# Relationship between lorenz curve gini coefficient graph

### Lorenz curve - Wikipedia

To the right is the basic setup for a Lorenz curve graph. Along the horizontal The Gini coefficient is a numerical measure of distributional inequality. The idea. Whereas the GINI-Coefficient is a measure of relative poverty, and it is use to Figure 1, on the horizontal axis the numbers of income recipients are plotted, not in Whereas the Lorenz Curve shows the quantitative relationship between the . IN SUMMARY WITH REFERENCE TO THE ABOVE GRAPH In economics, the Lorenz curve is a graphical representation of the distribution of income or of.

By introducing market reforms, opportunities emerged for private gain through entrepreneurial activities. Inequality in the US is higher than in most developed countries. Many people attribute the higher inequality to policies favouring the rich. Worsening inequality in the US can be explained by a range of factors, including tax policies that favour the rich, education policies that dampen the opportunities for intergenerational mobility see Section Lorenz curves for China, with labelled Gini coefficients.

Lorenz curves for the US, with labelled Gini coefficients. These ratios all help give policymakers an idea of the distribution of income in the economy and where income is concentrated. Policymakers may use the information to decide on policies favouring certain income deciles of the population.

Policymakers can use the information to decide how much income to redistribute to the poorest. The ratio can also be used to determine the distribution of tax burden among the relatively rich population.

## Lorenz curve

Policymakers can use the information to determine the amount of income to be redistributed to each group, and to determine who is in relative poverty many governments define the poverty line relative to the median income.

Students will plot the data for the ratio measures by changing the variable selected for the Gini coefficient.

The inter-decile ratios are calculated as the ratios between incomes of various deciles of income distribution. Larger values mean the income from one decile of the distribution is higher relative to the income from another decile. Countries that rank highly on the Gini coefficient also generally rank highly on ratio measures.

Lorenz Curve and Gini Coefficient - Measures of Income Inequality

There are, however, some exceptions. The potential differences in rankings of different measures mean it is important to look at more than one measure. The Gini coefficient is an overall measure of a distribution that may mask extreme inequalities between certain groups of the population.

### Doing Economics: Empirical Project 5 Solutions

This measure looks at the high end of the income distribution the right tail. Larger values indicate that the very rich have a larger share of the income, and that there is therefore more inequality between the very rich and the rest of society. However, this is a narrower measure of inequality than the Gini coefficient because it only tells us about how the very rich are doing.

Share of children living in relative poverty: This measure is defined as the share of children living in a household with half of the disposable income of the median household. A larger value indicates that a larger proportion of children are living in relative poverty. Mortality inequality Gini coefficients — Mortality inequality has been falling over time in all countries except Russia. Developing countries tend to have greater mortality inequality than developed countries.

Industrialized, richer countries seem to have materialized most of the available improvement somewhere at a mortality Gini of 0. Exceptions to this are India and Brazil, which are both still on a significant downward trend and still not close to a mortality Gini value of 0. The only country in this set of countries where some of the gains are being reversed is Russia, although the latest upward movement is fairly modest, and one may interpret this as Russia having settled on a higher mortality Gini of about 0.

Countries ranked according to mortality inequality Gini coefficients in The rankings are different in and Japan, for example, moved up five places in the ranking to become the second most equal country in The rapid economic development in Japan has led to rising life expectancy. Living to old age is now the norm in Japan rather than a privilege enjoyed only by the rich. The rising proportion of elderly voters has contributed to policies aimed at improving elderly care, which have reduced the variation in life expectancy.

The United States, on the other hand, dropped four places to become a relatively less equal nation in the group. The high costs of healthcare may prevent poor people from accessing treatment, especially if uninsured.

It is more likely for disadvantaged groups in society such as minorities or part-time workers to lack insurance coverage. This example looks at access to essential medicines. The median availability of selected generic medicines in percentage terms is a measure of the access to treatment. Data on availability, defined as the percentage of medicine outlets where a medicine was found on a given day, are collected through surveys in multiple regions for each country.

Lorenz curves for actual income distributions fall between those two hypothetical extremes. Typically, they intersect the diagonal line only at the very first and last points. Between those points, the curves are bow-shaped below the degree line. The Lorenz curve of market income falls to the right and below the curve for after-tax income, reflecting its greater inequality. Both curves fall to the right and below the line of equality, reflecting the inequality in both market income and after-tax income.

The intuition is straightforward although the mathematical formula will look a little messier. On a Lorenz curve, greater equality means that the line based on actual data is closer to the degree line that shows a perfectly equal distribution. Greater inequality means that the line based on actual data will be more "bowed" away from the degree line.

The Gini coefficient is based on the area between the degree line and the actual data line. As the CBO writes: Once again, the extreme cases of complete equality and complete inequality bound the measure. At one extreme, if income was evenly distributed and the Lorenz curve followed the degree line, there would be no area between the curve and the line, so the Gini index would be zero.