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 &

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:

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)

11 Mortality rate (top level)

12 Fertility rate (top level)

13 BASE scenario 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% ) is very close; – dependency ratio, mortality and fertility rates are all higher

14 Real growth of GDP components, percent under BASE scenario

15 MDG indicators for BASE

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-ftrforeign transfers – fp-taxdomestic taxation – fp-dbdomestic borrowing – fp-fbforeign 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 , lower 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

19 Population for BASE and FP-ftr

20 Dependency Ratio

21 Total Fertility Rate (TFR)

22 Base scenario Women Men FP-tax scenario

23 MDG indicators for fp-tax: change from BASE

24 Change in final-year EV per capita, %

25 Annual growth rate of per-capita consumption

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 Change in Government Expenditure when Annual Cost of Protection per Couple is: $15$31 $76

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

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

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