I was ‘reminded’ about Gini coefficient on Saturday evening during a debate organised by private broadcaster, Zodiak Broadcasting Station (ZBS), involving four of the 11 presidential running mates in the forthcoming May 20 Tripartite Elections.
There were interesting responses to the question on how to narrow the gap between the rich and the poor.
Put loosely, Gini coefficient is a measure of distribution of wealth in an economy such as Malawi. It is a statistical dispersion designed to represent income distribution among citizens, poor or rich, developed by Italian statistician Corrado Gini as published in his paper ‘Variability and Mutability’ back in 1912.
Since then, the Gini index, as it is sometimes called, has been used to measure distribution of income as well as consumption expenditure among households or individuals.
How does the Gini index analyse income levels? The index is based on the Gini coefficient as explained above and ranks income distribution in an economy on a scale of between zero and one. This means that a reading of one indicates perfect inequality where one person holds all the income. A zero means a perfect distribution where members have more or less equal incomes.
The Gini index is worked out alongside the Lorenz curve, a graphical representation of the distribution of wealth produced by Max Lorenz, an American economist, in 1905. The Lorenz curve, on a particular graph, lies under a straight diagonal line representing perfect equality of wealth distribution. It indicates the reality on the ground in terms of wealth distribution, with the difference between the straight line and the curved line representing the amount of inequality of wealth distribution or what is called Gini coefficient.
The Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The Gini index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line.
Back to the running mates debate. Statistics add value, but statistics wrongly used distort the picture altogether. For example, Minister of Industry and Trade Sosten Gwengwe drew a round of applause from the audience when, in his response to the question on “Gini coefficient”, he said the People’s Party (PP) administration, through programmes lined up in its manifesto, would “increase” the Gini coefficient from 0.40 during former president the late Bingu wa Mutharika’s time to 0.90.
This left many wondering as to why some sections of the debate audience applauded President Joyce Banda’s running mate as, in effect, what his response meant was that his administration will or plans to widen the inequality gap between the ‘haves” and “have-nots” or the rich and the poor. By way of background, in the 1960s with founding president the late Hastings Kamuzu Banda and the Malawi Congress Party (MCP) at the helm, Malawi’s Gini coefficient was .45 and it rose to .63 in 1993 which means that income distribution worsened during the period.
The Integrated Household Survey 2010-2011 published by the National Statistical Office (NSO) in September 2012 shows that using the Gini coefficient, inequality income or wealth distribution was slightly higher in 2011 as compared to 2005. The extent of the inequality did not differ across rural areas. However, the populous Southern Region had the largest Gini coefficient followed by rural areas in the Central and Northern regions in that order.
Reading the survey report, which is the latest data available so far in Malawi, the tables therein indicate worsening distribution of income by about 15 percent.
