DEMOGRAPHIC DIVIDEND IN AFRICA: DOES IT APPLY TO

MALAWI?

David Canning

Harvard T.H. Chan School of Public Health

Friday 5th AugustIFPRI, Lilongwe, Malawi

1

Population and Development

• Negative effects of population growth-population bomb

• Positive effects – scale and technology

• National Academy of Sciences 1986 – no effect empirically

• Neutral position on population

2

Components of Population Growth

• Kelly and Schmidt 1995

• While growth of population numbers does not matter, components do matter.

• Population growth = birth rate- death rate.

• High birth rates seem to have a negative effect on growth.

• High death rates seem to have a negative effect on growth.

4

Figure 1b

Birth Rates and Economic Growth

-8

-6

-4

-2

0

2

4

6

8

10

0 1 2 3 4 5 6

Crude Birth Rate 1980 (percent)

GD

P p

er

Cap

ita G

row

th R

ate

1980-2

000

(perc

en

t)

Based on data for 127 countries from the World Bank's World Development Indicators 2011.

5

-8

-6

-4

-2

0

2

4

6

8

10

0 0.5 1 1.5 2 2.5 3

GD

P p

er

Ca

pit

a G

row

th R

ate

1980

-2000 (p

erc

en

t)

Crude Death Rate 1980 (percent)

Death Rates and Economic Growth

Based on data for 127 countries from he World Bank's World Development Indicators 2011.

Asian Economic Miracle

• What caused the Asian miracle? ADB 1997

• Growth, labor, capital Bloom, Williamson

• Growth regressions

– Infrastructure

– Health (Life expectancy)

– Age structure

6

New View on Importance of Population

• Not just population numbers

• Age structure effects - very large effects

• Explains about a third of the Asian Miracle

7

Health and Wealth of Nations

• Effects of child health on physical and cognitive development

• Effects of life span on life cycle behavior

• Effect of child mortality reductions on fertility

• WHO Commission on Macroeconomics and Health 2001

8

The Demographic Dividend

• Pure age structure effects

• Behavioral effects

– Female labor supply

– Investments in child health and education

– Longevity and saving

• Dividend not automatic

– extra resources must be productively employed

– Dividend must be earned by investments – increased policy effects

9

Working Age Share is Linked to Economic Takeoff

1

1.5

2

2.5

3

1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100

Rat

io o

f W

ork

ing

Age

to

D

epen

den

ts

YearSource: World Bank Medium Fertility Variant

Ratio of Working Age to Dependents

Sub Saharan Africa

East Asia

South Asia

10

11

12

Structure• Introduction

• Demographic Dynamics in Africa

• Determinants of the Demographic Transition

• Human Development Payoffs

• Jobs Payoffs

• Economic Growth in Africa

• Policies to Speed up the Demographic Transition

• Policies to Reap the Demographic Dividend13

Total Fertility Rate in Select World Regions, 1960–2010

14

0

1

2

3

4

5

6

7

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Tota

l Fer

tilit

y R

ate

Sub-Saharan Africa East Asia & Pacific Europe & Central Asia Latin America & Caribbean

Middle East & North Africa North America South Asia World

Source: Health, Nutrition and Population Statistics. The World DataBank 2013.

Great Heterogeneity in Fertility Transition

15

1 2 3 4 5 6 7Mauritius Réunion Gabon Togo Senegal Malawi Niger

South Africa Lesotho Ghana Comoros DRC

Cape Verde Namibia Ethiopia Gambia Zambia

Botswana Zimbabwe Congo Mozambique Chad

Swaziland Côte d'Ivoire Sierra Leone Uganda

Sao Tome and Principe Burundi Guinea-Bissau Somalia

Sudan Equatorial Guinea Mali

Cameroon Liberia

Eritrea Rwanda

Mauritania Guinea

Kenya Benin

Madagascar Tanzania

CAR Nigeria

Angola

Burkina Faso

Total Fertility Rates

Fertility ReductionThe Demographic Dividend

• Pure age structure effects

• Behavioral effects

– Female labor supply

– Investments in child health and education

– Longevity and saving

• Dividend not automatic

– extra resources must be productively employed

– Dividend must be earned by investments

16

Proximate Determinates of Fertility

17

Source: Madhavan et al 2013. Data Source: Various DHSs.

Proximate Determinants of Fertility Change

18

From Madhavan et al 2013. Data Source: Various DHS.

