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Gimi coefficient - Essay Example

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Course Date CRITICISIM OF GINI COEFFICIENT AS A MEASURE OF INEQUALITY Source: http://en.wikipedia.org/wiki/Gini_coefficient Gini coefficient is a measure of inequality developed by the Italian statistician CorradoGini and this was published in his paper in 1912 "Variabilita e mutabilita" (Grossi, Marina, n.p)…
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Download file to see previous pages According to the ranges of gini coefficient, the developing or poor countries, those countries who have per captia GDP low, comes 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 area can be used to elaborate the gini coefficient. In Lorenz curve if we say that A symbolizes the area among the line of perfect equality and B symbolizes as the Lorenz’s curve inner area then A/(A+B) is the equation which 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 gini coefficient measure of inequality leads to many advantages, one of which is that it can be used to compare income distributions crosswise diverse population. Gini coefficient is easily used because of its simplicity rather than other measuring techniques, through gini coefficient we can come to the results of changed distribution of income over the year in a country. It also satisfies great principles of anonymity, scale independence and population independence. As on one hand it has many advantages, on the other side there are many problems faced while using gini coefficient measure of inequality. 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 whiles in gini coefficient, there is no description of the proportions used for measurement. As granularity impacts the measurements of 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 is high granularity the results would be higher gini coefficient if we take both of these figures from the similar distribution (Mandal 129). Because it a measure of income dispersion a lot of care have to be taken through the use of gini coefficient as a measure of egalitarianism. For example We will get a result of difference in gini coefficients when we take two different countries having equal egalitarian, but as they both have different policies, gini coefficient will be different. As it measures at a point in time of the greatest problem of gini coefficient is that is errors a lot of energetic information about lifetime income of the individual. In gini coefficient, not only the income but also the individual’s age distribution within population and mobility in income classes are not taken into consideration (Mandal 129). It can be observed that if gini coefficient is showing higher results at one point, but will not gibe same result at different point because gini coefficient does not notice the changes over a period of time. A number of more problems arise when it comes to measurement through gini coefficient; difficulty arises that is when two counties income are associated as both the countries differ in benefits systems, like some countries give benefit in monetary form, while others not in monetary form. Some countries may include benefits some may not, as the ...Download file to see next pages Read More
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