Literature Economic Development and Policy:
(for deeper understanding read lecture notes too, especially for estimates and econometric calculations)
Lecture 1
Acemoglu & Johnson (2007) - The Effect of Life Expectancy on Economic Growth
Introduction:
Social objective is to improve health around the world. There is consensus that improving health can have equally large indirect
payoffs through accelerating economic growth, but there is no established causal effect of health and disease on economic
growth.
Even among the poor or middle income, LE tends to go closer to initially rich people.
In addition, international epidemiological transition provides us with an empirical stratefy to isolate exogenous changes in
Health conditions
• before 1940s specific conditions such as tuberculosis and malaria
• then: global health interventions such as penicillin, DDT against mosquitoes
• GDP case: GDP per capita and GDP per working age population show relative declines in countries
experiencing large increases in life expectancy.
This picture shows no convergence in income per capita. Explanation? Neoclassical growth theory.
Increased LE raises population, which reduces capital-to-labor and labor-to-labor ratios —> depression of income per capita.
Part II: equations and calculus
,Part III: Background and Data:
Despite early improvements in public health in western Europe, the US and other places, there were limited improvements in
Africa, Asia and South and Eastern Europe (1940s). The situation changed due to three factors:
1. Global drugs and chemical innovations + antibiotics and vaccination
2. Establishment of WHO
3. Change in international values
They collected data on 15 of the most infectious diseases across a wide range of countries before the 1940s
a. Tuberculosis
b. Malaria
c. Pneumonia
d. Influenza
e. Cholera
f. Typhoid
g. Smallpox
h. Whooping cough
i. Measles
j. Diphtheria
k. Scarlet fever
l. Yellow fever
m. Typhus fever
n. Diarrhea
They looked at key variables: LE at birth, LE at different ages, total births.
Then they performed the OLS estimates:
, Then they outlined a source of exogenous variation in LE that may help estimate causal effects between life expectancy and
economic variables:
, Table 4: determine the role of the diseases when excluding one at a time (4-7). Tuberculosis and Pneumonia the most
impactful because the furthest from the baseline values (1-3).
Strong negative correlation in base sample!!
This shows the same relationship without the richest countries. It shows that the first-stage relationship is not driven by the
comparison of initially rich countries to initially low- and middle-income countries.
(for deeper understanding read lecture notes too, especially for estimates and econometric calculations)
Lecture 1
Acemoglu & Johnson (2007) - The Effect of Life Expectancy on Economic Growth
Introduction:
Social objective is to improve health around the world. There is consensus that improving health can have equally large indirect
payoffs through accelerating economic growth, but there is no established causal effect of health and disease on economic
growth.
Even among the poor or middle income, LE tends to go closer to initially rich people.
In addition, international epidemiological transition provides us with an empirical stratefy to isolate exogenous changes in
Health conditions
• before 1940s specific conditions such as tuberculosis and malaria
• then: global health interventions such as penicillin, DDT against mosquitoes
• GDP case: GDP per capita and GDP per working age population show relative declines in countries
experiencing large increases in life expectancy.
This picture shows no convergence in income per capita. Explanation? Neoclassical growth theory.
Increased LE raises population, which reduces capital-to-labor and labor-to-labor ratios —> depression of income per capita.
Part II: equations and calculus
,Part III: Background and Data:
Despite early improvements in public health in western Europe, the US and other places, there were limited improvements in
Africa, Asia and South and Eastern Europe (1940s). The situation changed due to three factors:
1. Global drugs and chemical innovations + antibiotics and vaccination
2. Establishment of WHO
3. Change in international values
They collected data on 15 of the most infectious diseases across a wide range of countries before the 1940s
a. Tuberculosis
b. Malaria
c. Pneumonia
d. Influenza
e. Cholera
f. Typhoid
g. Smallpox
h. Whooping cough
i. Measles
j. Diphtheria
k. Scarlet fever
l. Yellow fever
m. Typhus fever
n. Diarrhea
They looked at key variables: LE at birth, LE at different ages, total births.
Then they performed the OLS estimates:
, Then they outlined a source of exogenous variation in LE that may help estimate causal effects between life expectancy and
economic variables:
, Table 4: determine the role of the diseases when excluding one at a time (4-7). Tuberculosis and Pneumonia the most
impactful because the furthest from the baseline values (1-3).
Strong negative correlation in base sample!!
This shows the same relationship without the richest countries. It shows that the first-stage relationship is not driven by the
comparison of initially rich countries to initially low- and middle-income countries.
