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Chapter 1
The Facts
to Be Explained
About Our Author…
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A World of Rich and Poor
Source: Easterly and Levine (2001).
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A Country of Rich and Poor
Source: Easterly and Levine (2001).
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A Country of Rich and Poor
Source: Easterly and Levine (2001).
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Our Neighborhood of Rich and Poor
Source: Easterly and Levine (2001).
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Why Focus on GDP per Capita?
Economic Development – the overall “well-being” of a society.
Income per Person will be our proxy for “well-being.”
Income per Person is associated with many “goods.”
To take just a couple of examples…
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Trends in Infant Mortality, by Region
Annual number of deaths to infants under age 1 per 1,000 live births
133
99
93
89
81
52
48
22
21
7
World
Africa
Asia
1970-1975
Latin America
and the
Caribbean
More
Developed
Regions
2005-2010
Source: UN, World Population Prospects: The 2004 Revision (medium scenario), 2005.
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Population Living on Less Than US $2 per
Day
2002
Percent
78
75
50
41
23
World
South Asia
Sub-Saharan
Africa
East Asia
and the
Pacific
20
Latin America Middle East
and the
and North
Caribbean
Africa
Source: World Bank, World Development Indicators 2006.
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A More Holistic Measure of Living Levels
– the Human Development Index
HDI = 1/3 (Income Index) + 1/3 (life expectancy index) + 1/3 (education index)
• Income Index = log(GDP per cap) – log(100)
log (40,000) – log(100)
• Life Exp Index = life exp - 25
85 – 25
• Educ Index = (2/3) * (adult literacy/100) + (1/3) * (school enrollment/100)
Does this statistic do a better job at measuring “development?”
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HDI vs. Income
Income vs. HDI
HDI Value, 2003
1.200
1.000
0.800
0.600
0.400
0.200
0.000
0
10000
20000
30000
40000
50000
60000
70000
GDP per Capita (PPP US $ 2003)
Source: Human Development Report (2005).
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What About Happiness?
Subjective well-being rankings of 82 societies
(based on combined Happiness and Life Satisfaction scores)
HIGH
Puerto Rico 4.67
Mexico
4.32
Denmark
4.24
Ireland
4.16
Iceland
4.15
Switzerland 4.00
N. Ireland
3.97
Colombia
3.94
Netherlands 3.86
Canada
3.76
Austria
3.69
El Salvador 3.67
Venezuela
3.58
Luxembourg 3.52
U.S.
3.47
Australia
3.46
New Zealand 3.39
Sweden
3.36
Nigeria
3.32
Norway
3.25
Belgium
3.23
Finland
3.23
MEDIUM HIGH
Saudi Arabia
Singapore
Britain
W. Germany
France
Argentina
Vietnam
Chile
Philippines
Taiwan
Domin.Rep.
Brazil
Spain
Israel
Italy
E. Germany
Slovenia
Uruguay
Portugal
Japan
Czech Rep
3.01
3.00
2.92
2.67
2.61
2.61
2.59
2.53
2.32
2.25
2.25
2.23
2.13
2.08
2.06
2.02
2.02
2.02
1.99
1.96
1.94
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MEDIUM-LOW
S. Africa
Croatia
Greece
Peru
China
S. Korea
1.86
1.55
1.45
1.32
1.20
1.12
Iran
0.93
Poland
Turkey
Bosnia
Morocco
Uganda
Algeria
Bangladesh
Egypt
Hungary
Slovakia
Jordan
0.84
0.84
0.82
.74
0.67
0.57
0.54
0.52
0.41
0.40
0.39
LOW
Estonia
Serbia
Tanzania
Azerbaijan
Montenegro
India
Lithuania
Macedonia
Pakistan
Latvia
Albania
Bulgaria
Belarus
Georgia
Romania
Moldova
Russia
Armenia
Ukraine
Zimbabwe
Indonesia
0.24
0.21
0.13
0.13
0.06
0.03
-0.07
-0.14
-0.30
-0.70
-0.86
-0.87
-0.92
-1.11
-1.30
-1.63
-1.75
-1.80
-1.81
-1.88
-2.40
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Can You “Buy” Happiness?
