Gimi Coefficient - Essay Example

According to the ranges of the Gini coefficient, the developing or poor countries, those countries who have per capita GDP low, come in the range from 0.25 to 0.71. As far as rich countries are concerned they come in the range of under 0.40 (Mandal 126). The Lorenz curve diagrams ratio of the area can be used to elaborate the Gini coefficient. In the Lorenz curve, if we say that A symbolizes the area among the line of perfect equality and B symbolizes the Lorenz’s curve inner area then A/(A+B) is the equation that represents the Gini coefficient.

Subsequently A+B = 0.5, the gini coefficient, G = 2A = 1-2B. By incorporation the value of B can be found if the Lorenz curve is characterized by the function Y= L(x) and the equation will be, (Catalano and George D. n.p). The usage of the Gini coefficient measure of inequality leads to many advantages, one of which is that it can be used to compare income distributions crosswise diverse populations. The Gini coefficient is easily used because of its simplicity rather than other measuring techniques, through the gini coefficient we can come to the results of the changed distribution of income over the year in a country.

It also satisfies great principles of anonymity, scale independence, and population independence. On one hand, it has many advantages, on the other side there are many problems faced while using the Gini coefficient measure of inequality. The Gini coefficient uses income gained from wealth, it measures net income more than net worth, having a possibility of misinterpretation. For example, a low Gini coefficient for income is seen in Sweden, but Sweden’s coefficient for wealth is higher. Numerous while in the Gini coefficient, there is no description of the proportions used for measurement.

As granularity impacts the measurements of the Gini coefficient, we find numerous problems while conducting measurements through it. If there is low granularity, that is four 20% quantiles it will lead to a lower Gini coefficient, while at the same time if we take twenty 4% quantiles that are high granularity the results would be a higher Gini coefficient if we take both of these figures from the similar distribution (Mandal 129). Because it is a measure of income dispersion a lot of care has to be taken through the use of the Gini coefficient as a measure of egalitarianism.

For example, We will get a result of the difference in Gini coefficients when we take two different countries having equal egalitarianism, but as they both have different policies, the Gini coefficient will be different. As it measures at a point in time the greatest problem of the Gini coefficient is that it errors a lot of energetic information about the lifetime income of the individual. In the Gini coefficient, not only the income but also the individual’s age distribution within the population and mobility in income classes are not taken into consideration (Mandal 129).

It can be observed that if the Gini coefficient is showing higher results at one point, but will not gibe the same result at different points because the Gini coefficient does not notice the changes over a period of time. A number of more problems arise when it comes to measurement through the Gini coefficient; the difficulty arises that is when two counties' incomes are associated as both the countries differ in benefits systems, like some countries give benefits in monetary form, while others do not in monetary form.