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Toward a better Population Consensus: Adding the Quality Dimension
Human Capital Development A new population policy paradigm for the 21st century ?
Wolfgang Lutz World Population Program, International Institute for Applied Systems Analysis (IIASA),
Vienna Institute of Demography, Austrian Academy of Sciences, WU, University of Economics Vienna
Oxford University
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Main Points• The pendulum of population concerns starts coming
back (focus on growth – reproductive rights – growth again). We should be able to do better, have learned a lesson and arrive at a better paradigm!
• Adding education to age and sex: Educational attainment as a key demographic dimension.
• Interactions between education, health and fertility: They greatly depend on each other.
• Educating girls has stronger effect on fertility than only trying to meet the unmet need for Family Planning: They greatly reinforce each other.
• A paradigm also for ageing and shrinking societies.
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People as an Asset – People as a Liability
• The focus on poverty reduction and economic growth must start with a focus on the people who produce it (with their own hands or through designing, building and operating the machines or institutions that make it possible).
• But people do not come as an amorphous mass. Not every member of a given population makes the same contribution to society and the economy.
• People differ by age, sex, educational attainment, health status, labor force participation and other observable and relevant dimensions.
• For reasons of data availability we first focus only on the educational attainment dimension of human capital by age and sex.
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Mortality under age 5 by mothers’ education (Source: DHS)
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6Source: IIASA
low edu high edu
poor 50.3 30.4
rich 35.6 18.0
0.0
10.0
20.0
30.0
40.0
50.0
60.0IM
R
India
7Source: IIASA
low edu high edu
poor 29.3 19.2
rich 26.8 11.3
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
IMR
Indonesia
8Source: IIASA
low edu high edu
poor 66.7 51.2
rich 64.5 46.2
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
Title
Malawi
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Education matters more than income
• Vicious circle argument: Poor health and high fertility inhibit the development that would then bring down fertility and improve health.
• Good news: This argument seems to be wrong!• The vicious circle can be broken by the combination
of education and RH (RH alone will not do)• In most of the successful countries (female) education
efforts came before economic growth.• The direct causal effect of education on economic
productivity, fertility decline and health (infant mortality, reproductive health, disability, infectious diseases, adaptive capacity) makes it a prime candidate for breaking the vicious circle of poverty, poor health and rapid population growth.
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2800 2100 1400 700 0 700 1400 2100 2800
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Republic of Korea - Population by Age, Sex and Educational Attainment in 2000 - Global Education Trend - Scenario
No Education
Primary
Secondary
Tertiary
World Population ProogramIIASA 2009
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2800 2100 1400 700 0 700 1400 2100 2800
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Republic of Korea - Population by Age, Sex and Educational Attainment in 1995
No Education
Primary
Secondary
Tertiary
World Population ProogramIIASA 2009
12
2800 2100 1400 700 0 700 1400 2100 2800
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Republic of Korea - Population by Age, Sex and Educational Attainment in 1990
No Education
Primary
Secondary
Tertiary
World Population ProogramIIASA 2009
13
2800 2100 1400 700 0 700 1400 2100 2800
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Republic of Korea - Population by Age, Sex and Educational Attainment in 1985
No Education
Primary
Secondary
Tertiary
World Population ProogramIIASA 2009
14
2800 2100 1400 700 0 700 1400 2100 2800
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Republic of Korea - Population by Age, Sex and Educational Attainment in 1980
No Education
Primary
Secondary
Tertiary
World Population ProogramIIASA 2009
15
2800 2100 1400 700 0 700 1400 2100 2800
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Republic of Korea - Population by Age, Sex and Educational Attainment in 1975
No Education
Primary
Secondary
Tertiary
World Population ProogramIIASA 2009
16
2800 2100 1400 700 0 700 1400 2100 2800
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Republic of Korea - Population by Age, Sex and Educational Attainment in 1970
No Education
Primary
Secondary
Tertiary
World Population ProogramIIASA 2009
17
2800 2100 1400 700 0 700 1400 2100 2800
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Republic of Korea - Population by Age, Sex and Educational Attainment in 2010 - Global Education Trend - Scenario
No Education
Primary
Secondary
Tertiary
World Population ProogramIIASA 2009
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Kenya 2000
6000 4000 2000 0 2000 4000 6000
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Kenya - Population by Age, Sex and Educational Attainment in 2000 - Global Education Trend -Scenario
No Education
Primary
Secondary
Tertiary
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Kenya 1970
6000 4000 2000 0 2000 4000 6000
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Kenya - Population by Age, Sex and Educational Attainment in 1970
No Education
Primary
Secondary
Tertiary
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Kenya 2050 – Global Education Trend
6000 4000 2000 0 2000 4000 6000
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Kenya - Population by Age, Sex and Educational Attainment in 2050 - Global Education Trend -Scenario
