1. INCOME DISTRIBUTION
This article discusses about the income distribution in a country, the problems involved
and how inequality can be measured for a given income distribution.
For calculating income per capita we require total income and total population.
However for many countries this data does not exists. So all the calculations are done
based on household income per year rather than average of ten years.
Inequality can be measured using a Lorenz curve. It is a graph showing the bottom x%
of households, what percentage y% of the total income they have. The percentage of
households is plotted on the x-axis, the percentage of income on the y-axis. Perfect
equal income distribution is depicted by straight line y=x called the line of perfect
equality. Inequality is measured using Gini coefficient. The Gini coefficient is the area
between the line of perfect equality and the observed Lorenz curve, as a percentage
of the area between the line of perfect equality and the line of perfect inequality. The
higher the coefficient, the more unequal the distribution is.
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2. The impact of economic development on income distribution is then analyzed. The
data for income should be after taxes and it should include contributions by
government. This type of data will show greater level of inequality in developing
countries. This reduction in the inequality raises real income per capita. Also the
distribution by longer term average income shows less reduction in inequality than do
the distributions by annual incomes.
The income inequality in the early phases of economic growth when there is transition
from pre industrial to industrial civilization is more rapid; then becomes stable for a while;
and then narrowing in the later phases.
The hypothesis that income inequality first rises and then falls with development is
known as inverted U hypothesis. It was given by Simon Kuznet in 1955. He observed this
inequality in Germany, United Kingdom and United States. In these countries the
distribution in agriculture was more equal than the distribution of income in urban areas,
so as the development and urbanization took place, overall inequality rises. The decline
in inequality in later phases was due to better adaptation of children of rural- urban
migration to city economic life and growing political power of urban rural income
groups to enact legislation favoring their interests.
Montek Ahluwalia took sample of 60 countries and found that income share of all
groups except top 20% first decreases and then increases where as in case of top 20%
inverse happens. Kuznets inter-sectoral explanation of changes in income inequality,
were later formalized by Robinson 1976. Knight 1976 and Fields 1979, in their framework,
the rural–urban income differential is constant but the share of the population in the
agricultural sector changes with development, producing the familiar inverted U-shape
for evolution of income inequality over time. This is known as RKF model. The
assumptions of this model are based on the studies of less developed countries.
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3. In 1960 rural-urban migration in the LDCs was found to be a symptom of and a
contributing factor to underdevelopment. In LDC wages for skilled labour tend to be
higher in formal urban jobs than in rural jobs. These studies formed the basis of Todaro
(1969) and Harris-Todaro (1970) models which provided a widely accepted theoretical
framework for explaining the urban unemployment in many LDCs3.
Rural-Urban migration primarily as an economic phenomenon, the Harris-Todaro model
(HT) demonstrates that, in certain parametric ranges, an increase in urban employment
may actually result in higher levels of urban unemployment and even reduced national
product. The paradox is due to the assumptions that in choosing between labor
markets, risk-neutral agents consider expected wages; that the probability of obtaining
urban employment is approximated by the ratio of urban jobs to the urban labor force;
and that the urban wage rate is considerably and consistently higher than the rural
wage rate.
Under these assumptions, inter-labor market (rural-urban) equilibrium mandates urban
unemployment. This unemployment ensures that the expected urban wage is equal to
the rural wage (which is assumed constant throughout).
In LDC upon migration some rural migrants immediately obtain jobs in formal sector
while others get employed in small businesses and self employment i.e. informal sector.
Thus we have three classes of wage earners: rural (agricultural) workers, urban formal
sector workers, urban informal sector workers. Thus the size and income of these three
groups define the inequality during the course of development.
Robinson was challenged by James Rauch all individuals would prefer to be in the
sector with higher average income , and that once the need for migration equilibrium is
taken into account the cause of the inverted-U path of income inequality completely
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4. changes.In Rauch’s model Rauch supposes that individuals are indifferent in equilibrium
between earning the agricultural income with certainty or taking their chances in urban
sector, where they earn a high income if they are lucky and find a formal sector job
and a low income if they are unlucky and get stuck in the informal-sector under
informal
employment. The main source of inequality in the Rauch’s model is inequality within the
urban sector between informally and formally employed workers. As urbanization
increases the urban sector gains greater weight in the determination of overall
es
inequality, causing it to rise, but at the same time the share of the underemployed in
the urban population falls, eventually causing inequality within the urban sector and
overall inequality to fall. Therefore the inverted U in the income inequality is closely
related to the growth and decline of the proportion of the population that falls into the
poorest class, the underemployed. So Rauch’s result for overall income inequality is
similar to Kuznets’s original Hypothesis.
The inverted U curve
The next section is impact of income distribution on economic development. The
dominant view for many years was that income inequality promoted savings and
therefore promoted savings. The studies by Alberto Alesina and Dani Rodrick has shown
that income inequality and inequality of land ownership are negatively associated with
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5. per capita income growth during during the periods 1960-85 and 1970-85 for the
countries with available data. From that result they found that the impact of inequality
on development is negative. It was found, the key intervening variable in this
mechanism is political instability, so income inequality hypothesized to cause political
instability, which in turn is hypothesized to reduce investment, so it will be difficult to
sustain development.
Two case studies from Taiwan and Brazil has been discussed that show the impact of
govt. policies on income distribution and the impacts of income distribution on the
economy. The following graphics show the time line data of the two countries & their
economic conditions.
CASE STUDY: TAIWAN
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6. CASE STUDY: BRAZIL
CONCLUSION
The report aims at highlighting the crucial points about income distribution and the
economy and the chain of factors linking them. Though in real life there is a plethora of
factors that affect the economic development and income distribution but the above
subject do form the theoretical base for the same.
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