Family Planning, Human Development

and Growth in Uganda

Jouko Kinnunen, VATTHans Lofgren, World BankDino Merotto, World Bank

Presentation for the Twelfth Annual Conferenceon Global Economic Analysis, Santiago, Chile

June 10-12, 2009

THE WORLD BANK

GOVERNMENT INSTITUTE FOR ECONOMIC RESEARCH (VATT), Finland

&

2

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

3

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?

4

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

5

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)

6

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

7

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

8

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

9

The dynamics of the demographic extension

Population(sex,age) at time t (beginning

of the year)

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+1

10

Constant elasticity function (bottom level)

stockcapitaltureinfrastruc

force;laborofeducatedofshare7a;and2indicatorsMDG

n;consumptiohhdcapitaperlevel;servicecapitaper

indicator

cdemographi

forvariable

teintermedia

;;

;;;

inf

CE

QFINSQFINSMDGVAL

QHPCpoptotQQCEZDEMG

fcapgovflabmdgdmg

11

Mortality rate (top level)

valuesmortalitytedisaggregaand

valueMDGaggregatebtwfactoradjustment

indicatortdevelopmengeneralermediate

LOG

mortalitymaternal

thancausesother

forratemortality

ADJMDGZDEMGLOGMORTRATE mrtga

4

;int

4;,

12

Fertility rate (top level)

fertility

oneffectservice

planningfamily

valuesmortalitytedisaggregaand

valueMDGaggregatebtwfactoradjustment

indicatortdevelopmengeneralermediate

LOG

childofgender

andgroupage

perolds

forratefertility

FAMSERVZDEMGLOGFERTRATE frtga

1

*4

;int4915

1*,

13

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

14

Real growth of GDP components, percent under BASE scenario 2009-2030

0

1

2

3

4

5

6

7

8

9

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

GDP growth

Government consumption

Private consumption

Exports

Imports

Private investment

Government investment

15

MDG indicators for BASE

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

150

2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029

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)

16

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 simulation-specific financing adjustments:– fp-ftr foreign transfers– fp-tax domestic taxation– fp-db domestic borrowing– fp-fb foreign borrowing

17

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

18

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 fp-db fp-fb

Absorption 15532.6 6.22 6.08 6.19 6.18 6.08Consumption - private 10337.2 6.27 6.19 6.33 6.31 6.19Consumption - government 2275.5 6.04 5.69 5.65 5.65 5.69Fixed investment - private 2205.0 6.32 6.15 6.32 6.27 6.15Fixed investment - government 715.0 5.57 5.34 5.35 5.35 5.34Stock change 0.0Exports 1781.0 6.56 6.94 6.72 6.64 6.94Imports 3517.6 6.22 6.07 6.23 6.21 6.07GDP at market prices 13796.1 6.26 6.20 6.26 6.23 6.20GDP at factor cost 12648.1 6.25 6.21 6.25 6.23 6.21Total factor employment (index) 5.09 5.02 5.06 5.04 5.02Total factor productivity (index) 1.155 1.189 1.194 1.188 1.189Real exchange rate (index) -0.19 -0.02 -0.17 -0.17 -0.02Note: Base-year column shows data in LCU.

19

Population for BASE and FP-ftr

0

5,000

10,000

15,000

20,000

25,000

30,000

2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029

6 to 12 base

6 to 12 fp-ftr

13 to 17 base

13 to 17 fp-ftr

18 to 64 base

18 to 64 fp-ftr

Primary school age

Secondary school age

People in working age (over secondary school age)

20

Dependency Ratio

60

70

80

90

100

110

120

2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029

base

fp-ftr

fp-tax

fp-db

fp-fb

UN Medium variant 2008

21

Total Fertility Rate (TFR)

4

4.5

5

5.5

6

6.5

7

7.5

2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029

base

fp-ftr

fp-tax

fp-db

fp-fb

UN Medium variant

22-1300 -1100 -900 -700 -500 -300 -100 100 300 500 700 900 1100 1300

0

4

8

12

16

20

24

28

32

36

40

44

48

52

56

60

64

68

72

76

80

84

88

92

2003

-1300 -1100 -900 -700 -500 -300 -100 100 300 500 700 900 1100 1300

0

4

8

12

16

20

24

28

32

36

40

44

48

52

56

60

64

68

72

76

80

84

88

92

2005

-1300 -1100 -900 -700 -500 -300 -100 100 300 500 700 900 1100 1300

0

4

8

12

16

20

24

28

32

36

40

44

48

52

56

60

64

68

72

76

80

84

88

92

2010

-1300 -1100 -900 -700 -500 -300 -100 100 300 500 700 900 1100 1300

0

4

8

12

16

20

24

28

32

36

40

44

48

52

56

60

64

68

72

76

80

84

88

92

2015

-1300 -1100 -900 -700 -500 -300 -100 100 300 500 700 900 1100 1300

0

4

8

12

16

20

24

28

32

36

40

44

48

52

56

60

64

68

72

76

80

84

88

92

2020

-1300 -1100 -900 -700 -500 -300 -100 100 300 500 700 900 1100 1300

0

4

8

12

16

20

24

28

32

36

40

44

48

52

56

60

64

68

72

76

80

84

88

92

2025

-1300 -1100 -900 -700 -500 -300 -100 100 300 500 700 900 1100 1300

0

4

8

12

16

20

24

28

32

36

40

44

48

52

56

60

64

68

72

76

80

84

88

92

2030

-1300 -1100 -900 -700 -500 -300 -100 100 300 500 700 900 1100 1300

0

4

8

12

16

20

24

28

32

36

40

44

48

52

56

60

64

68

72

76

80

84

88

92

2030

Base scenario

Women Men

FP-tax scenario

23

MDG indicators for fp-tax: change from BASE

-6

-5

-4

-3

-2

-1

0

1

2

3

4

2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029

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)

24

Change in final-year EV per capita, %

0%

5%

10%

15%

20%

25%

30%

35%

40%

Ruralhouseholds

Urbanhouseholds

Ruralhouseholds

income quartiles1-2

Ruralhouseholds

income quartiles3-4

Urbanhouseholds

income quartiles1-2

Urbanhouseholds

income quartiles3-4

All households

FP - foreign transfers

FP - foreing borrowing

FP - domestic borrowing

FP - taxation

25

Annual growth rate of per-capita consumption

0

1

2

3

4

5

6

2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029

base totalfp-ftr totalfp-tax totalfp-db totalfp-fb total

26

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

27-1000

-800

-600

-400

-200

0

200

400

2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

fp-ftr

fp-fb

fp-tax

fp-db

Change in Government Expenditure

when Annual Cost of Protection per Couple is:

$15

-1000

-800

-600

-400

-200

0

200

400

2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

fp-ftr

fp-fb

fp-tax

fp-db

$31

-1000

-800

-600

-400

-200

0

200

400

2004 2006 2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

fp-ftr

fp-fb

fp-tax

fp-db

$76

28

Government’s share of GDP with FP unit cost of $76

10

12

14

16

18

20

22

24

2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029

base

fp-ftr

fp-tax

fp-db

fp-fb

29

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

30

Thank Your for Your Attention!

¡Muchas gracias por su atención!

jouko.kinnunen@vatt.fihlofgren@worldbank.orgdmerotto@worldbank.org