Income vs Happiness
6
Well-Being Score
5
4
3
2
1
0
-1 0
10,000
20,000
30,000
40,000
50,000
60,000
-2
-3
GDP per capita
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Convergence vs. Divergence
• Japan’s story implies that countries initally
poor “converged” to living standards of the
rich. True in general?
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Are Poor Countries Catching Up?
Growth Rates vs. Per Capita Income for Currently Developed
Countries, 1870-1979
3.0
☻
Growth rate (%)
☻☻
☻
☻●
● ●
●
●
●●
●
●
●
●
1.0
0
Per capita income in 1870 (1975 dollars)
2,000
Source: Barrow and Sala-i-Martin (1995).
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Income Relative to U.S., 1988
GDP per Cap Relative to the U.S., 1960 vs. 1988
(log scale)
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Income Relative to U.S., 1960
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Growth Before 1820
• Growth was glacial (on average, 0.01% before 1500,
0.04% 1500 – 1700, 0.07% 1700 – 1820)….
– “Ups and downs certainly. Visitations of plague, famine, and
war. Golden intervals. But no progressive, violent change.”
• Income differences between countries were very
small.
• After 1820. some countries grew a lot, while others
were left behind.
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World Economic History in One Picture
Source: Clark (2005).
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Measuring and Comparing GDP Using
Purchasing Power Parity
• Three Big Issues with Income – measuring it,
comparing it over time, and comparing it
across countries.
– Measuring: Counting up all goods and services,
multiply by respective prices, and add ‘em up.
– Comparing Over Time: Due to inflation, need a
base year to construct a price index (price of a
basket of goods at one year)
– Comparing Over Countries: Since countries use
different currencies, why not just use official
exchange rates?
• Exchange rates very volatile
• While traded goods tend to have same price, non-traded
goods tend to be much cheaper in developing countries.
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Measuring and Comparing GDP Using
Purchasing Power Parity
Comparisons of GDP at market exchange rates
systematically understate the relative income of developing
countries.
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Problem from Book, pg. 26
Country
Computers
Ice Cream
Price of
Computers in
Local Currency
Price of Ice
Cream in Local
Currency
U. S.
12
4
2 dollars
4 dollars
China
3
1
1 yuan
1 yuan
Computers can be traded, ice cream can not.
a)
Calculate the level of GDP per capita in each country, measured in its own
currency.
b)
Calculate the market exchange rate between the currencies of the two
countries.
c)
What is the ratio of GDP per capita in the U.S. to GDP per capita in China,
using the market exchange rate?
d)
Calculate the purchasing power parity exchange rate between the two
currencies (Hint: calculate the cost of a “basket” of goods for each country).
e)
What is the ratio of GDP per capita in the U.S. to GDP per capita in China,
using the PPP exchange rate?
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Model vs Reality
• In models, we assume what is exogenous and
what is not.
• With some relationships, this is clear (rain fall
and crop height).
• With most economic relationships, it is not
(living standards, education, health, etc…).
• Economics is a science because we can
test these theories with data.
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General Issues with Economic Data
• Interesting things are often unmeasurable
(utility, social capital,…)
• Comparison often difficult – countries collect
info in different forms.
• Biases of official agencies
• Data is almost always observational, not
experimental
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Correlation vs. Causation
• Determining if x and y move together is
easy
• Corr coef:
Σ (x – meanx) (y - meany)______
sqrt ( (x – meanx)2) sqrt ( (x – meanx)2)
• Determining if x causes y is much harder
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Examples
1)
2)
3)
4)
5)
Every time I eat chocolate, it gives me acne.
Recent studies have proven that watching too much
violence on television leads to people being violent in
real life.
Researchers at the Aabo Akademi found that Finns who
speak the language of their Nordic neighbors were up to
25 percent less likely to fall ill than those who do not.
Most drug use occurs among the poor - this is because
poverty causes people to engage in risky behavior, like
abusing narcotics.
Morality in this nation has worsened at the same time
that adherence to traditional Christian beliefs has
declined. Obviously, the latter has caused the former, so
encouraging Christianity will ensure a return to
traditional moral standards.
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