V. Income Inequality
begin to understand what life is like in a country—to know, for example, how many of its inhabitants
are poor—it is not enough to know that country’s per capita income. The number of poor
people in a country and the average quality of life also depend on how
equally—or unequally—income is distributed.
Cross-country Comparisons of Income Inequality
In Brazil and Hungary, for example, the GNP per capita levels are rather close, but the incidence
of poverty in Brazil is higher. The reason for this difference can be understood with the help of Figure
5.1, which shows the percentages of national income received by equal percentiles of individuals
or households ranked by their income levels.
In Hungary the richest 20 percent (quintile) of the population received about 4.5 times more than
the poorest quintile, while in Brazil the richest quintile received more than 30 times more than the
poorest quintile. Compare these ratios with an average of about 6:1 in high-income countries. In the
developing world income inequality, measured the same way, varies by region: 4:1 in South Asia, 6:1
in East Asia and the Middle East and North Africa, 10:1 in Sub-Saharan Africa, and 12:1 in Latin America.
Lorenz Curves and Gini Indexes
To measure income inequality in a country and compare this phenomenon among countries more accurately,
economists use Lorenz curves and Gini indexes. A Lorenz curve plots the cumulative percentages of total
income received against the cumulative percentages of recipients, starting with the poorest individual
or household (see Figure. 5.2). How do they construct the curve?
First, economists rank all the individuals or households in a country by their income level, from
the poorest to the richest. Then all these individuals or households are divided into 5 groups, 20
percent in each, (or 10 groups, 10 percent in each) and the income of each group is calculated and
expressed as a percentage of GDP (see Figure 5.1). Next, economists plot the
shares of GDP received by these groups cumulatively—that is, plotting the income share of the
poorest quintile against 20 percent of the population, the income share of the poorest quintile and
the next (fourth) quintile against 40 percent of the population, and so on, until they plot the aggregate
share of all five quintiles (which equals 100 percent) against 100 percent of the population. After
connecting all the points on the chart—starting with the 0 percent share of income received by
0 percent of the population—they get the Lorenz curve for this country.
deeper a country’s Lorenz curve, the less equal its income distribution. For comparison, see
in Figure 5.2 the “curve” of absolutely equal income distribution.
Under such a distribution pattern, the first 20 percent of the population would receive exactly 20
percent of the income, 40 percent of the population would receive 40 percent of the income, and so
on. The corresponding Lorenz curve would therefore be a straight line going from the lower left corner
of the figure (x = 0 percent, y = 0 percent) to the upper right corner (x = 100 percent, y = 100 percent). Figure
5.2 shows that Brazil’s Lorenz curve deviates from the hypothetical line of absolute equality
much further than that of Hungary. This means that of these two countries Brazil has the higher income
A Gini index is even more convenient than a Lorenz curve when the task is to compare income inequality
among many countries. The index is calculated as the area between a Lorenz curve and the line of absolute
equality, expressed as a percentage of the triangle under the line (see the two shaded areas in Figure
5.2). Thus a Gini index of 0 percent represents perfect equality—the Lorenz curve coincides
with the straight line of absolute equality. A Gini index of 100 implies perfect inequality—the
Lorenz curve coincides with the x axis and goes straight upward against the last entry (that is, the
richest individual or household; see the thick dotted line in Figure 5.2). In
reality, neither perfect equality nor perfect inequality is possible. Thus Gini indexes are always
greater than 0 percent but less than 100 percent (see Figure 5.3 and Data
Costs and Benefits of Income Inequality
Is a less equal distribution of income good or bad for a country’s development? There are different
opinions about the best pattern of distribution—about whether, for example, the Gini index should
be closer to 25 percent (as in Sweden) or to 40 percent (as in the United States). Consider the following
An excessively equal income distribution can be bad for economic efficiency. Take, for example, the
experience of socialist countries, where deliberately low inequality (with no private profits and minimal
differences in wages and salaries) deprived people of the incentives needed for their active participation
in economic activities—for diligent work and vigorous entrepreneurship. Among the consequences
of socialist equalization of incomes were poor discipline and low initiative among workers, poor quality
and limited selection of goods and services, slow technical progress, and eventually, slower economic
growth leading to more poverty.
In many high-income countries relatively low inequality of incomes is achieved with the help of considerable transfer
payments from the government budget. However, economists often argue that mitigating inequality
by increasing the burden of government taxes tends to discourage investment,
slow economic growth, and undermine a country’s international
On the other hand, excessive inequality adversely affects people’s quality of life, leading
to a higher incidence of poverty, impeding progress in health and education, and contributing to crime.
Think also about the following effects of high income inequality on some major factors of economic
growth and development:
- High inequality reduces the pool of people with access to the resources—such as land or
education--needed to unleash their full productive potential. Thus a country deprives itself of the
contributions the poor could make to its economic and social development.
- High inequality threatens a country’s political stability because more people are dissatisfied
with their economic status, which makes it harder to reach political consensus among population groups
with higher and lower incomes. Political instability increases the risks of investing in a country
and so significantly undermines its development potential (see Chapter 6).
- High inequality may discourage certain basic norms of behavior among economic agents (individuals
or enterprises) such as trust and commitment. Higher business risks and higher costs of contract
enforcement impede economic growth by slowing down all economic transactions.
- High inequality limits the use of important market instruments such as changes in prices and fines.
For example, higher rates for electricity and hot water might promote energy efficiency (see Chapter
15), but in the face of serious inequality, governments introducing even slightly higher rates
risk causing extreme deprivation among the poorest citizens.
These are among the reasons why some international experts recommend decreasing income inequality
in developing countries to help accelerate economic and human development. But the simple fact that
high levels of income inequality tend to strike many people as unfair, especially when they imply starkly
different opportunities available to children born in the same country, also matters for sustainable
development. After all, how can people care about the needs of future generations if they don’t
care about people living today?