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Fertility,
the Demographic Dividend,
and Economic GrowthDavid E. Bloom,
David Canning
Günther Fink
Jocelyn E. Finlay
Harvard School of Public Health
Fourth Annual Research Conference on Population, Reproductive Health, and Economic Development
Cape Town, January 2010
Effects of Fertility
on Income per Capita
Investigate the effects of fertility on income
Control for endogeneity by using changes in
abortion law as an instrument. About 26% of
pregnancies end in abortion.
Look at the mechanisms through which fertility
operates
Income per worker
Labor force participation
Working age share of population
Not Population Growth!
Population growth is fertility rate – mortality
rate + net migration.
Fertility rate and mortality rate have very
different economic effects.
The “effect of population growth” is not well
defined unless we know the source of the
growth.
Caveats
Income per capita is not a welfare measure
Focus on average income not distribution and
poverty
Macro income per capita still interesting. Macro
can capture effects micro misses
Social norms in behavior
Thresholds and critical value effects
Social Spillovers Micro model
Difficult to estimate since endogenous and
common to everyone in the community
Macro model
y x y
y x y
y
1y x
Figure 4: Income per Capita
and Fertility in 2000
Albania
Algeria
Antigua and Barbuda
Argentina
Armenia
AustraliaAustria
Azerbaijan
Bahamas, TheBahrain
Bangladesh
Barbados
Belarus
Belgium
Belize
Benin
Bosnia and Herzegovina
BotswanaBrazil
Brunei
Bulgaria
Burkina Faso
Burundi
Cambodia
Cameroon
Canada
Cape Verde
Central African RepublicChad
Chile
China
Colombia
Comoros Congo, Rep.
Costa Rica
Cote d'Ivoire
Croatia
Cuba
Cyprus
Czech Republic
Denmark
Djibouti
Dominica
Dominican Republic
EcuadorEgypt, Arab Rep.El Salvador
Equatorial Guinea
Eritrea
Estonia
Ethiopia
Fiji
FinlandFrance
Gabon
Gambia, The
Georgia
Germany
Ghana
Greece
Guatemala
Guinea
Guinea-Bissau
HaitiHonduras
Hungary
Iceland
India
Indonesia
Iran, Islamic Rep.
IrelandIsraelItaly
Jamaica
Japan
Jordan
Kazakhstan
KenyaKiribatiKorea, Dem. Rep.
Korea, Rep.
Kuwait
Kyrgyz Republic
Lao PDR
Lebanon
Lesotho
Liberia
Lithuania
Luxembourg
Macedonia, FYR
MadagascarMalawi
Malaysia
Maldives
Mali
Malta
Mauritania
Mauritius
Mexico
Micronesia, Fed. Sts.
Moldova
Mongolia
Morocco
Mozambique
Namibia
Nepal
Netherlands
New Zealand
Nicaragua
Niger
Nigeria
Norway
Oman
Pakistan
Panama
Papua New GuineaPeruPhilippines
Poland
Portugal
Qatar
Romania
Russian Federation
Rwanda
Samoa
Sao Tome and Principe
Saudi Arabia
Senegal
Sierra Leone
Singapore
Slovak Republic
Slovenia
Solomon Islands
Somalia
South Africa
Spain
Sri Lanka
St. Kitts and Nevis
St. LuciaSt. Vincent and the Grenadines
Sudan
Suriname
Swaziland
SwedenSwitzerland
Syrian Arab RepublicTajikistan
Tanzania
Thailand
Togo
Tonga
TunisiaTurkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United Kingdom
United States
Uruguay
UzbekistanVanuatu
Venezuela, RB
Vietnam
Yemen, Rep.
Zambia
Zimbabwe
67
89
1011
Log
Rea
l GD
P p
er C
apita
, 200
0
0 2 4 6 8TFR, 2000
Mechanisms
Most economic models focus on income per
worker effects – Malthus, Solow
We also have effects on workers per capita
Age structure – working age share
Female labor force participation
Workers per capita is bounded – cannot explain
long run growth but can vary a lot in the
“medium” term
Components of Income per Capita
Identity
t t t t
t t t t
Y Y L W
P L W P
log log log logt t t t
t t t t
Y Y L W
P L W P
Income per worker
Land per worker
Malthusian effect, number of workers
Capital per worker
Solow effect, growth rate of workforce
Savings rather than children for old age security
Human capital per worker
Investment in children, quality quantity tradeoff
Income per worker: Timing
Most effects only occur when fertility affects
growth in labor force. Time lag of 15-20 years
before children enter the labor force.
Large effects after long run adjustment to steady
state – income to investment - several
generations.
Working Age Share
Lower fertility always reduces the youth dependency rate.
Lower fertility lowers the number of worker age people in 20-60 years, increasing old age dependency
Turning point in overall effect is close to replacement fertility.
Youth dependency effect is immediate. Old age dependency effect is longer run.
