Modeling the Demographic Dividend: DemDiv Scott Moreland, Bernice Kuang, Kaja Jurczynska ( Palladium) Elizabeth Leahy Madsen (Population Reference Bureau) Demographic Dividend and African Development: 11th Global Meeting of the NTA Network, Saly, Senegal, 20-24 June 2016
The demographic dividend is: The accelerated economic growth That begins with a change in population age structure And is achieved through strategic investments and policies
How does a demographic transition cause a demographic dividend? The dependency effect: When the dependency rate falls, it permits an increase in income per capita The life-cycle-savings effect: A larger population at working age relative to the dependent (young) population can save more, which results in higher levels of investment The experience effect: An increase in productivity may result from a more mature and experienced population The labor force participation effect: Higher labor-force participation may result when there are fewer dependents, thus boosting the labor force
The demographic dividend is not automatic; it requires 4 key elements Favorable population age structure Large working-age population (15+ years old) Small dependent population (0 14 years old) Investments in education Completion of primary and secondary education, especially for girls Sound labor market and economic policies Good governance
Purpose of the DemDiv Model Build on the longstanding interest in the relationship between population growth and economic growth Quantify specific policies that may help a country achieve a demographic dividend Demonstrate that multisectoral, interacting policies are more effective than emphasizing any single sector Realizing a dividend requires economic and human-capital policies in addition to demographic ones Target audience: Influential policymakers outside the health sector Appropriate for any high-fertility country
DemDiv basics Core model relating family planning, population age structure, investment, employment, and income/productivity Statistically rigorous and evidence-based Makes projections for multiple scenarios Adaptable to each country s context Accessible to diverse audiences No special or proprietary software Data available from public sources
Model structure Two linked sub-models: Demographic and economic User designs up to three policy scenarios for the future, plus a base scenario Uses cross-national regression to estimate social and economic indicators and quantify impact of changes in them Standard projection period is 2010 to 2050 can be adjusted Uses Microsoft Excel, automatically linked to the DemProj model in Spectrum
Demographic sub-model CPR Sterility Total Fertility Rate Marriage Girls Education PPI High-Risk Births Population Under-5 Mortality Life Expectancy
The Global Competitiveness Index Also included in the model Schwab, K. 2013. The Global Competitiveness Report 2013 2014: Full Data Edition. Geneva: World Economic Forum.
Economic sub-model Pop15+/Pop GDP Per Capita (t-1) Pop 15+ Total Population GCI: Financial Efficiency Investment/ Capital Stock Employment GCI: Labor Flexibility GCI: ICT GCI: Public Institutions Total Factor Productivity Gross Domestic Product Average Years of Education GCI: Imports as % of GDP GDP Per Capita
Applying the model is a participatory process Work through our local offices and advisors Establish a technical working group, normally with strong multi-sector linkages (Health, Planning, Economy, Finance, Labor ) Often collaborate with other donors (DFID, UNFPA ) Maximize use of local data Use country-defined scenarios Include advocacy and dissemination by country teams
DemDiv main inputs and outputs Inputs Financial market efficiency Labor market flexibility Public institutions Imports as % of GDP Information & communications technology use Male and female education Family planning Girls education Outputs Population by age and sex Dependency ratio Infant, child and maternal mortality Fertility rate Life expectancy Labor force by age and sex Employment Investment GDP and GDP per capita GDP growth rate
DemDiv and DemProj
Model applications to date Kenya Uganda Ethiopia Burkina Faso Cote d Ivoire Nepal South Africa Tanzania Malawi Nigeria Zambia Senegal
DemDiv results: Kenya A globally competitive and prosperous nation with a high quality of life Kenya Vision 2030