A Family Planning Intervention Reduced Fertility in Navrongo, Ghana

Treatment Area: Comparison Area

19n

Malawi Family Planning Project• Improving Access to Post Partum Family

Planning in Lilongwe

• RCT – 2000 women

• Components – FP counselling, transport to Good Health Kauma Tunza clinic, free FP services, side effect treatment

• Outcomes: Contraceptive prevalence, birth spacing, child health and education, female health and employment

• Demographic dividend in the household20

Policies to Promote Fertility Decline Decrease Child Mortality

21*World Development Indicator Data. 2010

Mortality Transition

22

Below 50 50-99 100-149 150-199 200-249

Réunion Namibia Comoros Guinea Chad

Mauritius Botswana Tanzania Cameroon

Cape Verde Madagascar Kenya Zambia

Eritrea Gambia Nigeria

Ghana Ethiopia Niger

Sao Tome and Principe Swaziland Burundi

Gabon Congo Burkina Faso

South Africa Lesotho Equatorial Guinea

Zimbabwe Togo Angola

Senegal Mauritania CAR

Sudan Côte d'Ivoire Sierra Leone

Liberia Somalia

Uganda DRC

Rwanda Mali

Benin Guinea-Bissau

Malawi

Mozambique

Under 5 Mortality per 1000 Births

Fertility Rates by Women’s Education

Data from various Demographic and Health Surveys.

Female Education Is a Major Diver of Fertility Rates

24

Education of Women by Birth Year: Ethiopia

25

01

23

45

Ave

rag

e Y

ea

rs o

f S

choo

ling

, F

em

ale

1960 1970 1980 1990Birth Cohort

No Coverage Partial Coverage Full Coverage

26

Male-Female Education Gap in Sub-Saharan Africa--

Secondary Enrollment

0

0.5

1

1.5

2

2.5

3

12-14 years 15-19 years 20-24 years 25-29 years(Reference)

30-34 years 35-39 years 40-44 years 45-49 years

Infant MortalityAdjusted RRR: Age of Mother at Birth

Short Birth Spacing Increases Infant Mortality

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

7-11months

12-17months

18-23months

24-29months

30-35months

36-47months

(ref)

48-59months

60-95months

>95months

Adjusted Relative Risk by Birth Interval

28

-3

-2

-1

0

1

2

3

4

5

6

1961-1965 1966-1970 1971-1975 1976-1980 1981-1985 1986-1990 1991-1995 1996-2000 2001-2005 2006-2010

Annual Growth RatesGDP & GDP per capita

GDP growth GDP per capita growth

Economic Growth in Sub-Saharan Africa

29

30

Economic ConsequencesThe Demographic Dividend

• Working age share 30 – 50 year boost

– Labor force per capita

• Investments in

• Child Health

• Education

• Female Labor Force Participation

• Savings

31

Demographic Dividend is not Automatic

• Depends on effective policies in other areas – Education– Labor market– Trade– Governance– Macroeconomic management

• Demography creates supply side increases in labor, human capital, and saving – but there is still a need for jobs and investment

Increasing Youth Cohorts In Sub Saharan Africa

0

5

10

15

20

25

30

35

40

19

50

19

55

19

60

19

65

19

70

19

75

19

80

19

85

19

90

19

95

20

00

20

05

20

10

20

15

20

20

20

25

20

30

20

35

20

40

20

45

20

50

Ye

arl

y C

oh

ort

15

-24

(M

illi

on

)

Eastern Asia South-Central Asia Sub-Saharan Africa

33

Impact of large youth cohorts

• Youth Unemployment

• Underemployment in unpaid and low productivity jobs

• Slows industrialization and structural transformation, youth are absorbed in low productivity sectors such as agriculture

• Requires high levels of investment to maintain capital labor ratio

34

35

Goals Polices

Speed the Demographic Transition

To empower women and allow fertility choices

Child mortality, female education, social norms, access to family planning

Realizing the Labor Force Dividend

To absorb Youth Bulge FDI, domestic saving, natural resource revenueseducation, infrastructure, Industrialization(Agriculture and natural resources not sufficient)

Realizing the Savings Dividend

Harness the 2nd dividend Improve policies and institutions for promotingdomestic savings and investment

A Macrosimulation Model of the Effect of Fertility Decline on Economic Growth in Africa

Mahesh Karra

David Canning

Joshua Wilde

Forthcoming in Population and Development Review

PRELIMINARY RESULTS FROM THIS PAGE ONWARDS

PLEASE DO NOT CITE36

Effective Labor

37

Population by Age

Labor SupplyEducation

Fertility

Height (Health)

Male Labor

Supply

Female Labor

Supply+

Effective Labor

Production

38

Effective Labor

Fertility

Physical CapitalLand

Modern Sector

Production

Savings

Previous

slide

Old Age

Dependency

Rate

Traditional Sector

Production +

Production

Raw Materials

MalawiTFR Under Different Scenarios

39

Malawi Fertility - DHS

40

MalawiTotal Population Under Different

Scenarios

41

MalawiWorking Age Share of the

Population

42

MalawiAverage Years of Schooling of the

Workforce

43

MalawiShare of Workers not in Agriculture

44

Key:

DRCShare of Workers not in Agriculture

45

Key:

MalawiPPP Income per Capita

46

DRCPPP Income per Capita

47