Alternative Indicators of Welfare

Idea

Because national income statistics speak only to the material standard of living, economists supplement them with indicators that capture distribution and the non-material quality of life. Three are in the syllabus: the Gini coefficient, the Human Development Index, and the Measure of Economic Welfare.

Mechanism

Gini coefficient. A statistical measure of income inequality, derived from the Lorenz curve — a curve showing the proportion of national income earned by a given cumulative percentage of the population, ordered from poorest to richest. The Gini coefficient is the ratio of the area between the Lorenz curve and the line of equality (area A) to the whole area beneath the line of equality (area A + area B):

$\text{Gini coefficient} = \frac{\text{Area A}}{\text{Area A} + \text{Area B}}$

It ranges between 0 and 1. Under perfect equality the Lorenz curve is the 45° line of equality, area A is zero, and the coefficient is 0. Under perfect inequality one person earns everything, the curve hugs the axes, area B is zero, and the coefficient is 1. Real economies lie strictly between; a higher value means greater inequality.

Human Development Index (HDI). The most widely used alternative, a composite indicator combining three sub-indices: a life expectancy index (a proxy for the quality and availability of healthcare), an education index (expected and mean years of schooling, a proxy for knowledge), and GNI per capita at PPP (the material standard of living). It runs from 0 to 1.

Measure of Economic Welfare (MEW). A composite that starts from GDP per capita at PPP and adjusts it for the value of leisure time, the value of unpaid work, and environmental costs — adding back what raises welfare but goes uncounted, and netting off the negative externalities of growth.

Diagram

Lorenz curve. The 45° line of equality and the bowed Lorenz curve below it; the Gini coefficient is area A (between the two) over area A + area B (the whole area under the line of equality).

Considerations

Each indicator trades completeness against objectivity. The Gini coefficient captures distribution but nothing else. The HDI and MEW broaden the picture, but their composite construction is subjective: the weights placed on the sub-indicators — education versus life expectancy, leisure versus environmental cost — have no agreed value, so different weightings yield different rankings. They complement rather than replace real GDP per capita.