Four policy scenarios Scenario Key Characteristics Base Case No change in any variable between 2010-2050 Economic Only Improvements in financial market efficiency, ICT use, imports, labor market flexibility, and public institutions Economic indicators improve to match current levels for Malaysia Economic + Education In addition to economic improvements, educational attainment improves School life expectancy for girls increases from 11 to 16 years Combined: Economic + Education + FP FP improvements layered on top of economic and education changes MCPR increases from 39 to 70% by 2050
The combined scenario of economic, education, and FP policies produces a youth bulge 2050 base scenario 2050 combined scenario With constant fertility, Kenya s age structure remains very young and is dominated by dependents Percentage of Total Population The Economic+Education+FP scenario produces a large potential labor force with fewer dependents to support
Combined economic, education, and FP policies yield a higher level of investment US$ 2,000 1,600 1,200 800 Investment per capita Economic + Education + FP Economic + Education Economic Only 400 0 2010 2015 2020 2025 2030 2035 2040 2045 2050 Base Case
Combined economic, education, and FP policies produce the smallest gap between employment and Pop 15+ 45 43 Difference between Pop15+ and employment (millions) 40 35 30 25 20 15 10 10 13 9 8 5 0 2010 2050 Base Case 2050 Econ Only 2050 Econ+Ed 2050 Econ+Ed+FP
With higher investment and employment, GDP per capita is larger in the combined scenario 12,000 $11,288 Current US$ 10,000 8,000 6,000 4,000 $6,693 Demographic Dividend $8,748 2,000 0 $907 $896 2010 2050 Base Case 2050 Econ Only 2050 Econ+Ed 2050 Econ+Ed+FP
DemDiv Kenya dissemination Launched in Nairobi in July 2014 by Dr. Rachel Nyamai, MP, Chair of the Parliamentary Committee on Health Launched in Nyeri and Kakamega Counties, July-August 2014 Credit: Health Policy Project/Kenya
DemDiv results Uganda
Three policy scenarios Scenario Key Characteristics Business As Usual Make modest investments in family planning, education, and economic reforms Continue slow progress in economic development and demographic transition Economic Emphasis Maximize economic competitiveness to the level envisaged in Vision 2040 benchmark countries Make modest investments in family planning and education Vision 2040 Maximize economic competitiveness to the level envisaged in Vision 2040 benchmark countries Simultaneously prioritize family planning and education to the Vision 2040 benchmark levels
Employment gap People ages 15+ Millions 25 20 15 10 Difference between labor force and employment Business As Usual Economic Emphasis Vision 2040 5-2011 2016 2021 2026 2031 2036 2040
Gross Domestic Product US$ Billions 800 700 600 500 Vision 2040 $677 $563 Demographic Dividend 400 300 Economic Emphasis 200 100 0 2011 2016 2021 2026 2031 2036 2040 Business As Usual
GDP per capita US$ $10,000 $9,567 $8,000 Vision 2040 Demographic Dividend $6,000 $6,084 $4,000 Economic Emphasis $2,000 $927 $0 2011 2016 2021 2026 2031 2036 2040 Business As Usual
DemDiv Uganda dissemination Launched at the National Population Conference in July 2014 Results included in NPA DD report signed by Pres. Museveni Credit: United Nations Population Fund Family planning is good for the children for the family welfare, and for the country. The family would spend less on children and their needs. In turn, they would save and make wealth. President Yoweri Museveni of Uganda, July 28, 2014
What metrics should we use for the demographic dividend? Change in GDP per capita Change in GDP Change in poverty Change in investment or capital stock Change in employment Change in labor force-employment gap
50% Percentage change in GDP per capita in final year: Economic only vs. economic + education + family planning 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Uganda Kenya Tanzania Malawi Cote d'ivoire Burkina Faso South Africa Ethiopia Zambia Nepal
Percentage change in GDP and GDP per capita in final year: Economic only vs. economic + education + family planning 50% 40% 30% 20% 10% 0% Uganda Kenya Tanzania Malawi Cote d'ivoire Burkina Faso South Africa Ethiopia Zambia Nepal -10% GDP GDP/pop
How much GDP changes depends on how much employment changes in relation to how much capital changes 2/3 X [% Change in Employment] + 1/3 X [% Change in Capital] = % Change in GDP
35% Percentage changes in employment, capital stock and GDP under two scenarios 30% 25% 20% 15% 10% 5% 0% -5% -10% -15% Capital stock Employment GDP