Family Planning Programs for the 21st Century:

Rationale and Design Reconsidered

Monica Das GuptaJohn Bongaarts

John ClelandShareen Joshi

Outline of talk1. Why discuss family planning, not female education?

2. Rationale for family planning programs. Review literature on:a) Does rapid population growth affect developing countries prospects of

economic growth?b) Does rapid population growth affect prospects of sustainable management of

resources?c) Are family planning programs effective?

3. The donor retreat & its implications:a) The donor retreat b) Implications for Sub-Saharan Africac) Implications for women’s health

4. Designing family planning programs:a) Strengthening the supply of servicesb) Building demand for services

5. Conclusions

SECTION 1 WHY DISCUSS FAMILY PLANNING, NOT FEMALE EDUCATION?

Why discuss family planning, not female education?

• Female education strongly associated with lower fertility and better outcomes of many kinds– But well-established in the policy arena, – Well-recognized private & social returns

• By contrast, family planning relatively neglected by donors– Less awareness of its intrinsic benefits & positive

externalitiesWorld Bank (2009) notes its support for population nearly disappeared

Percent of donor expenditures on population assistance by activity, 1995-2007

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 20070

10

20

30

40

50

60

70

80

Family planning servicesBasic reproductive health servicesSTD/HIV/AIDS activities

Source: UNFPA 2003:Table 5, UNFPA 2009:Table5

SECTION 2 THE RATIONALE FOR FAMILY PLANNING PROGRAMS: A LITERATURE

REVIEW

1a: Does rapid population growth affect developing countries’ prospects of economic growth?

• Coale-Hoover ― rapid population growth hinders economic growth (in poor, agrarian 1950s India):– Resources diverted from investment in production to meet needs of:

• Growing population • Rising youth dependency ratios

• Studies challenging these models ― and rationale for family planning programs(cross-country regressions 1960s to 1980s)

• Recent studies indicate:– Low dependency ratios: can increase productivity, invest in future growth– Household-level: lower fertility ass with better health, schooling, laborforce participation– Population increases associated with lower growth in per capita income– Rapid population growth can constrain economic growth, especially where policy settings

hinder productivity rise

Throughout, broad consensus that policy & institutional settings are key driver of economic growth, while population growth rate plays a secondary role.

1b: Does rapid population growth affect prospects of sustainable management of resources?

• Innovation obviates population pressure on resources:– Population growth induces innovation– Innovation makes resource base effectively infinite (Simon)

• Constraints to innovation:– Where resources are free or under-priced – Difficulties of managing use of global common property resources

Intensive agriculture has contributed to the proliferation of dead zones

Source: World Bank (2010a) World Development Report 2010: Map 3.4 (derived from Diaz and Rosenberg 2008).

Required growth in agricultural productivity

1965 1970 1975 1980 1985 1990 1995 2000 2005 2015 2025 2035 2045 205550

100

150

200

250

Climate change

Population growth

Change in percapita consumption

}}}

•••• The scenario with climate change― The "business as usual" scenario without climate change --- The "business as usual" scenario without climate change AND NO POPULATION GROWTH AFTER 2005

Source: World Bank (2010a) World Development Report 2010: Figure 3.5 (derived from Lotze-Campen et al 2009). We thank Dr Lotze-Campen for disaggregating the “business as usual” scenario into two estimates: (1) with population held constant at the 2005 level, and (2) the WDR 2010’s “business as usual” scenario, which includes anticipated population increase to 9 billion by 2055.

1c: Are family planning programs effective?

• (Pritchett): fp programs little effect on fertility– Controlling for desired family size– Mass media found effective at reducing desired family size – Major component of fp progs

• Randomized evaluation data virtually non-existent– But many careful studies indicate fp programs reduce fertility

SECTION 3 IMPLICATIONS FOR SUB-SAHARAN AFRICA

IMPLICATIONS FOR WOMEN’S HEALTH

2b: Implications for Sub-Saharan Africa

Trends in fertility by region, 1960-2010

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 20100

1

2

3

4

5

6

7

8

Birh

s/w

oman

Sub-Saharan Africa

Latin America

Asia

Source: UN 2009

% increase in population aged 0-14, 1970-2005

Asia LAC SSA Niger0

20

40

60

80

100

120

140

160

180

200

Source: UN 2009

Changes in per capita food production, 1961-2005

Source: The Royal Society 2009: Figure 1.4

Growth in GDP per capita, 1960-2004

785

208124

0

100

200

300

400

500

600

700

800

900

1960

1964

1968

1972

1976

1980

1984

1988

1992

1996

2000

GD

P pe

r cap

ita in

dex,

196

0=10

0East Asia & Pacific

Low income

Sub-Saharan Africa

Source: World Bank 2007b: Figure 2.5, derived from the World Bank World Development Indicators database

Note: GDP per capita index 1960=100

Fertility decline helps improve women’s health:Ratio of Male to Female Mortality, India, 1970-1990

0 1 5 10 15 20 25 30 35 40 45 50 55 60 65 70

0.600000000000001

0.700000000000001

0.800000000000001

0.900000000000001

1

1.1

1.2

1.3

1.4

1.5

1.6

Age

Male / female ratio in mortality

Source: Government of India, Sample Registration Bulletin 16(1), June 1982, and SRS Based Abridged Life Tables 1988-92, New Delhi: Registrar-General of In -dia.

Reproductive age group (15-44)

male/female mortality ratio 1970-75

male/female mortality ratio1988-92

SECTION 4 DESIGNING FAMILY PLANNING PROGRAMS

Section 4:Designing family planning programs

• Strengthening the supply of services• Strengthening the demand for services

Population projections for sub-Saharan Africa Maintaining one less birth per woman reduces projected population size in 2050 by half a billion

1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 20500

1000000

2000000

High variant

Low variant

Difference is onebirth per woman throughout theprojection period}

Source: UN 2009

Section 5: Conclusions