LABOR READINGS

Laws of supply and demand determine wage structure; inequality exists due to productivity differences and varying returns to skills.
Wage dispersion reflects productivity differences among workers and the rate of return to skills, impacting the wage gap between skilled and unskilled workers.
The wage distribution in industrialized labor markets shows a long tail at the top, with a few workers earning a large share of rewards.
Income inequality in the U.S. rose in the 1980s, and no single factor fully explains the changes in the wage structure; changes in labor market institutions and economic conditions jointly contributed to this shift.
Wage differentials can persist across generations due to parental investments in children's human capital, creating a correlation between parent and child earnings.

The distribution of full-time weekly earnings illustrates wage dispersion and positive skewness, where most earn relatively low wages and a few earn disproportionately large rewards.
Wage distribution properties
- There is a lot of wage dispersion.
- The wage distribution is positively skewed with a long right tail.
There are significant differences in income distribution across countries; the top 10% of households in the U.S. earn 30% of total income, while the bottom 10% receive only 2%.
The human capital model is used to study wage distribution, considering differences in accumulated human capital and the returns from prior investments.
Workers invest in human capital until the marginal rate of return equals the rate of discount, leading to a positively skewed wage distribution even with a symmetric distribution of ability.
High-ability workers earn more due to their inherent productivity and greater acquisition of human capital. The positive correlation between ability and human capital investments "stretches out" wages, generating positive skewness.

Inequality in income distribution can be measured in several ways, often based on the share of income going to particular segments of the distribution.
Ranking all households according to their income level, from lowest to highest.
Population broken into five groups of equal size or quintiles.
Perfect income equality vs different quintiles' income.
Lorenz Curve - Cumulative share of income accruing to various groups.
- "perfect-equality" Lorenz curve must be a straight line with a $45 \degree$ angle.
- The actual distribution of household income in the United States as of 2006 shows variations from perfect equality.
The more inequality in an income distribution, the further away the actual Lorenz curve will be from the $45 \degree$ line
The Gini coefficient is defined as:
- $Gini coefficient = \frac{Area \ between \ perfect–equality \ Lorenz \ curve \ and \ actual \ Lorenz \ curve}{Area \ under \ perfect–equality \ Lorenz \ curve}$
- The Gini coefficient is 0 when the actual distribution of income exhibits perfect equality and would equal 1 when the distribution of income exhibits perfect inequality
- The Gini coefficient for household income in the United States is 0.43.
Additional measures of inequality include the 90-10 wage gap (range of income distribution) and the 50-10 wage gap (inequality between the "middle class" and low-income workers).

Dispersion in the wage distribution significantly increased in the U.S. during the 1980s and 1990s.
Wage gap increased between the high and the low paid.
Wage differentials widened among education, experience, and age groups.
Wage dispersion occurred even within demographic and skill groups.
The Gini coefficient rose dramatically after 1970, due to the widening of the 80-50 wage gap (stretching of income at the upper end).
The wage gap between college graduates and high school graduates rose dramatically, with college graduates earning 90% more than high school graduates by 2001.
The average 90-10 wage gap within a group of workers with the same age, education, gender, and race showed an upward trend, indicating increased wage dispersion within similar groups of workers.

The increase in wage inequality in the 1980s and 1990s has no single explanation; it was likely caused by concurrent changes in economic "fundamentals" and labor market institutions.
The labor supply and labor demand framework illustrates how shifts in these curves could have caused the increase in wage inequality with skilled and unskilled workers.
The relative wage of skilled workers increased due to a sizable increase in the returns to schooling. The structural changes in the U.S. labor market led to a historic increase in the rewards for skills