lecture 1 economic growth and income diﬀerences...

Lecture 1

Economic Growth and Income Differences:

A Look at the Data

Rahul Giri∗

∗Contact Address: Centro de Investigacion Economica, Instituto Tecnologico Autonomo de Mexico (ITAM). E-mail:

[email protected]

Economic growth has been the centerpiece of the evolution of macroeconomics over the last

60 years. The main issues on economic growth that macroeconomics has focused on are:

• Cross-Country Income Differences: There is a great inequality in income levels (income

per capita and income per worker) across countries. Countries at the top of the world income

distribution are are more than 30 times as rich as those at the bottom. For example, in

2000, gross domestic product (GDP) per capita in the United States was more than $34, 000

whereas in Nigeria it was about $1, 000. In Mexico it was $8, 000, in China about $4, 000 and

in India just over $2, 500. These numbers are expressed in 2000 US dollars and are adjusted

for purchasing power parity (PPP). Furthermore, this inequality has somewhat increased over

time.

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Figure 1: Estimates of Distribution of countries according to PPP-adjusted GDP per capita

Source: “Introduction to Modern Economic Growth”, Daron Acemoglu, 2009, Princeton

University Press.

Source Data: Heston, Allen, Summers, Robert and Bettina Aten (2002), “Pen World Tables

Version 6.1.” Downloadable Data Set. Philadelphia: Center for International Comparisons

at the University of Pennsylvania.

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Figure 2: Estimates of Distribution of countries according to PPP-adjusted Log GDP per worker


University Press.




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Figure 3: Histogram for GDP per capita in 1960

Source: “Economic Growth” Robert J. Barro and Xavier Sala-i-Martin, 2nd ed., The MIT

Press.




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Figure 4: Histogram for GDP per capita in 2000


Press.




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So, in 1960 (the data is for 113 countries) the mean per capita GDP was $3, 390, measured in

PPP adjusted 1996 US dollars. Switzerland was the richest country with a per capita GDP

of $14, 980, which was 39 times the lowest per capita GDP value of $381 for Tanzania. The

US was second with a per capita GDP of $12, 270. Overall, the OECD countries along with

Argentina and Venezuela were the richest countries. Most of the Latin American countries

were in the middle of the distribution. The poorer countries were mix of African and Asian

countries, with the exception of some Asian countries who were in the middle of the distri-

bution. In 2000 (the data is for 150 countries) the mean per capita GDP was $8, 490, which

is 2.5 times the mean of 1960. The highest value of $43, 990 for Luxembourg was 91 times

the lowest value of $482 for Tanzania. The OECD countries still dominated the top group,

joined by some East Asian countries. Most other Asian countries were in the middle range of

per capita GDP, as were most Latin American countries. The poorest countries belonged to

Sub-Saharan Africa.

• Income and Welfare: So, what if there are such large income differences? Should we care?

Yes, we should. Income levels correlate very strongly with standards of living, and health.

The next two graphs show the association between GDP per capita and consumption per

capita, and that between GDP per capita and life expectancy at birth in 2000. We see that

the richest countries are not only producing 30 times as much as the poorest countries, but

are also consuming 30 times as much. Similarly, in the richest countries life expectancy at

birth is as high as 80 years while in the poorest countries it is only between 40 to 50 years.

Thus income levels show a strong positive correlation with welfare indicators. However, this

does not mean that every individual in a rich country is a winner. Very often during the

process of growth some individuals or groups of them are left behind.

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Figure 5: Association between GDP per capita and consumption per capita in 2000


University Press.




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Figure 6: Association between GDP per capita and life expectancy at birth in 2000


University Press.




Source Data: World Bank Development Indicators.

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• Economic Growth and Income Differences: The reason for such large cross-country

income differences is the difference in growth rates. To illustrate this point, consider two

countries with the same initial level of income. Suppose one country experiences 0% growth

in per capita income, whereas the other country grows at 2% per capita. Then in 200 years the

country with 2% growth rate will be more than 52 times richer than than the other country.

Let us look at how different countries and regions of the world have grown over time. The

first graph that follows shows the estimated distribution of growth rate of GDP per worker

(PPP adjusted) for 1960 (geometric average over 1950 and 1969), 1980 (geometric average

over 1970 and 1989) and 2000 (geometric average over 1990 and 2000). There is a significant

variability in the growth rates in every period. Furthermore, the variability has increased

over time.

The next graph shows the detail of countries in the distribution of growth rate of per capita

GDP from 1960-2000. It shows that sub-Saharan Africa grew at the slowest rate, and given

that these countries started with the lowest GDP per capita levels they ended at the lowest

per capita GDP levels in 2000. Asia, on the other hand, started slightly higher than Africa

and in may cases grew more rapidly and ended up mostly in the middle of the distribution.

Latin America started in the mid to high range of per capita GDP but grew at slower rate

than Asia and therefore ended up in the middle with Asia. Lastly, OECD countries started

the highest and grew in the middle range of growth rates and therefore ended up at the top

of income levels in 2000.

The last graph shows the evolution of log per capita GDP from 1960 to 2000 for some specific

countries to illustrate how some countries experienced rapid growth in per capita GDP while

others fell behind even though they started with higher income levels.

