chapter 1 the facts to be explained. copyright © 2005 pearson addison-wesley. all rights reserved....

Chapter 1

The Facts to Be Explained

Copyright © 2005 Pearson Addison-Wesley. All rights reserved. 1-2

About Our Author…


A World of Rich and Poor

Source: Easterly and Levine (2001).


A Country of Rich and Poor



Our Neighborhood of Rich and Poor



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…


Annual number of deaths to infants under age 1 per 1,000 live births

81

99

133

93

21

89

52

7

22

48

World Africa Asia Latin Americaand the

Caribbean

MoreDeveloped

Regions

1970-1975 2005-2010

Trends in Infant Mortality, by Region

Source: UN, World Population Prospects: The 2004 Revision (medium scenario), 2005.


Population Living on Less Than US $2 per Day

2002Percent

50

7875

41

23 20

World South Asia Sub-SaharanAfrica

East Asia and thePacific

Latin Americaand the

Caribbean

Middle Eastand North

Africa

Source: World Bank, World Development Indicators 2006.


A More Holistic Measure of Living Levels – the Human Development Index

• Income Index = log(GDP per cap) – log(100)log (40,000) – log(100)

• Life Exp Index = life exp - 2585 – 25

• Educ Index = (2/3) * (adult literacy/100) + (1/3) * (school enrollment/100)

Does this statistic do a better job at measuring “development?”

HDI = 1/3 (Income Index) + 1/3 (life expectancy index) + 1/3 (education index)


HDI vs. Income

Income vs. HDI

0.000

0.200

0.400

0.600

0.800

1.000

1.200

0 10000 20000 30000 40000 50000 60000 70000

GDP per Capita (PPP US $ 2003)

HD

I Val

ue,

200

3

Source: Human Development Report (2005).


What About Happiness?Subjective well-being rankings of 82 societies

(based on combined Happiness and Life Satisfaction scores) HIGH MEDIUM HIGH MEDIUM-LOW LOW 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

Saudi Arabia 3.01 Singapore 3.00 Britain 2.92 W. Germany 2.67 France 2.61 Argentina 2.61 Vietnam 2.59 Chile 2.53 Philippines 2.32 Taiwan 2.25 Domin.Rep. 2.25 Brazil 2.23 Spain 2.13 Israel 2.08 Italy 2.06 E. Germany 2.02 Slovenia 2.02 Uruguay 2.02 Portugal 1.99 Japan 1.96 Czech Rep 1.94

S. Africa 1.86 Croatia 1.55 Greece 1.45 Peru 1.32 China 1.20 S. Korea 1.12 Iran 0.93 Poland 0.84 Turkey 0.84 Bosnia 0.82 Morocco .74 Uganda 0.67 Algeria 0.57 Bangladesh 0.54 Egypt 0.52 Hungary 0.41 Slovakia 0.40 Jordan 0.39

Estonia 0.24 Serbia 0.21 Tanzania 0.13 Azerbaijan 0.13 Montenegro 0.06 India 0.03 Lithuania -0.07 Macedonia -0.14 Pakistan -0.30 Latvia -0.70 Albania -0.86 Bulgaria -0.87 Belarus -0.92 Georgia -1.11 Romania -1.30 Moldova -1.63 Russia -1.75 Armenia -1.80 Ukraine -1.81 Zimbabwe -1.88 Indonesia -2.40


Can You “Buy” Happiness?

Income vs Happiness

-3

-2

-1

0

1

2

3

4

5

6

0 10,000 20,000 30,000 40,000 50,000 60,000

GDP per capita

We

ll-B

ein

g S

core


Convergence vs. Divergence

• Japan’s story implies that countries initally poor “converged” to living standards of the rich. True in general?


Are Poor Countries Catching Up?

☻ ☻ ☻

0 2,000

1.0

3.0

Per capita income in 1870 (1975 dollars)

Gro

wth

rat

e (%

)

Growth Rates vs. Per Capita Income for Currently Developed Countries, 1870-1979

☻

● ● ● ●

● ● ● ●

●

●

●

☻

Source: Barrow and Sala-i-Martin (1995).


GDP per Cap Relative to the U.S., 1960 vs. 1988 (log scale)

Income Relative to U.S., 1960

Inco

me

Rel

ativ

e to

U.S

., 19

88


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.


World Economic History in One Picture

Source: Clark (2005).


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.


Measuring and Comparing GDP Using Purchasing Power Parity

Comparisons of GDP at market exchange rates systematically understate the relative income of developing countries.


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?


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.


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


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


Examples

1) Every time I eat chocolate, it gives me acne.

2) Recent studies have proven that watching too much violence on television leads to people being violent in real life.

3) 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.

4) Most drug use occurs among the poor - this is because poverty causes people to engage in risky behavior, like abusing narcotics.

5) 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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