Figure 1: Relationship between fertility and steady
state working age share
0%
10%
20%
30%
40%
50%
60%
70%
0 1 2 3 4 5 6 7 8 9
Total fertility rate
Wor
kin
g ag
e sh
are
Life expectancy 40 years (Zambia, 2005)
Life expectancy 60 years Yemen, 2005)
Life expectancy 80 years (France, 2005)
Figure 2: Total fertility rates and
working age shares in 2000
AlbaniaAlgeria
Angola
Argentina
Armenia
AustraliaAustria
Azerbaijan
Bahamas, The
Bahrain
Bangladesh
BarbadosBelarus
Belgium
Belize
Benin
Bolivia
Bosnia and Herzegovina
Botswana
BrazilBrunei
Bulgaria
Burkina FasoBurundi
Cambodia
Cameroon
Canada
Cape Verde Central African Republic
Chad
Chile
China
Colombia
Comoros
Congo, Rep.
Costa Rica
Cote d'Ivoire
Croatia
Cuba
Cyprus
Czech Republic
Denmark
Djibouti
Dominican RepublicEcuador
Egypt, Arab Rep.El Salvador
Equatorial GuineaEritrea
Estonia
Ethiopia
Fiji
Finland
France
Gabon
Gambia, The
Georgia
Germany
Ghana
Greece
GuatemalaGuinea
Guinea-Bissau
Guyana
HaitiHonduras
Hungary
Iceland
India
Indonesia
Iran, Islamic Rep.
Ireland
Israel
Italy
Jamaica
Japan
Jordan
Kazakhstan
Kenya
Korea, Dem. Rep.
Korea, Rep.Kuwait
Kyrgyz Republic
Lao PDR
Lebanon
Lesotho
Liberia
Libya
LithuaniaLuxembourgMacedonia, FYR
MadagascarMalawi
Malaysia
Maldives
Mali
Malta
Mauritania
Mauritius
Mexico
Micronesia, Fed. Sts.
Moldova
MongoliaMorocco
MozambiqueNamibia
Nepal
Netherlands
New Zealand
Nicaragua
Niger
Nigeria
Norway
Oman
Pakistan
Panama
Papua New GuineaParaguay
Peru
Philippines
PolandPortugal
Qatar
RomaniaRussian Federation
Rwanda
SamoaSao Tome and Principe
Saudi Arabia
Senegal
Sierra Leone
Singapore
Slovak RepublicSlovenia
Solomon Islands
Somalia
South Africa
SpainSri Lanka
St. LuciaSt. Vincent and the Grenadines
Sudan
Suriname
Swaziland
Sweden
Switzerland
Syrian Arab Republic
TajikistanTanzania
Thailand
Togo
Tonga
TunisiaTurkey
Turkmenistan
Uganda
Ukraine
United Arab Emirates
United KingdomUnited States
Uruguay
Uzbekistan
Vanuatu
Venezuela, RBVietnam
Yemen, Rep.Zambia
Zimbabwe
4050
6070
80
Wor
king
age
/Pop
ulat
ion
0 2 4 6 8Total fertility rate
Household Model
Utility
Time Constraint
Consumption
1 fl d bf
f f mc w l w e
0( , , , ) log log ( ) ( )e
U c d f e c c d f k N ff
Household Decisions
Female labor supply
Fertility
Investment in children
0( )11
(1 )
mf
f
e c wl bf
w
1 flf
b k
0
1f f me w l w c
Effects of Fertility
Female labor supply adjusted for investment in
children
Investment per child adjusted for labor supply
1f
f
l bfw
(1 ) /m ftf
t t
w wew b
f f
Female Labor Force Participation
High labor force participation in poor countries –
possible to work and care for children at the same
time.
Fertility to female labor supply effect may appear
when women have formal sector work where
child care and work time are separated.
Migration to urban areas may split extended
family links that provide childcare.
Income per Capita and Female Labor Force
Participation, 2000
Tanzania
Mozambique
Sudan
Egypt
Thailand
Iceland
US
0
10
20
30
40
50
60
70
80
90
100
6 6.5 7 7.5 8 8.5 9 9.5 10 10.5 11
Log (Real GDP per Capita 2000)
Fem
ale
Lab
or F
orce
Par
tici
pati
on R
ate
2000
Quality Quantity Tradeoff
Increased investment in children as fertility declines
May be household effect or effect via government spending
Influences income per worker in the long run
Short run effect on school enrollment
Enrollment may not reflect all investment educational quality, health
Figure 3: Change in the
Total Fertility Rate 1960-2000
Algeria
Australia
Barbados
Belgium Benin
Brazil
Burkina Faso
Cameroon
Canada
Cape Verde
Chad
Chile
China
Congo, Rep.
Denmark
Dominican Republic
Egypt, Arab Rep.El Salvador
Equatorial Guinea
Ethiopia
France
Gambia, The
Ghana
Greece
Guatemala
Guinea
Guinea-Bissau
HondurasIndia
Indonesia
Iran, Islamic Rep.
Ireland
IsraelItaly
Jamaica
Japan
Jordan
Kenya
Korea, Rep.
Lesotho
Luxembourg
Madagascar
Malawi
Malaysia
Mali
Mauritius
MexicoMorocco
Mozambique
Netherlands
New Zealand
Nicaragua
Niger
Nigeria
Pakistan
Panama
Peru
Philippines
Portugal
Romania
Rwanda
Senegal
Singapore
South Africa
Spain
Sri Lanka
SwedenSwitzerland
Syrian Arab Republic
Tanzania
Thailand
Togo
Turkey
Uganda
United Kingdom
United States
Uruguay
Venezuela, RB
Zimbabwe
-6-4
-20
2
Cha
nge
in T
FR
196
0-20
00
1 2 3 4 5 6 7 8 9 10Total fertility rate, 1960
Abortion Laws
Figure 5: Abortion Index:
Average 1960-2005
2
2.5
3
3.5
4
4.5
5
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
Year
Inde
x (s
ampl
e av
erag
e)
Are Abortion Laws Exogenous?
Timing of changes may be exogenous.
Contingent factors in many examples.
Extreme views and majority rule give sharp discontinuities in legal changes.
French and UK liberalization had spillover effects to former colonies. Laws often used as templates for changes to laws “inherited” at independence.
We use laws not enforcement.
Table 3 The effect of Fertility
on Income per Capita
(4) (5) (6)
Dependent variable: log GDP per capita
Total fertility rate -0.369*** -0.551*** -0.196**
(0.026) (0.160) (0.086)
Year dummies Yes Yes Yes
Country fixed effects No Yes Yes
Regional time trends No No Yes
Estimation method IV IV IV
Observations 1169 1169 1169
R-squared 0.541 0.897 0.957
Cragg-Donald F-stat 373.0 16.15 35.05
Table 4 First Stage: The effect of Abortion Laws
on Fertility
(1) (2) (3)
Dependent variable: Total fertility rate
Abortion index -0.410*** -0.072*** -0.096***
(0.020) (0.020) (0.018)
Year dummies Yes Yes Yes
Country fixed effects No Yes Yes
Regional time trends No No Yes
Observations 1169 1169 1169
R-squared 0.354 0.928 0.950
Note: Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1
Table 5: The Effect of Fertility on the
Components of Income per Capita (1) (2) (3) (4)
Dependent variable: ln(GDP/P) ln(GDP/L) ln(L/W) ln(W/P)
Total fertility rate -0.196** -0.061 -0.071*** -0.068***
(0.089) (0.085) (0.019) (0.010)
Year dummies Yes Yes Yes Yes
Country fixed effects Yes Yes Yes Yes
Regional time trends Yes Yes Yes Yes
Estimation method IV IV IV IV
Observations 1169 1105 1129 1145
R-squared 0.957 0.965 0.897 0.941
Cragg-Donald F-stat 35.05 32.38 32.75 34.49
Note: Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1
Table 6: The Effect of Fertility on Income per
Capita: Mechanisms
(1) (2) (3) (4)
Dependent variable: Log capital per
worker
Population
growth rate
Female labor
force
participation rate
Male labor
force
participation rate
Total fertility rate 0.021 0.645*** -9.947*** 0.495
(0.099) (0.292) (2.210) (0.695)
Year dummies Yes Yes Yes Yes
Country fixed effects Yes Yes Yes Yes
Regional time trends Yes Yes Yes Yes
Estimation method IV IV IV IV
Observations 1105 999 1129 1129
R-squared 0.976 0.690 0.906 0.897
Cragg-Donald F-stat 32.38 14.87 32.75 32.75
Table 6: The Effect of Fertility on Income per
Capita: Mechanisms
(5) (6) (7)
Dependent variable: Working age share
Youth
dependency
rate
Old-age
dependency
rate
Total fertility rate -4.076*** 12.38*** -0.964**
(0.646) (1.780) (0 .416)
Year dummies Yes Yes Yes
Country fixed effects Yes Yes Yes
Regional time trends Yes Yes Yes
Estimation method IV IV IV
Observations 1145 1145 1145
R-squared 0.935 0.957 0.955
Cragg-Donald F-stat 34.49 34.49 34.49
Table 7: The Effect of
Fertility on Education
Why is the Macro Labor Force Effect
so Large?
Social Spillovers.
Work is contagious.
Life course decisions different with the possibility of fertility control.
Abortion laws affect women who are at he margin of working (local average treatment effect).
Effect mainly in middle and high income countries?
Future Directions
Add laws on access to contraceptives as well as
abortion.
Use micro data (DHS) at different levels of
aggregation.
Interaction with demand side
Unemployment, underemployment