Lorenze curve- shows the cumulative of income against the cumulative percent of families or households. Gini coefficient- a measure of income inequality. Shows the ratio of the area A to the area A + B in the lorenze curve graph. Perfect Income Equality versus Perfect Income Inequality Ex: 100 Family country in which everyone makes 10,000$ a year. This country has perfect income equality. The gini coefficient would be zero. Ex: Consider 100 family country which one family makes a million dollars and everyone else makes nothing. The Lorenze curve runs along the horizontal axis. The Gini coefficient would be 1. The distribution of income in the US has gotten more unequal over time. Income inequality is increasing because the incomes for households at the top of the income distribution have been growing, while incomes for households at the bottom of the income distribution have been stagnant. Incomes for the HH at the 90th percentile have risen much faster than incomes at the 10th percentile. Real median income has increased very modestly. Changes between the bottom of the income distributions have been relatively small. Sources of Income Inequality Differences in Human Capital Human Capital- the stock of skill and knowledge that individuals possess. Education is an important component of human capital. There is a substantial income inequality within education groups. Differences in native ability Differences in hours and weeks worked Differences in income by race- there are substantial differences by they have diminished slightly over time. Differences in income by sex there are substantially differences, but they are shrinking due to higher incomes among women. Taste-based discrimination- explicit preference for one group over another Statistical Discrimination- employers may believe that one group of workers as differentiated on the basis of pre-market factors such as race or sex has a different distribution of ability types than another group. If the employer believes these differences exist then it may pay members of the group that it believes to have lower average abilities lower wages, or it may be more inclined to hire workers from the group with higher perceived abilities. Statistical discrimination can also be based on uncertainly be risk-adverse employers. Maybe there are no perceived mean differences in ability between groups, but there is a perceived difference in variance. In this context, the employer, wanting to reduce risk, is going to be more likely to hire from the group with the lower variance. Perhaps an employer has more difficulty in assessing the productivity of some groups of workers. Then the employer is going to be more likely to hire from the group where productivity is easier to ascertain. It is hard to distinguish between taste-based discrimination and statistical discrimination. There are substantial differences between groups even when you control broadly for human capital- skill. Some inequality is natural and good, but too much inequality can be bad because then there will be a small amount of people that hold all the money and power. Mobility in comparative perspective- the US is amongst the least mobile wealthy countries. Causes of Increasing Inequality Technological Change- changes if technology has increased demand for more skilled workers and decreased demand for less skilled workers. Globalization- The US now imports most labor intensive products. This has decreased demand for less skilled workers domestically. Immigration- on average immigrants are less skilled than the native born. In this sense immigration will increase the supply of less skilled workers, leading to reduced wages.
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