Gini index of income inequality

(a)      Name:    Gini Index of Income Inequality.
(b)      Brief Definition:  A summary measure of the extent to which the
actual distribution of income, consumption expenditure, or a related variable,
differs from a hypothetical distribution in which each person receives an
identical share.
(c)      Unit of Measurement:   A dimensionless index scaled to vary from a
minimum of zero to a maximum of one; zero representing no inequality and one
representing the maximum possible degree of inequality.

(a)      Agenda 21:  Chapter 3: Combating Poverty.
(b)      Type of Indicator:   State.

(a)      Purpose:  The Gini Index provides a measure of income or resource
inequality within a population.  It is the most popular measure of income
inequality. 

(b)      Relevance to Sustainable/Unsustainable Development: This indicator is
particularly relevant to the equity component of sustainable development.
Income or resource distribution have direct consequences on the poverty rate
of a country or region. Broadly speaking, average material welfare can be
defined by the per capita Gross Domestic Product (GDP).  However, statistical
averages can mask the diversity that exists within any country. Therefore,
from a sustainable development perspective, it is informative to examine
income and wealth distribution throughout a population.  A country can, for
example, have a high per capita GDP figure, but its income distribution so
skewed that the majority of people are poor. This indicator is useful both to
measure changes in income inequality over time and for international
comparisons.

(c)      Linkages to Other Indicators:  This indicator is linked to several
other sustainable development measures, including the poverty indicators,
women per 100 men in the labour force, GDP per capita, population dynamics in
mountain areas, and sustainable development strategies.

(d)      Targets:  Not available.

(e)      International Conventions and Agreements:  Not available.

(a)      Underlying Definitions and Concepts:  The concept and definition of
this indicator are well understood and readily available.  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 of
perfect equality (see Figure 1 in section 4b below).  The Gini Index is
defined as one half of the average value of the absolute differences between
all possible pairs of "incomes".

(b)      Measurement Methods: The Lorenz Curve plots the cumulative
percentages of total income received (on the vertical axis) against the
cumulative percentage of recipients, starting with the poorest individual or
household (see Figure 1). 

                   Figure 1: The Lorenz Curve and Gini Index of Income

                             (Not available on the Internet)

There are a number of choices about data which can influence the precise value
of the Gini Index obtained. For example, a Gini Index for consumption
expenditure will typically be lower in value than one for income, even within
the same population. This is because households smooth their consumption over
time in response to income changes.  At any one date, there will be some
households with unusually low incomes and others with unusually high ones;
with some opportunities for saving and/or borrowing. Thus, household
consumption will be less unequal. 

It is important how "income" is measured, for example whether it is total
household income or per capita household income, or income per equivalent
adult. In addition, it matters whether or not the incomes are weighted by
household size, since households with lower income per person tend to be
larger. Thus, the income share of the poorest 20% of households will be higher
than the income share of the poorest 20% of persons. 

The World Bank, for example, prefers to weight by household size and calculate
the shares held by persons rather than households for most purposes. As a
general rule, the Bank also considers consumption expenditure to be the more
reliable indicator of welfare than income, which can be excessively variable
over time, and is also more difficult to measure accurately, particularly in
developing countries.  Looking at the sample of 67 low and middle income
countries for which Gini indices of income are reported in the World Bank's
draft report World Development Indicators, this coefficient ranges from a low
of 22% to a high value of 64%. 

There are a number of ways of estimating the Gini Index of income, and the
choice depends in part on the type of data available. Distributional data are
often available in grouped form, such as the income share of the lowest decile
of households, where households are ranked by income per person. To estimate
the Lorenz Curve, and thus the Gini Index, from such data, the World Bank
often uses a software package called POVCAL. Having specified the type of
data, the program calculates both the General Quadratic specification for the
Lorenz Curve and the Beta specification. It then calculates the Gini Index and
various other statistics, including poverty measures for each Lorenz Curve.
The program also advises which is the better specification for the Lorenz
Curve for the specific data used.  

(c)      The Indicator in the DSR Framework:  In the DSR Framework, this
indicator represents a measure of the State of income inequality.

(d)      Limitations of the Indicator:  The Gini Index is not a very
discriminating indicator. Two very different distributions--one having more
inequality amongst the poor, the other having more amongst the rich--can have
exactly the same Gini Index.

Measurement errors in data sets are thought to be greater for incomes compared
to consumption expenditure, which will add to measured inequality (see section
4b above).  Differences between countries in the measured Gini index may thus
reflect in part differences in the welfare measures used. 

While the Gini Index of income (in common with most other measures of
inequality) captures information on the pattern of relative levels of
wellbeing in the population, it is independent of any considerations of
absolute living standards. So there is nothing to guarantee that a lower Gini
Index of income entails higher social welfare in any agreed sense, since the
mean income may have also fallen. The Gini Index is at best a partial
indicator, and other measures will be needed to complete the picture of how
levels of economic welfare are evolving in a society.

It should be noted that there are several comparability problems across
countries in the use of data from household surveys (see section 5 below).
These problems are diminishing over time as survey methodologies are improving
and becoming more standardized, but they remain. 

(e)      Alternative Definitions: There are many other measures of inequality,
with various strengths and weaknesses.  These are discussed in Sen (1973) (see
section 7a below).  

5.	Assessment of the Availability of Data from International and National Sources 

The most important source of data on living standards is household surveys.
The results of these surveys can be obtained from government statistical
agencies, often via published reports. About two thirds of the developing
countries have done sample household surveys which are representative
nationally, and some (but certainly not all) of these provide high-quality
data on living standards. 

Data can also be obtained from international agencies such as The World Bank
(mostly data for low and middle income countries emerging from the Living
Standards Measurement Study and Social Dimensions of Adjustment Project for
Sub Saharan Africa). Data for developed countries can be obtained from the
Statistical Office of the European Union (Eurostat), the Luxembourg Income
Study, or the Organisation for Economic Co-operation and Development (OECD). 

The lead agency involved is The World Bank (WB).  The contact point is the
Chief, Indicators and Environmental Valuation Unit, Environment Department,
WB; fax no. (1-202) 477 0968.

(a)      Further Readings:

Chen, S., G. Datt, M. Ravallion. POVCAL: A Program for Calculating Poverty
Measures from Grouped Data. Poverty and Human Resources Division, Policy
Research Department, Washington DC: World Bank. 1992. 

Ravallion, M., and S. Chen. What Can New Survey Data Tell Us About Recent
Changes in Living Standards in Developing and Transitional Economies?. Working
Paper 1. Research Project on Social and Environmental Consequences of
Growth-Oriented Policies, Washington DC: World Bank.

Sen, A.  On Economic Inequality. Oxford: Oxford University Press. 1973.

The World Bank.  World Development Indicators.  Draft Report.  1996.

LEAD AGENCY: WORLD BANK