Transcript Lecture 6

Lecture 10
World Income Inequality: past,
present and future.
Read Outline to Chapter 11.
The Inequality of Nations
• The richest to poorest ( at $400 ) nation indicator tells
you about the opportunities lost in poor nations
• It reflects an increasing gap between technological and
institutional potential and the consequences of not being
able to absorb advanced technology because of
malfunctioning institutions, poor educational standards
and bad government – and poor advice from
international aid agencies?
• Most of the ‘Divergence Big Time’ is a post 1800
phenomenon but you can trace the beginning back to
c.1500.
Is our wealth based on exploitation
of the poor?
• Not much, but
• Rich world’s agricultural protectionism lowers world
market price for poor peasants world wide
• International division of labour has given poor countries
exportable commodities with high price volatility
• Foreign investments in poor countries smaller than
expected
• Major problem is ‘unlimited supply of labour’ which
pushes wages down to subsistence and translates
technological progress into falling commodity prices and
potentially falling terms of trade for the poor relative to
the rich world, the W. A. Lewis hypothesis
The sources of inequality
• Inequality of personal income is linked to
• natural talent
• skill acquired by education and on the job
training
• accumulated wealth
• inherited wealth
• market imperfections
• discrimination
Measuring Inequality
• Standard dispersion measures will do
such as, standard deviation or coefficient
of variation
• We will concentrate on the so-called Ginicoefficient
• The intuition behind G: it measures the
deviation of observed income distribution
from the ideal state of perfect equality
The Gini explored
Interpretation of the numbers
• A Gini coefficient of 1 means absolute or perfect
inequality, total income is held by the richest person.
• As the coefficient get smaller than 1 the economy gets
less unequal. At zero we have perfect equality:
everybody earns the average income
• Ginis are not consistently used as fractions of 1 but often
as the fraction, say, 0.5 multiplied by 100 = 50.
• Next table indicates considerable inequality in medieval
European cities which reflects a sophisticated division of
skills and labour as well as unequal distribution of wealth
The inequality possibility frontier
• Absolute inequality is not possible since
there is a minimum subsistence income.
• Assume that income to be 400$PPP (of
1990).
• If 99.9 per cent of the population earns
that income and the rich 0.1 per cent
extracts the rest we get an increasing
inequality possibility frontier as average
income rises.
A curve of maximum inequality
Implications
• Rich contemporary nations are far away
from the maximum inequality even if the
Ginis are similar to those of Roman and
the Byzantine Empires.
• Pre-industrial and Early Modern (16th and
17th centuries) economies were more
unequal that modern economies.
Inequality in the modern world
Why do trends differ?
• Un-weighted inequality increases: each
nation is represented by its average GDP
per head and all nations have the same
weight = 1
• Population weighted inequality controls for
the fact that nations differ in population
size, the larger the nation is the larger
weight its GDP per head gets
World income inequality paradox
• Population weighted inequality falls because
many of the fast growing economies, such as
China and India, have large populations
• But early modernizing economies have skill
shortages increasing the so called Kuznets
inequality
• As a consequence ‘global inequality’ which
controls for changes in each nation’s inequality
has not fallen
Kuznets at work
Long term trends
• Next figure follows the long run trends in unweighted (concept 1)and population weighted
inequality
• Increase in pop. weighted inequality (concept 2)
when a small number of economies join the
‘growth club’ but decrease when a large number
of economies join the growth club by 1950 and
converge to income levels of the richest nations
China makes a difference!
Predicting the future from the past
• Next table estimates observed transition
probabilities, for example the probability of
getting from low initial income to high
growth, from medium level initial income
to high growth into high growth etc.
• Assuming that these probabilities are
stable a Markow process predicts a stable
long run outcome
Conclusion:
• Inequality will fall but it will not disappear
• The very poor nations will fall in numbers
and the very rich will increase
• But the estimates are based on historical
transition probabilities and these
probabilities will change
• A nation with a low transition probability to
high growth might change institutioins and
policy to improve chance
Back to the Future
The Lucas simulation
• Assume that all economies can – sooner or later – get
into the growth club
• The number of economies joining the club is initially
small, then increases until all nations are in the club
• The larger the income gap to the leading economies the
faster will initial growth be for the newcomer
• In the long run all economies will grow at the same rate
which is lower than the newcomer rate
• From these assumptions the evolution of average world
growth rate and income dispersion can be predicted
• World average growth rates will reach a maximum and
then fall in the future and so will ( un-weighted) income
inequality
More equality in the future!
Conclusion
• World inequality has probably peaked.
• When emerging economies expand their
educational systems skill shortages will
ease and domestic inequality will fall.
• Modern economies have Ginis similar to
the Roman empire but lower than Earl
modern Europe but they are far from their
maximum inequality.