Gini Coefficient

Developed by the Italian statistician Corrodo Gini, and published in his 1912 paper 'Variability and Mutability' this measure of statistical dispersion is called 'Gini Coefficient'. Gini index and Gini ratio are other names by which Gini coefficient is often referred to.

This application is used in the study of statistical dispersion in fields as diverse as economics, health science, ecology, chemistry and engineering. World over, though not in every country, Gini coefficient is adopted to measure inequality of income or wealth of a nation's residents. Inequalities among values of a frequency distribution, like income, are measured by Gini coefficient.

In any measure of inequality, a Gini coefficient of zero expresses perfect equality - this means all the values are the same - in other words, everyone has the same income. A Gini coefficient of one (or 100%) means, there is maximal inequality among values (that is one person has all the income and others have none). But in larger groups, values close to or above 1 should be unlikely.

Gini coefficient features

There are certain features that makes Gini coefficient useful as a measure of statistical dispersion, inequalities in particular. First and foremost, as a ratio analysis measure, this method is simple to understand and interpret.

Gini coefficient avoids references to statistical averages. Therefore, it is widely used among diverse populations to compare different regions, age groups in diverse countries. It can be used to interpret data in any state, country, urban versus rural population and areas, gender and ethnic groups.

Hence, Gini coefficient can compare income inequalities between male and female population in a country or among countries. It can also be used to assess whether the inequality is increasing or decreasing independent of absolute incomes. Other significant features that make Gini coefficient really efficient are:

• Anonymity: It does not matter who the high and low income earners are.
  
  
• Scale independence: The size of the economy, the way of measurement, or whether the country is rich or poor on an average are not considered.
  
  
• Population independence: It does not worry about how large the population of a country is.
  
  

Gini coefficient as a measurement of income inequality

In general, inequality of income can be measured before and after taxes and transfers. Expertise, productiveness, work experience, inheritance, gender and race are factors that strongly influence distribution of personal income in the US and elsewhere. The distribution of transfers has declined from 1979 to 2007 as it was found that transfers are less progressive. Federal taxes have also shrunk progressively as a percentage of market share.

In the US, income inequality has grown significantly since the early 1970s and is consistently exhibiting higher rates of income inequality than most developed nations. This has happened after several years of stability.

Inequality measured by Gini in the US was not uniform among the states as after tax income revealed greater inequality in 2009 - and it was greatest in Texas and lowest in Maine.

A measure of income distribution by Gini coefficient reveals that disparity widens as one go up in the income distribution. In the US for instance, when a 2011 study revealed that top earning 1 percent of households increased their income by about 275% at one period of time between 1979 and 2007, after federal taxes and income transfers were effected.

About 42% of Americans think that income inequality has increased in the past 10 years and in 2012 the gap between the richest 1 percent and the 99 percent remaining population was the widest since 1920. The disparity is between the middle class and top earners, with gap widening further with higher income distribution.

In the US, incomes of the wealthiest 1 percent has risen nearly 20 percent whereas the incomes of the balance 99 percent has risen only 1 percent by comparison.

A 2013 study indicates that income inequality in the US is comparable to other developed countries before taxes and transfers but is worst among 22 developed countries after taxes and transfers. Public policy choices, more importantly than market factors drive the US income inequality compared to other wealthy nations.

On comparison, in the case of the other OECD (20 countries including USA and Canada that signed the Convention on the Organization for Economic Co-operation and Development) countries, Gini coefficient ranged between 0.24 and 0.49 considering tax effects and transfer payments. Slovenia was the lowest and Chile the highest during the 2000s. The countries in Africa had the highest per tax Gini coefficient in 2008-9.

Gini indexing in countries

Different sources often give different Gini values for the same country or population that is measured. A Census Bureau revealed Gini coefficient in the US as 46.9 in 2010, an upward swing from an all time low of 38.6 in 1968. In the OECD countries, Gini coefficient for income inequality is 37 in the US and is still the highest in the developed world and the lowest is Denmark with 24.3 and Norway with 25.6 and then comes Sweden with 25.9.

There are arguments that inequality is higher in some countries than official statistics indicate because of unreported income and as European countries have higher income of wealth in offshore countries.

Gini coefficient and Lorenz curve

Gini coefficient is graphically presented by means of a Lorenz curve, which is a measure of distribution of wealth, or income or any other factor in a society. The x value in the curve corresponds to the population and the y value represents that portion of the total value of the characteristic in question held by people no wealthier than the x value percentile of population. If the value graphically presented is 0.7, 0.3 then it means that the bottom 70% of the population owns 30% of the total wealth in the society. The coefficient would run from zero in a perfect egalitarian society to one in a society in which the wealthiest person holds all wealth.

Income inequality measurement between male and female

Male and female income difference is referred to as 'gender gap in earnings' or 'gender wage gap' and this is the ratio of female to male median yearly earnings, among full-time, year round among workers. The statistics are gathered by the United States Census Bureau.

The gap in income between male and female employees has decreased considerably since 1953. As such women currently study more than men - earn more Bachelors', Master's degrees than men. They also pursue as many professional courses and doctorates as men. It is estimated that by 2016, women will earn two thirds of Associate's, Bachelor's and Master's degrees as men

In 2010, female-to-male earning was 0.81 and in 2009 female workers earned 19% less than their male counterparts. Skill, occupation, education or hours worked are not taken into consideration. While some portion of the wage gap is unexplained and this is attributed to gender discrimination.

The discriminatory disparities seem to grow as men and women progress in their careers. Contrary, there are studies that argue that men and women would have equal pay if only they make the same choices, had the same experience, education etc.

Interestingly, Bloomberg News reported in 2009, that there are sixteen women heading companies with averaged earnings of $14.2 million in their latest fiscal years, which is 43 percent more than the male average. While in 2009 women got a 19 percent raise men took 5 percent cut.