No Education
Primary
Secondary
Tertiary
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Kenya 2050 – Constant Enrollment Rates
7000 5000 3000 1000 1000 3000 5000 7000
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Kenya - Population by Age, Sex and Educational Attainment in 2050 - Constant Enrollment Rate -Scenario
No Education
Primary
Secondary
Tertiary
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Kenya 2050 – Constant Absolute Enrollment Numbers
7000 5000 3000 1000 1000 3000 5000 7000
15-1920-2425-2930-3435-3940-4445-4950-5455-5960-6465-6970-7475-7980-8485-8990-9495-99100+
Males Population in Thousands Females
Kenya - Population by Age, Sex and Educational Attainment in 2050 - Constant Enrollment Number - Scenario
No Education
Primary
Secondary
Tertiary
National Success Stories
• The story of Finland in the 19th and 20th century • The Story of Germany 1945-1970 • The Story of Mauritius 1960-1990
• The Story of South Korea 1970-2000
• The Story of Iran 1980-
Alfred Sauvy, 1958 book“ Fertility and Survival: Population
Problems from Malthus to Mao Tse-tung”
Writes about the “miracle” of Germany’s economic rise after total destruction in 1945 and the fact that it had to absorb five million refugees:
“Why this success, contrary to the forecasts of all doctrines …? Because these men without capital came with their knowledge, their qualifications. They worked and they recreated the capital that was lacking, because they included a sufficient number of engineers, mechanics, chemists, doctors, sociologists, etc. If five million manual workers had entered Western Germany instead there
would be five million unemployed today.”
Systems ModelsMulti-sectoral computer models with systems of non-linear equations and feed-backs trying to capture real world interactions as comprehensively as possible are the best way for testing which factors are primary drivers and
which are intermediate ones.
• World 3: The 1972 “Limits to growth” study did not explicitly consider education stocks.
• PDE (Population-Development-Environment) in depth case studies by IIASA: Mauritius, Cape Verde, Yucatan, Namibia, Botswana, Mozambique. All explicitly include human capital (by age and sex and 3-5 education categories) as part of comprehensive multi-sectoral systems models. Extensive sensitivity studies showed in all cases that investing in education is key to success.
• PEDA (Population-Environment-Development-Agriculture) Models by UN-ECA included literacy by age and sex in the model. Also turns out to be key to sustainable food security in seven African countries.
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Lessons:• Education matters greatly for fertility and mortality and therefore for
population growth. More education leads to later age at first birth, better access to family planning and lower desired fertility and hence reduces population growth (in high fertility countries).
• High fertility is an obstacle to increasing school enrolment. A rapidly increasing school age population makes it more difficult to increase or even maintain school enrolment rates (see absolute enrolment numbers scenario) – lower average schooling in turn leads to higher fertility (see Nigeria).
Policy Implications
• Education as a fertility policy: More effective than only addressing “unmet need” because it also lowers desired family size and is strictly voluntary and considered desirable by almost everybody.
• Lower fertility as an education policy: Efforts to increase school enrolment rates are greatly helped by reducing the growth in the school age population.
The combination of education and reproductive health (schola et sanitate) is key to breaking the vicious circle of poverty, lack of education and rapid population growth.
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Female education and the “unmet need” concept
From a human rights / empowerment perspective:
• Education empowers women in all aspects of their lives (family, society, economy, access to health services including RH).
• “Unmet need” for FP has only narrow focusFor fertility reduction:
• Potential reduction through education much greater than through meeting unmet need. Data for Ethiopia (DHS 2005): No education: 6.0, secondary: 2.0: Difference 4.0 Total pop actual fertility: 5.4, ideal 4.5: Difference 0.9 For poorest quartile of women ideal is 6.0: practically no difference
• Obstacles to meeting the “need” mostly not related to supply: perceived lack of exposure, opposition (of husband) to FP, lack of knowledge about methods and side effects.
• Female education can greatly help to remove these obstacles.
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Summary
More education (of women) is the key to:• Higher standing of women in family and society• Better reproductive health• Better nutrition and adult health, lower disability• Escaping from the poverty trap• Reducing high population growth• Compensating for aging and population decline• Enhancing democracy and better governance• Enhancing the adaptive capacity to unavoidable
climate change
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Could Human Capital Development (HCD) become a new 21st century population policy paradigm?
• It points to a clear priority in international development which is completely in line with the ICPD mandate. (The quality dimension of population: health, education, gender equity and well-being)
• It could introduce a sense of priority among the rather incoherent MDGs when it is clear that many will fail.
• It is currently not covered well by any UN agency. UNFPA does not directly address education and UNESCO focuses only on the process of education and not the human resource base (combining health, educational attainment, actual skills and others) of the population.
• It can make an important contribution to the climate change debate by pointing at the importance of differential vulnerability and the adaptive capacity of populations.
• People count !!!