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Figure 7: Estimates of distribution of countries according to growth rate of GDP per worker


University Press.




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Figure 8: Histogram of growth rate of per capita GDP from 1960 to 2000


Press.




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Figure 9: Evolution of lof GDP per capita from 1960 to 2000


University Press.




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• Going Back in History: So, should we conclude that the differences in the growth rates

across countries in post-war era can explain the per capita income differences? The answer

is no. This is because large per capita income differences already existed in 1960. The first

figure that follows plots log GDP per worker of a country in 2000 versus log GDP per capita

of the same country in 1960 (in both cases relative to the US value). Most observations are

around the 45 degree line, which implies that the relative ranking of countries has changed

little between 1960 and 2000. Thus, the ultimate origins of of very large income differences

across nations are older than we think. In other words, the world income distribution has

been fairly stable over a long time period, with a slight tendency to become more unequal.

But, then the question to ask is when did this growth gap emerge? The answer is that much

of this gap was created in the nineteenth and early twentieth century. The second figure

that follows, using PPP adjusted data compiled by Angus Maddison, shows the evolution

of GDP per capita for five groups of countries. The Western offshoots of Europe include

Australia, Canada, New Zealand and the US. It shows that during the nineteenth century

Western Europe and Western offshoots of Europe experienced rapid growth while Africa and

Asia remained stagnant and Latin America showed little growth. The relatively small income

gap in 1820 became much larger by 1960.

Going back further, evidence suggests that income gaps were even smaller. The third figure

that follows shows evolution of average of GDP per capita for the same group of countries

starting from 1000 A.D.. Although the data is not very reliable, its shows the same trends

as we observed in the earlier graph. Another aspect of the process of economic growth that

becomes clear from this graph is that each set of the countries experiences a “take-off ” (or

“industrial revolution”) in GDP per capita. The first to experience the take-off was Western

Europe starting in 1800s, followed by the Western offshoots, followed by the others though

not so much Africa. Macroeconomists and historians, alike, have asked why the take-off did

not take place before 1800s; why it started in Western Europe and then spread to other parts

of the world and what the are the drivers of such rapid and sustained growth in GDP per

capita? The last figure shows that evolution of income for some specific countries since 1820.

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Figure 10: Log GDP per worker in 200 versus log GDP per capita in 1960


University Press.




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Figure 11: Evolution of average GDP per capita, 1820-2000


University Press.

Source Data: Historical Data compiled by Angus Maddison.

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Figure 12: Evolution of average GDP per capita, 1000-2000


University Press.


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Figure 13: Evolution of GDP per capita in specific countries, 1820-2000


University Press.


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• Conditional Convergence: The data so far suggests that large income differences across

countries emerged in ninteenth and early twentieth century, and over time these differences

have increased. However, our analysis has looked at the unconditional distribution of in-

come across countries, i.e. we looked at whether income gap between countries increased

or decreased regardless of countries’ characteristics. Barro and Sala-i-Martin argue that one

should look at conditional distribution of income. In fact, they find that in the post-war era

income gaps between countries with similar characteristics become smaller over time. The

first graph that follows shows that for the world there is no tendency for convergence. There is

no relationship between the average growth rate of GDP from 1960 to 2000 and the log GDP

per worker in 1960. However, when we plot the same relationship for the OECD countries,

there is a strong negative relationship, i.e. countries that had higher GDP per worker in 1960

had lower growth rate of GDP over 1960-2000. Thus, the relatively poor countries in the

OECD showed a tendency to catch-up with the rich ones. The OECD countries share similar

characteristics in terms of institutions, policies, and initial conditions. Thus, there might be

some type of conditional convergence when we control for certain country characteristics that

potentially affect economic growth.

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Figure 14: Conditional Convergence for the World


University Press.




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Figure 15: Conditional Convergence for the OECD


University Press.




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• Correlates of Economic Growth: So what factors drive the process of economic growth,

i.e. what are the causal factors? Isolating the causal factors is not an easy task because of

the interaction between the potential factors and that between economic growth and these

factors. Therefore, for now, we will look at the correlation between economic growth and

potential factors that theories of economic growth have focused on. The first figure that

follows shows a strong positive correlation between growth rate of GDP per capita and the

average “investment” rate. The second figure that follows shows a positive correlation between

growth rate of GDP per capita and years of schooling. These figures suggest that rapid growth

countries have invested more in physical and human capital. These are not the only factors

that correlate with growth, but are the factors that theory has focused on. Another important

factor that theory has focused on is technology.

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Figure 16: Correlation between average growth rate of GDP per capita and average growth of

investments to GDP ratio, 1960-2000


University Press.




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Figure 17: Correlation between average growth rate of GDP per capita and average years of school-

ing, 1960-2000


University Press.




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So, even if these correlations between economic growth and physical capital, human capital

and technology are in fact also causal relationships and these factors are the drivers of eco-

nomic growth, the question that one would like to answer is that why some of the countries

failed to invest in physical capital, human capital and technology? Thus, fundamental factors

that lie behind these proximate causes of growth are what we would like to understand in

order to truly understand the process of economic growth.

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