The most widely used single measure of inequality is the Gini coefficient. It is based on the Lorenz curve, a cumulative frequency curve that compares the distribution of a specific variable (e.g. income) with the uniform distribution that represents equality.

In a reassessment of the income gap between the country’s top earners and lowest-paid, an official report by the Office for National Statistics “ONS”, into the years between 2002 and 2018 found that inequality levels have remained relatively static since the turn of the millennium.

Taking account of the latest revisions, the ONS said the UK’s Gini coefficient – the most common (but still flawed) international measurement of inequality which uses a score of 0-100%, whereby 100% would indicate one person controlling everything – should have been 34.5% in the financial year ending in 2018.

While the Gini coefficient has many desirable properties – mean independence, population size independence, symmetry, and Pigou-Dalton Transfer sensitivity – it cannot easily be decomposed to show the sources of inequality and does not consider age or sex based differences. Household surveys, the data sources traditionally used to observe inequality dynamics, do not properly capture these evolutions. Surveys provide useful information and cover many countries, but they do not inform adequately on income and wealth levels of the richest individuals.

Nevertheless, according to the fresh analysis, income inequality rose sharply in the years up to the financial crisis, fell during the economic collapse, and has been broadly flat since.

The report detailed average income of the top 10% rose by 28.5% between 2001-02 and 2007-08. As the banking collapse damaged the earnings of the highest paid, incomes for the highly paid fell by 20.8% by the end of 2012-13.

Britain has one of the highest Gini scores for income inequality in the western world, after the divide between rich and poor ballooned in the late 1970s and early 1980s. It has remained relatively unchanged with a score in the mid-30s since the early 1990s.

Globally over the past decades, the increase in economic inequalities was largely driven by a rise in income and wealth accruing to the top of the distribution. According to research from the Nobel prize-winning economist Angus Deaton and the Institute for Fiscal Studies, the UK is at risk of following the US to become one of the most unequal wealthy nations.

The best-known entropy measures are Theil’s T and Theil’s L, both of which allow one to decompose inequality into the part that is due to inequality within areas (e.g. urban, rural) and the part that is due to differences between areas (e.g. the rural-urban income gap). Typically at least three-quarters of inequality in a country is due to within-group inequality, and the remaining quarter to between-group differences.

It maybe beneficial to calculate an inequality index using Theil’s T and Theil’s L or even find an even more accurate methodology to calculate inequality data. There appears to be greater accuracy coming from wid.world team – Lets work together to help reduce inequality.