perfectly inelastic supply curve, S0, indicates that the relative number of skilled workers is fixed. Initially, the labor market is in equilibrium at point A. Suppose the relative supply of skilled workers increases to S1. The rising relative wage of skilled workers can then be explained only if there was a sizable outward shift in relative demand from D0 to D1 (ending at point C).

Supply shifts.

Increased international trade.

Skill-biased technological change.

Institutional changes in the U.S. labor market.

Decline in Unionization

Decreases in the Inflation-Adjusted Minimum Wage

The superstar phenomenon – a few persons in some professions have very high earnings and dominate their fields: athletes, actors, musicians, authors

Even if a “job” is the same, individuals bring different skills to these same jobs.

There is a positive correlation between the labor-market skills, and earnings, of parents and their children.

High-income parents typically invest more in the education of their children than do low-income parents.

However, there is a tendency for income differences across families to get smaller over time (“regression toward the mean”).

Earnings of Children

A, Slope = 1

C, Slope is between 0 and 1

B, Slope = 0

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Earnings of Parents

The slope of the regression line between child earnings and parental earnings is the intergenerational correlation. If the slope equals 1, the parent’s earnings persists entirely into the next generation, and there is no regression toward the mean. If the slope equals 0, the earnings of children are independent of the earnings of their parents, and there is complete regression toward the mean.

The quality of the social environment in which a child grows up helps determine the acquisition of human capital.

Quality of the residential neighborhood.

Importance of religious organizations.

Socioeconomic background of peers, such as neighbors and classmates.