1. Gini Coefficient:
The gini index is a measure of statistical dispersion, a measure of the inequality of a distribution, 0 being total equality and a value of 1 maximal inequality. It is most commonly used in economics to assess the inequality of wealth or income, but is also used in other fields such as health, science, ecology, chemistry and engineering. Gini coefficients range from 0.23 (Sweden) to 0.70 (Namibia), but not every country has been assessed.
The index is defined through the Lorenz curve, by plotting the proportion of the total income of the population (y-axis) by the bottom x% of the population): The 45 degree line represents the total inequality line. The Gini coefficient is thus calculated using the following formula : G = A/(A+B). A low Gini coefficient represents a more equal distribution, whereas a higher one represents a high income inequality.
Developed European nations and Canada tend to have indices between 0.24 and 0.36, whilst the United States and Mexico both have theirs above 0.40, showing there is greater inequality in those two nations. Using the gini index is helpful in quantifying differences in welfare and compensation policies and philosophies. Can be misleading when comparing small and large nations.
Advantages of using index as measure of inequality: * Main advantage is that inequality is measured by means of a ratio analysis, as opposed to per capita income or gross domestic product. * Can be used to compare income distributions across different population sectors as well as countries: urban vs. rural areas. * Better than GDP statistics because they do not represent changes for the whole population, whereas the index demonstrates how income has shifted from the poor to the rich. * Can be used to compare inequality over time * Four important principles: * Anonymity: it does not matter who the high and low earners are. * Scale Independence: