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Family Planning, Human Development
and Growth in Uganda
Jouko Kinnunen, VATT
Hans Lofgren, World Bank
Dino Merotto, World Bank
Presentation for the Twelfth Annual Conference
on Global Economic Analysis, Santiago, Chile
June 10-12, 2009
THE WORLD BANK
GOVERNMENT INSTITUTE FOR ECONOMIC RESEARCH (VATT), Finland
Background and Motivation
• Extremely high fertility and youthful population in Uganda;
why a problem?
• Development and public expenditure planning needs of GoU
• Need to endogenize population in MAMS
• Role of fertility within development
• Recent changes in the international politics of family
planning
2
Research Questions
• What is the impact of increased family planning (FP)
services on macro and MDG indicators in Uganda?
• Does the way of financing the increased (?) public
expenditure on FP matter?
• How sensitive are the results to FP cost estimates?
3
Main results
• Major effects of FP:
–
–
–
–
improved EV welfare for (living) Ugandans;
better outcomes for MDG indicators; and
creation of additional fiscal space in the medium- to long-run
Macro-level effects are otherwise minor
• ”Domesticity” of the adjusting government income variable
plays a role
• Expected per-capita cost of FP very moderate
• Qualitative results are not very sensitive to the cost of FP
4
Current situation
•
•
•
•
•
•
•
•
Total fertility rate (TFR) close to 7 children
Dependency ratio
= [population not 14-65]/[population 14-65] = 110 percent
Unmet demand for contraceptives for 41% of households
Current contraception prevalence = 24%
2 out of 7 children unwanted
High pressure on land use  potential for conflicts
Pressures on public expenditure on health and education
Dependency of GoU on foreign aid (its value similar to direct tax receipts)
5
Economics and Demography
• Links between growth in per-capita GDP and
population
• Age structure affects labor supply, private and
public consumption, investment, and productivity
• Human development and demography closely
linked: MDGs, social services
• Increasing number of CGE models with (at least
partly) endogenous demography
6
MAMS
•
•
•
•
•
•
•
•
MAMS = Maquette for MDG Simulations
Developed at World Bank; applied to 35 countries (in many cases in
collaboration with UNDESA and UNDP)
Used to analyze medium- to long-run impact of strategies, including
effects on monetary poverty and human development (MDG indicators).
Recursive-dynamic single-country model
Government services modeled in relatively detailed fashion: public sector
as producer, consumer, and investor
Productivity impact of public infrastructure
MDGs covered in Uganda application: 1 (headcount poverty), 2 (net
primary completion), 4 (under-five mortality), 5 (maternal mortality), 7
(access to improved water)
For more information on MAMS: www.worldbank.org/mams
7
The demographic extension
• Population disaggregated by gender and (one-year)
age cohorts
• Fertility and mortality modeled with two-level
constant elasticity and logistic functions (mimics
modeling of MDGs in MAMS)
• Constant net migration rates
8
The dynamics of the
demographic extension
Fertility (by age
of mother, sex
of child) at time t
Mortality
(sex,age)
at time t
Migration
(sex, age)
at time t
Population(sex,age)
at time t (beginning
of the year)
Population(sex,age)
at time t+1
9
Constant elasticity function (bottom level)
 QQ; poptot; QHPC ;


ZDEMG dmg  CE

MDGVAL
;
QFINS
;
QFINS
mdg
flab
fcapgov
inf


 intermedia te 
per capita service level; per capita hhd consumptio n;

 variable for 

  CE MDG indicators 2 and 7a; share of educated of labor force; 


demographi c 
infrastruc ture capital stock



indicator

10
Mortality rate (top level)
MORTRATE a , g  LOG ZDEMG mrt ; MDG 4 ADJ 
mortality rate for 
 int ermediate general development indicator ; 
other causes than   LOG  adjustment factor btw aggregate MDG 4 value 




 and disaggrega te mortality values

maternal mortality 


11
Fertility rate (top level)
FERTRATE a , g  LOG ZDEMG frt * 1  FAMSERV 
 fertility rate for 
 int ermediate general development indicator ;  1  family planning 
15  49 olds per 

 


  LOG  adjustment factor btw aggregate MDG 4 value  *  service effect on

age group and 
 and disaggrega te mortality values
  fertility







 gender of child 
12
BASE scenario 2003-2030
• Annual GDP growth 6.2% (recent average growth rate).
• Growth in government consumption declines due to
completed reforms in primary education
• Improvements in MDGs
• In terms of official MDG targets, only MDG1 (poverty) is
attained by 2015
• TFR falls from 7.3 in 2003 to 5.6 in 2030
• Compared to UN medium variant projection:
– population growth rate (3.1% 2003-2030) is very close;
– dependency ratio, mortality and fertility rates are all higher
13
Real growth of GDP components,
percent under BASE scenario 2009-2030
9
8
7
6
5
4
GDP growth
3
Government consumption
Private consumption
Exports
2
Imports
Private investment
Government investment
1
0
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
14
MDG indicators for BASE
150
Poverty rate (%)
Net primary completion rate (%)
Under-five mortality (per 1,000 births)
Maternal mortality (per 10,000 live births)
Access to clean water (% of population)
140
130
120
110
100
90
80
70
60
50
40
30
20
10
0
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
2027
2029
15
Policy simulations: increased family planning
• Gradual increase in spending on FP starting from 2007,
ceteris paribus reducing the fertility rate by 20% in each year
(of what it otherwise would be at that year) with simulationspecific financing adjustments:
–
–
–
–
fp-ftr
fp-tax
fp-db
fp-fb
foreign transfers
domestic taxation
domestic borrowing
foreign borrowing
16
Results for FP scenarios
• Small macro effects: sligtly slower GDP growth, higher
export share of GDP, more rapid growth in higher
consumption per capita
• Impact of FP on public expenditure: higher 2007-2016, lower
2017+
• Very small differences in demographic outcomes between FP
scenarios
• ”Domesticity” of the clearing variable for government
expenditure matters: most favorable macro effects when
changes (increases) in fiscal space are used to adjust (cut)
taxes.
• Population in 2030 declines from 61.0 to 53.7 million
17
Average growth rates of macro indicators
Table. Real macro indicators by simulation (% annual growth from 2006 to final 2030)
2006
base
fp-ftr
fp-tax
Absorption
15532.6
6.22
6.08
6.19
Consumption - private
10337.2
6.27
6.19
6.33
Consumption - government
2275.5
6.04
5.69
5.65
Fixed investment - private
2205.0
6.32
6.15
6.32
Fixed investment - government
715.0
5.57
5.34
5.35
Stock change
0.0
Exports
1781.0
6.56
6.94
6.72
Imports
3517.6
6.22
6.07
6.23
GDP at market prices
13796.1
6.26
6.20
6.26
GDP at factor cost
12648.1
6.25
6.21
6.25
Total factor employment (index)
5.09
5.02
5.06
Total factor productivity (index)
1.155
1.189
1.194
Real exchange rate (index)
-0.19
-0.02
-0.17
Note: Base-year column shows data in LCU.
fp-db
6.18
6.31
5.65
6.27
5.35
fp-fb
6.08
6.19
5.69
6.15
5.34
6.64
6.21
6.23
6.23
5.04
1.188
-0.17
6.94
6.07
6.20
6.21
5.02
1.189
-0.02
18
Population for BASE and FP-ftr
30,000
People in working age (over secondary
school age)
6 to 12 base
6 to 12 fp-ftr
25,000
13 to 17 base
13 to 17 fp-ftr
20,000
18 to 64 base
18 to 64 fp-ftr
15,000
Primary school
age
10,000
5,000
Secondary school age
0
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
2027
2029
19
Dependency Ratio
120
110
100
90
base
fp-ftr
80
fp-tax
fp-db
fp-fb
UN Medium variant 2008
70
60
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
2027
2029
20
Total Fertility Rate (TFR)
7.5
base
fp-ftr
fp-tax
fp-db
fp-fb
UN Medium variant
7
6.5
6
5.5
5
4.5
4
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
2027
2029
21
92
92
88
88
84
84
Base scenario
80
80
Women
76
76
2025
2030
2030
2005
2003
2010
2020
2015
Men
72
72
68
68
64
64
FP-tax scenario
60
60
56
56
52
52
48
48
44
44
40
40
36
36
32
32
28
28
24
24
20
20
16
16
12
12
88
44
00
-1300
-1300
-1100
-1100
-900
-900
-700
-700
-500
-500
-300
-300
-100
-100
100
100
300
300
500
500
700
700
900
900
1100
1100
1300
1300
22
MDG indicators for fp-tax: change from BASE
4
Poverty rate (%)
Net primary completion rate (%)
Under-five mortality (per 1,000 births)
Maternal mortality (per 10,000 live births)
Access to clean water (% of population)
3
2
1
0
-1
-2
-3
-4
-5
-6
2003
2005
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
2027
2029
23
Change in final-year EV per capita, %
40%
35%
30%
25%
FP - foreign transfers
FP - foreing borrowing
20%
FP - domestic borrowing
FP - taxation
15%
10%
5%
0%
Rural
households
Urban
households
Rural
Rural
Urban
Urban
households
households
households
households
income quartiles income quartiles income quartiles income quartiles
1-2
3-4
1-2
3-4
All households
24
Annual growth rate of per-capita consumption
6
5
4
base total
fp-ftr total
fp-tax total
fp-db total
fp-fb total
3
2
1
0
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
2027
2029
25
Sensitivity to cost of FP
• Even five-fold annual per-couple cost of protection
(~$15 to ~76$) does not change the qualitative
result of the study – FP economically beneficial in
the long run
• Government expenditures lower than under BASE
first in year 2023 instead of 2017
• An evaluation of whether FP is desirable or not does
not only depend on economic outcomes
26
Change in Government Expenditure
when Annual Cost of Protection per Couple is:
$76
$15
$31
400
200
0
-200
-400
fp-ftr
fp-fb
fp-tax
fp-db
-600
-800
-1000
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
2026
2028
2030
27
Government’s share of GDP
with FP unit cost of $76
24
22
20
18
16
base
fp-ftr
fp-tax
fp-db
fp-fb
14
12
10
2007
2009
2011
2013
2015
2017
2019
2021
2023
2025
2027
2029
28
Final Conclusions & Remarks
• Major effects of FP:
– improved EV welfare for (living) Ugandans;
– better outcomes for MDG indicators; and
– creation of additional fiscal space in the medium- to long-run
• Expected per-capita cost of FP very moderate
• Integration of economywide and demographic models is
often desirable
• Topics for possible future studies using this framework (with
marginal adjustments) include various issues in health
economics, including AIDS
29
Thank Your for Your Attention!
¡Muchas gracias por su atención!
[email protected]
[email protected]
[email protected]
30