Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Chapter 7 The Wage Structure

7-2 Introduction Some workers will earn more than others. –Productivity differences. –Rate of return to skills differs. Wage structure: factors that contribute to the shape of the wage distribution.

7-3 The Earnings Distribution The wage distribution is positively skewed. –A long right tail. A small percent of workers earn disproportionately large shares of the rewards for work.

7-4 The Wage Distribution in the United States, 2006

7-5 Facts About the Earnings Distribution Wage differentials 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 investments.) A positive correlation between ability and human capital investments, which “stretches out” wages in the population.

7-6 Income Distribution When Workers Differ in Ability r H*H* HLHL H Rate of Interest MRR * MRR L MRR H Human Capital

7-7 Measuring Inequality: The Lorenz Curve and the Gini Coefficient 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.

7-8 Measuring Inequality: The Gini Coefficient and Wage Gaps 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 provide wage ratios between different percentiles in the distribution Wage Gap = 90 th percentile wage ÷ 10 th percentile wage Wage Gap = 50 th percentile wage ÷ 10 th percentile wage.

7-9 台灣的所得分配

7-10 台灣的所得分配

7-11 Changes in the Wage Structure: 1980s The wage gap between those at the top of the wage distribution and those at the bottom widened dramatically. Wage differentials widened among education groups, experience groups, and age groups. Wage differentials widened within demographic and skill groups.

7-12 Earnings Inequality for Full-Time Workers, : Gini Coefficient

7-13 Earnings Inequality for Full-Time Workers, : The Wage Gap

7-14 Earnings Inequality for Full-Time Workers, : The Wage Gap

7-15 Wage Differential Between College Graduates and High School Graduates,

7-16 台灣大學以上 / 高中職薪資比例 ( )

7-17 Why Did Wage Inequality Increase? No single factor explains the changes. The increase in inequality seems to be caused by concurrent changes in economic “fundamentals” and labor market institutions.

7-18 Possible Factors That Widened the Wage Gap Demand for skilled workers increased relatively more than demand increased for unskilled workers. Increased physical capital helped to increase the productivity of skilled 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.

7-19 Changes in the Wage Structure from Shifts in Supply and Demand Relative Wage of Skilled Workers Relative Employment of Skilled Workers A S1S1 S0S0 D0D0 D1D1 B C p0p0 p1p1 r0r0 r1r1 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, S 0, 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 S 1. The rising relative wage of skilled workers can then be explained only if there was a sizable outward shift in relative demand from D 0 to D 1 (ending at point C).

7-20 Why did wage inequality increase? Supply shifts. International trade. Skill-based technological change. Institutional changes in the U.S. labor market. –Unions –Minimum Wage

7-21 The Earnings of Superstars Superstar phenomenon – a few persons in some professions earn very high salaries and seem to dominate their field. This suggests that even if a job is the same, different people bring different skills to the same job.

7-22 Superstar Earnings RankName2006 Income (in millions) 1Oprah Winfrey$260 2Jerry Bruckheimer$120 3Steven Spielberg$110 4Tiger Woods$100 5Johnny Depp$92 6Rolling Stones$88 7Jay-Z$83 8Tom Hanks$74 9Madonna$72 10Howard Stern$70 10Brian Grazer & Ron Howard$70

7-23 Inequality Across Generations There is a positive correlation between the skills of parents and their children. High-income parents typically invest more in the education of their children than do low-income parents. There is a tendency for income differences across families to get smaller over time (“regression toward the mean”).

7-24 The Intergenerational Link in Skills Earnings of Children Earnings of Parents 45  A, Slope = 1 B, Slope = 0 C, Slope is between 0 and 1 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 wage of children is independent of the wage of the parents, and there is complete regression toward the mean.

7-25 Social Capital The quality of the environment where a child grows up helps determine human capital. There is evidence that varied factors influence a child’s level of human capital. –Quality of neighborhood. –Importance of religious organizations. –Socioeconomic background of classmates.