Evidence on how Population and
Reproductive Health Impact Economic
Growth and Poverty Reduction
David Canning
Harvard School of Public Health
November 2, 2006
Theory and Evidence
• Theoretical models tell us what evidence
to look for.
• There are many mechanisms that
potentially link population to growth and
poverty reduction.
• Evidence of a narrow focus in the past on
the effect of population growth rate on
economic growth.
Theory: Population Effects on
economic growth
• Malthusian
– exhaustible resources (climate)
• Neo-classical growth theory
– capital dilution
• Positive scale effects
– technological progress and agglomeration
externalities
Impact of population growth on economic
growth
• Use cross-national data.
• Standard finding was of little effect of
population growth on economics growth
(NAS Report 1986).
• Result still holds today.
The 1986 Report in Historical Context
• The report was “revisionist” (Kelley 2001) as
opposed to other “population-alarmist”
reports.
• The authors were economists and allowed for
market and institutional mechanisms that may
alleviate the negative consequences of
population growth.
Critiques
• We have been looking at the wrong level
of aggregation. Many effects may occur
only at the global or city level.
• Other theoretical models would make us
look at different evidence.
• Test conflates several different effects.
Other Theories
• Quality- quantity tradeoff
– health and education of children
• Maternal health and productivity
• Female labor market participation
• Transition from family support to saving for old
age
• Age structure effects –
– Labor supply and saving vary with age.
• Differential effects of fertility, mortality and
migration
Components of Population Growth
• Population growth can be decomposed into
the crude birth rate, minus the crude death
rate, plus inward migration.
• Looking at effects of population growth as a
whole assumes these components have
exactly equal effects - the effect of a birth is
the same as an inward migrant or a death
avoided.
• The economic impact of changes the birth
rate, death rate, and migration rate are likely
to be very different.
Mortality and Health
• Low death rates are associated with
healthier populations; evidence has
emerged for such an effect in both the
micro and macro literature.
• It is common to capture health in growth
regressions by life expectancy
• This “health productivity” can be separated
from the population effect
Crude Birth Rate vs. Crude Death Rate, 1800-2000
50
Population grow th
rate = 2%/yr
Population grow th
rate = 1%/yr
Population grow th
rate = 0%/yr
1950
Crude Birth Rate (per 1,000)
40
30
2000
Sweden
1900
1900
1800
Japan
20
India
10
2000
0
0
10
20
30
40
Crude Death Rate (per 1,000)
50
Demography and Growth
• Low birth rate and low death rate are both
associated with faster economic growth.
• A high (and rising ) ratio of working age to
dependent population is associated with
economic growth.
• The effect is robust in growth models and
help forecast economic growth.
• Identification – timing. Past demography is
uncorrelated with future growth shocks.
Age Structure and Accounting
• There is an accounting effect of age
structure, where we take age specific
behavior to be constant and look at the
effect of a changing age pattern.
• This gives large effects of age structure
change on labor supply and saving.
• Age structure can be written as a function
of past fertility, mortality and migration
rates.
Total labor force participation rates by age group
90
80
70
Participation rate
Bolivia 1996
60
Dominican Rep 1996
50
Ecuador 1995
El Salvador 1995
40
Honduras 1998
Nicaragua 1993
30
Peru 1997
20
10
0
15-18 19-24 25-29 30-34 35-39 40-45 45-49 50-54 55-59 60-64
Age cohort
65+
Income and Consumption by Age,
Taiwan 1998
500000
400000
300000
200000
100000
0
-100000 0
Income
Consumption
20
40 Age 60
80
100
Demography and Saving
• Investment rates in most countries are closely
tied to domestic savings rates.
• Savings rates vary with age. Changing age
structure towards the older working age groups
(who have high savings rates) tends to increase
national savings rates.
• Macro effects are larger than those found by
calibration based on micro data – perhaps due to
the fact that aging populations have longer life
expectancy generating higher savings rates for
retirement at all ages.
Thousands
US Foroign Born Population Entered 2000-2003 by Age
1,000
900
800
700
600
500
400
300
200
100
0
0
10
20
30
40
50
Age
60
70
80
90
East Asia: Age Structure
160
140
120
Population 100
(m illions)
80
2050
60
2025
40
2000
20
0
0-4
1975
1950
10 14
20 24
30 34
40 44
50 54
60 64
Age group
70 74
80 84
90 94
100+
Year
Sub-Saharan Africa: Age Structure
180
Population (millions)
160
140
120
100
80
2040
60
2010
40
1980
20
1950
0
0 - 4 10 - 20 - 30 - 40 - 50 - 60 - 70 - 80 - 90 - 100+
14 24
34 44 54
64 74 84
94
Age group
Year
Ratio of Working Age to Dependant Population
2.5
2.0
Ratio
1.5
1.0
East Asia
USA
Sub-Saharan Africa
South Asia
Europe
0.5
0.0
1950
1960
1970
1980
1990
2000
Year
2010
2020
2030
2040
2050
Interactions
• High rates of growth of the working age
population produce an increase in labor supply.
• This supply must be met by demand if it is to be
employed.
• We have evidence that the beneficial effects of
age structure change only occur in countries with
good institutions and economic policies
• Estimation different from calibration
Poverty Reduction
• Cross country poverty and inequality data is very
low quality.
• Little evidence of an effect of fertility on inequality
in macro data (poor get proportional benefits).
• Some evidence that demographic transition
occurs first among the better off, widening
income inequality.
• The poorer families “catch up” later in the
transition.
Economic Growth, Welfare, and
Population Policy
• We find that lower fertility promotes growth
in GDP per capita. However, GDP per
capita is not a welfare measure. A broader
notion of welfare is required.
• If the benefits and costs of fertility fall
entirely on the family, we should aim to
achieve desired fertility. We do not have
evidence here of externalities (need to
compare effect within and across families).
Poverty Trap
• The temporary boost in GDP per capita due to
the demographic transition may help countries
escape from a poverty trap.
• The feedbacks from income, health and
education to fertility are a technical problem for
identifying the direction of causality.
• They are conceptually important in
understanding the process of development since
they set up a self reinforcing, positive feedback,
system
• Points to research on determinants of desired
fertility, and the system, as well as the
consequences of filling unmet need.
Casual Effects in Microdata
• Determining the effects of mortality, fertility, and
migration pose quite different problems
• Desired fertility is a choice and is the product of a
joint decision.
• Random shocks (unplanned births, infertility)
identify the effect of fertility on behavior.
• Access to family planning for unmet need is a
good instrument as it is also the likely policy
intervention.
• Changing desired fertility is likely to have
different effect from providing services to reduce
unmet need.
Micro Evidence
• Large family size is associated with
poverty.
• Few studies try to get at causality
• Twins and sex composition (with male
preference) are not good instruments.
Microeconomic evidence:
the economic effects of lowering fertility
– determining causality
• Miller, 2005, quasi-random placement of
family planning services in Columbia,
effects of women’s education and labor
supply.
• Joshi and Schultz, 2006, MATLAB family
planning experiment in Bangladesh, effect
on child health, woman’s health, and
income.
Focus: Theory
• Which mechanism (theoretical effect) is to
be focused on?
• Can we determine causality rater than
association.