Transcript growth rate

On the Evolution of
the World Income
by Charles I. Jones
Main questions
• Are poor countries catching up
to the rich countries or falling
behind?
• How might the world income
distribution look in the future?
Overview
• Empirical facts concerning the
distribution of GDP per worker across the
countries of the world and how the
distribution has changed since 1960.
• Characterize the future of the world
income distribution using 3 different
techniques.
3 different techniques
1) Using standard growth models to project the
current dynamics of the income distribution
forward.
2) Cross-country growth regression
3) Employ a statistical technique using the
frequency of growth miracles and growth
disasters
Facts
• First define income:
• GDP per capita seems natural.
• But in developing countries nonmarket
production is quite important => GDP per
worker.
• This paper, GDP per worker relative to U.S.
GDP per worker.
World Income Distribution, 1960 1988
Comments on the figure
U.S. highest GDP per worker in both 1960 &
1988.
U.S. GDP per worker grew relatively steady 1.4
pct. annually from 1960 to 1988.
1960
• Single-peaked
• Hump is between
5 & 30 %
1988
• Twin-peaked
• Hump is between
20 & 65 %
Relative Y/L, 1960 vs. 1988
Comments on the figure
• Changes in world distribution of income are
illustrated by departures from the 45-degree line.
• Convergence at the top of the income
distribution.
• Divergence at the bottom.
• Growth miracles: Hong Kong, Korea, Botswana.
• Growth disasters: manly sub-Saharan countries.
Density of GDP Per Worker Weighted
by Population
Comments on the figure
• No divergence at the bottom.
• The income of the country containing the
median person has improved from 8.1 pct. of
U.S. income in 1960 to 11.8 pct. in 1988.
• The 75th percentile of the population lived in
a country with 22.5 pct. of U.S. income in
1960, but 40.3 pct. in 1988.
The Assumption of Similar Long-Term
Growth Rates
• Conceptural view:
• The argument is, that otherwise will the
income ratios between to countries with
different long-term growth rates diverge to
infinity.
• What about all the endogenous growth
literature (ex. technological progress )?
• All countries eventually grow at the average
rate of growth of world knowledge.
The Assumption of Similar Long-Term
Growth Rates
• Empirical view:
• U.S. grew at an average rate of 1.8 pct. per year
from 1870 to 1994 while UK only grew at 1.3 pct.
• The resolution of this apparent inconsistency is
transition dynamics.
• This means that countries are changing position
within the world income distribution, their
average growth rate can be faster or slower then
the growth rate of world knowledge over any
finite period.
Income in the U.S. and UK
The Future of the Global Income
Distribution
• Solow
• Transition dynamics
• Frequency of growth miracles
and growth disasters
Solow
• In the classical Solow model the long run level
of output per worker is a function of the rate
of investment in capital, the growth rate of
labor force, and the level of technology.
• All we need is to perdict where these variables
are going to settle.
Solow
• Jones (1997) incorporates human capital.
• He further assumes that investment rates and
population growth settles at the rates
prevailed in the 1980s.
Steady State Incomes, based on
Current Policies
Comments on the figure
• 1988 distribution is quite similar to the
distribution of steady states.
• Countries like Uganda and Malawi are not
poor because of transition dynamics but
because technology levels and investment
rates are low (population growth rates have
relatively small effects in most neoclassical
models).
Comments on the figure
• In the top of the income distribution a number of
countries are predicted to surpass the U.S. in GDP
per worker.
• Differences in income are driven by differences in
investment rates in physical and human capital.
• U.S. have a high technology level and investment
rate in human capital but too low to compensate
for the low U.S. capital investment rate.
Transition Dynamics and Steady State
• The growth rate of relative income is proportional
to the gab between the country’s current position
in the income distribution and it’s steady state.
• Ex. A country has a GDP per worker relative to
the U.S. of 0.4 and a steady state of 0.5 (20 pct.
gab). If speed of convergence is 5 pct. per year,
the actural GDP grows at 1 pct. plus the growth
rate of world technological progress (ass the U.S.
has reached its steady state).
Transition Dynamics and Steady State
• The key parameter ”speed of convergence” is
estimated to be between 2 and 6.
• When using data on growth rates from 1960
to 1988 and initial incomes in 1960 the steady
states can be calculated (assuming that
countries obey the principle of transition
dynamics over this 28-year period):
Convergence Speed of 2 pct.
Convergence Speed of 4 pct.
Convergence Speed of 6 pct.
Comments on the figures
• Countries that have grown faster then the U.S.
over the 28-year period are predicted to
continue to increase relative to the U.S.
• If the speed is slow the steady state must be
far away in order to explain a given growth
differential, implying large additional changes
in the income distribution.
The Very Long-Run Income
Distribution
• Until now policy has been assumed constant.
• Predicting when and where large changes in
institutions and economic policies will occur is
extremely difficult.
• Instead it’s possible to use the frequency of
growth miracles and growth disasters.
Frequency of Growth Miracles and
Growth Disasters
Comments on the table
• Fast growth and slow growth occur at roughly
the same frequency at the bottom of the
income distribution.
• For countries with incomes of more then 10
pct. of U.S. GDP per worker frequency of rapid
growth rises.
World Income Distribution, Using
Markov Transition Metod
Comments on the table
• The long-run results suggest that there is no
development trap into which the poorest
countries will be permantly condemned.
• Markov’s results strongly suggest that the
convergence will play a dominant role in the
continuing evolution of the income
distribution.
Conclusion
• Fast growth has been more common then slow
growth from 1960 to 1988.
• Countries have shown tendency to move up in
the income distribution.
• Viewed in terms of populatons, the recent
growth in China and India reinforces this
conclusion.
• The fact that the world have not allready reached
the long-run distibution indicates that the forces
currently shaping the income distribution are a
somewhat recent phenomenon.