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Chapter 16: The Personal Distribution of Earnings

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1. Describing the Distribution of

Earnings

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Annual Earnings Distribution, 2002

• The distribution of personal earnings among full-time workers is highly unequal and

skewed right.• The distribution is

characterized by (1) much bunching around the leftward mode, (2) and

extended rightward tail, (3) a mean, $40,140, that exceeds the median, $30,000, (one-half above, one-half below).

0

2

4

6

8

10

12

Mil

lion

s of

Wor

kers

5 15 25 35 45 55 65 75 85 95

Thousands of Dollars

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Lorenz Curve• The Lorenz curve provides a

summary of the earnings distribution.

• The straight red line represents perfect equality in the earnings distribution. Twenty percent of all earners get 20 percent of all earnings, 40 percent of the workers would get 40 percent, etc.

• The curved blue line illustrates a Lorenz curve. The curve shows that lower income workers do not a proportionate share of all earnings.

• The greater the area between the line of perfect equality and the Lorenz curve, the more unequal the distribution of earnings.

Perc

ent o

f F

ull-

tim

e E

arni

ngs

Percent of Full-time Workers

Perfect Equality

0

100

100

Lorenz Curve

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Distribution of Annual Earnings, 2002

• The distribution of personal earnings among full-time workers is highly unequal as the highest 20% of earners received 46.5% of all earnings.

0%5%

10%15%20%25%30%35%40%45%50%

Per

cen

t of

All

Earn

ing

s

Bottom20%

Second20%

Third20%

Fourth20%

Highest20%

Income Quintile

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The Gini coefficient provides a way to quantify the Lorenz Curve.

Gini Coefficient

GiniCoefficien

t

=area between Lorenz curve and diagonal

total area below diagonal

The Gini coefficient ranges between 0 (perfect equality) and 1 (perfect inequality). The Gini coefficient in 1999 was .39

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Full versus part-time workers The previous data only includes full-time

workers. If part-time workers were included income

variability would increase. Fringe benefits

The previous data did not include fringe benefits.

If fringe benefits were included income inequality would increase since those with high incomes also have high fringe benefits.

Cautions

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Individual versus family income. The previous data is based on individual

income. The mean and median of the family income

distribution is higher. The family income distribution is more equal

since the wives of high-income men are less likely to work due to the income effect.

Static portrayal These income distribution don’t give

information about changes in the distribution

Cautions

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Other income sources High wage income persons tend to higher

rental, interest, and dividend income. Including these sources increases inequality.

Low wage income persons are more likely to get income transfers such as welfare. Including these sources decreases inequality.

If all other income sources are included, then the income distribution becomes more equal. The income transfer effect is stronger.

Cautions

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2. Explaining the Distribution of

Earnings

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Formal education Higher quality and quantity of formal

education leads to greater earnings. Differences in ability, discrimination, cost of

funds, individuals differ in the amount education they acquire. This leads to differences in earnings.

On-the-job training More on-the-job training increases earnings. On-the-job training helps explain why older

persons have higher earnings.

Human Capital Theory

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Persons with more formal education get on-the-job training and thus expands their earnings differentials with less-educated workers.

Workers with on-the-job training tend to work more hours per year and thus the variance in annual earnings.

Human Capital Theory

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Ability Direct effect

Persons with greater ability will have greater earnings due to their greater productivity.

Complementary effect If elements of ability are complementary

(e.g., IQ and motivation), then they will have a multiplicative rather than an additive effect on earnings.

Human capital effect Persons with more ability will get more

education and thus increase earnings inequality.

Modified Human Capital Theory

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Family background Direct effect

A child born into a family with a family-owned business is likely to employed in the family business and have higher earnings later in life.

Families with “good connections” may be able to help their children get high-paying jobs with friends and associates.

Human capital effect High income families can more readily

provide formal education for their children.

Modified Human Capital Theory

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Discrimination Discrimination increases earnings inequality

several ways: Lowers the earnings of women and

minorities. Occupational segregation raises the earnings

of males and whites as well as lowering the earnings of women and minorities.

Poorer black children tend to attend worse schools and are less likely to go to college.

Modified Human Capital Theory

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Chance and risk taking Luck and risk taking place a role in the

unequal distribution of earnings. A few high paying positions such as a

professional athlete, rock star, best-selling authors, CEO etc.

• This leads to an unequal distribution of earnings since only a few people who try succeed, many fail, and even more don’t try.

Random luck determines who gets a high wage offer in the distribution of earnings for a given occupation.

Modified Human Capital Theory

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Questions for Thought:1. Speculate as to how successful attempts by the

government to tighten the distribution of family income through transfers might inadvertently make the distribution of annual earnings more unequal.

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3. Mobility Within the Earnings Distribution

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Earnings rise with age and then fall near retirement.

Even if everyone had the same earnings stream over their career, we would still observe annual earnings inequality since the work force consists of workers of different ages.

The inequality in annual earnings overstates the inequality in life-time earnings.

Life-Cycle Mobility

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There is a lot of churning or year-to- year movement across earnings categories independent of life cycle effects.

The earnings mobility rates are lower for blacks than whites and less in the lowest and highest earnings categories.

Churning

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Questions for Thought:1. Critically evaluate this statement: “Lifetime

earnings are less equally distributed than annual earnings.”

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4. Rising Earnings Inequality

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Wage Inequality, 90-10 Ratio

0.00.51.01.52.02.53.03.54.04.55.0

1973 1978 1983 1988 1993 1998

90-1

0 R

atio

Male Female

• The 90-10 ratio is earnings at the 90th percentile divided by earnings at the 10th percentile.

• Earnings inequality has risen for both men and women.

• Earnings inequality grew most rapidly between 1979 and 1989.

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Deindustrialization Employment has shifted to the low wage and

high variance service sector. The employment shift to services can only

explain a small part of the rise in inequality. Import competition and the decline of

unions Increased import competition and the

associated decline in unionism has lowered the wages of less-educated workers and thus raised inequality.

Why the Increase in Earnings Inequality?

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Increased demand for skilled workers The demand for skilled workers has risen

relative to less-skilled workers, which has increased inequality. The demand for skilled workers has risen

within industries as firms have adopted new technologies.

Product demand has shifted across industries towards high-tech industries that employ more skilled workers.

Why the Increase in Earnings Inequality?

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Demographic changes The entrance of less-skilled baby boomers

and female workers during the 1970s and 1980s may have increased inequality between new and experienced workers. The increased labor supply may increased the

share of low-wage workers in all industries. The increased labor supply may increased the

wages of workers in low-wage labor markets. It is likely that labor supply shifts played a

small role since most of the increase in inequality has been within each age group.

Why the Increase in Earnings Inequality?

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EndChapter 16