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Research Pillar on Human Capital and Development

 

The research pillar aims to achieve through research and modeling a good understanding of issues related to fertility, mortality, migration, human capital, and development in Asia at national and sub-national level. For this purpose, the research pillar will develop aharmonized database from census and surveys relevant to demographic and human capital (education and health) characteristics and differential behaviors of thepopulation. The database will be then used to conduct comparative analysis across Asia at national and sub-national level (in larger countries) to analyze differential progression in various demographic and human capital related processes. It then aims to develop population and human capital projection models for each country of Asia. The research pillar plans to apply the research findings and the projections by fostering intra- and inter-disciplinary collaboration to future prospects of important population and development related issues (e.g. SDG indicators, Ageing, labor force, urbanization, food, water, airpollution, energy, environmental impacts, etc.)

Core members:

Samir KC (Leader of the research pillar, Professor)

Wu YingJi (Research Assistant and Ph.D. candidate)

 

External collaborators:

Marcus Wurzer (IIASA), Markus Speringer (IIASA), Wolfgang Lutz (IIASA)

 

Research Assistants:

Chen Lin

 

Biography:

Samir KC 

                                                       

Samir KC is a professor and a founding member of the Asian Demographic Research Institute (ADRI) at Shanghai University. KC leads ADRI’s research pillar on Human Capital and Development. In parallel, KC has worked at the International Institute for Applied Systems Analysis (IIASA) since 2005, and currently leads the 'Modelling Human Capital Formation' project at the Wittgenstein Centre for Demography and Global Human Capital, IIASA.

KC's major research interests are: developing and applying multi-state population models in demographic analysis and projections, with a particular focus on modelling human capital formation in education and health; and differential vulnerability to natural disasters at national and sub-national levels. KC’s work has been published in Science magazine (2011, 2014) and other peer-reviewed journals. Recently, KC has co-edited and written several chapters in the book “World Population and Human Capital in the Twenty-First Century” published by Oxford University Press in 2014.  

After obtaining a master's degree in Statistics from Tribhuvan University, Nepal (1997), KC taught university statistics in Kathmandu and worked as a biostatistician at the Nepal Health Research Council. KC received his PhD from the University of Groningen, the Netherlands (2009).

 

Yingji Wu

Yingji Wu is a Chinese,Ph.D. candidate and research assistant of Asian Demographic Research Institute (ADRI) at Shanghai University. His major research interests are: developing and applying multi-state population models in China demographic analysis and projections: and effect of China family planning policy at national and sub-national levels.Currentlyhe is participating in projects to build a multi-state projection models for China population and human capitals.

 

Ongoing Projects:

1.       Sub-national population projection in 11 Asian countries:

Analyzing and projecting recent trends in sub-national populations stratified by education and urban/rural residence, and develop alternative future scenarios following the SSP narratives and SDG scenarios in selected Asian countries.

 

Researchers atthe Asian Demographic Research Institute (ADRI), Shanghai University,  IIASA, the Wittgenstein Center for Demography and Global Human Capital (IIASA, VID/ÖAW, WU) have developed multi-dimensional/multi-state models to study population dynamics at the global, regional, national and sub-national level. Currently, an initiative to disseminate the methodology is undergoing in collaboration with institutional partners in eleven Asian countries/regions (Bangladesh, China, Hong Kong, India, Indonesia, Iran, Nepal, Pakistan, Philippines, Sri Lanka, and Thailand).

 

The first workshop took place between 7-11 April 2017 at ADRI, Shanghai University with more than 25 participants from more than 11 countries. The workshop focused on demographic and data issues in each country followed by an introduction tothe methodology of multistate demography.A hands-on training session with an R-package (MSDem, Multistate Demography) was conducted. While IIASA/ADRI will work with the main scenario along with the SSPs and some SDG variants hosted on an open-access website, country teams will be enabled to develop their own scenarios

 

Upcoming 2nd workshop: 22-24thJanuary 2018

 

2.       Understanding important sources of heterogeneity in India:

We conducted subnational population projections for India motivated by two research questions: (1) How does the accounting of socioeconomic heterogeneity, measured by educational attainment, improve population projections for India?, and (2) How will changing patterns in urbanization affect the population projections, depending on the spatial scale (national vs. subnational) considered in the projections?

 

In a country like India national projections ignoring spatial and socioeconomic heterogeneity would be too short-sighted considering its sheer population size of 1.2 billion in 2011. It was surprising to see that our population projections for India with baseline scenario were consistent with the UN medium variant and Wittgenstein Centre SSP2 until 2070. We found that while our fertility assumptions are lower, our mortality assumptions were also lower and compensated for the lower number of births (and no international migration) with ahigher number of survivors.

 

The results show that the overall fertility for India is lower than estimated/assumed by UN and Wittgenstein Centre due to lower starting values in our projection as well as due to explicit consideration of education in the model. This results in a rapid TFR decline to about 1.85 children per woman in the next two decades and stabilization for the rest of the century. The projection resulted in aslower rate of urbanization in India from 31% in 2011 to 40% in 2051, compared to the UN urbanization projection and we presented several explanations for that.

 

Presented at PAA (2016, 2017) and EPC (2016)

IUSSP 2017: Three presentations (30-31st, Oct 2017)

 

3.       China Study:

China has completed theuniversal transition to primary education, one of the Millennium Development Goals 2000-2015, long before the MDGs were announced in 2000. The new Sustainable Development Goals targeted for 2030 (United Nations, 2016), has raised the level and targets (SDG 4.1) a global achievement of universal secondary education, without explicitly mentioning the level i.e., lower (also known as basic education) or upper (high school) at first. However, recently revised list of indicators mentions lower secondary as the global target (SDG target: 4.1.1). In either case, we areinvestigating how challenging it will be - in terms of resources - for China to meet such target(s) of universal secondary education at a national and subnational level. We will also analyze whether current education policies in China are adequate enough to meet the SDG’s education target.

 

Presented at PAA 2017 by Wu Ying Ji.

IUSSP 2017: Poster Session 52

 

 

Publications

 

KC S, Speringer M, & Wurzer M (2017). Population projection by age, sex, and educational attainment in rural and urban regions of 35 provinces of India, 2011-2101: Technical report on projecting the regionally explicit socioeconomic heterogeneity in India. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-17-004

 

Abel G, Barakat B, KC S, & Lutz W (2016). Meeting the Sustainable Development Goals leads to lower world population growth. Proceedings of the National Academy of Sciences 113 (50): 14294-14299. DOI:10.1073/pnas.1611386113.


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