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Call for Application——Asian MetaCenter Hands-on Workshop on Modelling and Projecting Sub-national Population Trends

Created Date 11/23/2016 颖机   View Numbers  1922 Return    
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 7-11 April, 2017 at Asian Demographic Research Institute (Shanghai University) 
  Analyzing and projecting sub-national population trends by age, sex, education and urban/rural place of residence: Assisting sustainable development planning and developing the Shared Socioeconomic Pathways (SSP) in selected Asian countries
Purpose:
  To analyze 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.
Background
  Understanding population dynamics and heterogeneity within a country provides important insights for explaining social and environmental changes. It also helps to identify vulnerable sections of the population that are affected most by these changes. Projections of population dynamics and heterogeneity can serve as a prediction that assist policy makers and other stakeholders in visualizing an alternative future, to assess what-if scenarios, or to simulate sensitivity tests of single or multiple variables. While demographers are interested purely in population dynamics, the users of population projections are spread in many disciplines, among them development studies with a focus on Sustainable Development Goals (SDG), and the climate change research community working with the Shared Socioeconomic Pathways (SSP) framework.
  To assist government planning and setting targets for administrators, national statistical agencies are mandated to maintain population counts and monitor dynamics by various demographic and socioeconomic characteristics at the national and sub-national levels. The data are collected through censuses, surveys and other data sources, such as tables and/or microdata, that are available from the National Statistical Offices who often also conduct analyses and projections. However, the quality and frequency of the implementation of such a mandate varies largely between countries making it difficult to conduct cross-country comparisons and to predict the future population development.
  National level and cross-country population dynamics are also maintained and projected at the international level, for e.g. the estimates and projections by age and sex of the United Nations, and by age, sex, and educational attainment of the Wittgenstein Center for Demography and Global human Capital (IIASA, VID/ÖAW, WU). These institutes have their own methods that are largely consistent between countries and often the best option available. The downside of such extensive cross-country projections is that they employ a top-down approach that largely ignores what is happening in the country (local knowledge and expertise) and lack local ownership making them less popular among local users either for national level studies or at sub-national levels. 
  The incomparability of data produced by national statistical agencies due to quality issues and differing methods and the moderate use of data produced by international agencies that apply a supra-national approach motivated us to develop a consistent method for studying population dynamics across and within countries by collaborating with local partner institutions.
Qualification
  Our team at the International Institute for Applied Systems Analysis (IIASA), Wittgenstein Center (IIASA, VID/ÖAW, WU), and the Asian Demographic Research Institute (ADRI), Shanghai University have developed multi-dimensional/multi-state models to study population dynamics at the global, regional, national and sub-national level. By producing global level population projections by age, sex, and educational attainment, and projections for the SSPs for climate change research we created a dataset that is relevant and in high demand(Lutz, Butz, and KC 2014; KC and Lutz 2014).
  At the sub-national level, we have completed the projections by age, sex, and educational attainment for the rural/urban population in 35 Indian States and are currently completing the SSP narratives. We have presented our methods and findings at international demographic conferences and are currently documenting them to be published as working papers and in peer-reviewed journals. In addition, we are packaging our models developed in R to share them with a broad audience.
Concept
  As a first step, we propose to identify national partners from different countries as specified below who have a particular interest in jointly developing a multi-dimensional/multi-state population dynamics model for the past and the future. Next, we will organize a series of seminars and workshops to discuss data issues particular for the country, develop narratives for future hands-on training sessions that cover our models and methods, and present new insights (methods and results) from each country specific population model. All our efforts will be documented and openly shared through publications in peer-reviewed journals, R-packages, and through a website-based data visualization. While ADRI/IIASA will work with the main scenario along with the SSPs and some SDG variants hosted in an open-access website, country teams will be enabled to develop their own scenarios.
 
Working Plan
  The first Workshop will be held at ADRI, Shanghai University on 7-11 April, 2017 and will be divided in two parts.
•             First part: Discussion of data, reliability, completeness, consistency etc. (1.5 days). In a seminar-style settings the participants from each country will present their case. The team should be identified by the end of 2016. By the end of the first part, we will be preparing a list of country-specific data issues and possibly the solution as well.
•             Second part: Introduction to methods of multi-dimensional demographic analysis in R (3.5 days). In this part of the workshop, we will move to a computer-lab and start the hands-on training using the R-codes developed at IIASA/ADRI. While we will use India as a case study for demonstration, depending on data readiness participants are welcome and encouraged to use their own data. By the end of the workshop, we expect that the participants can independently implement the R-codes and more importantly develop a a strong network with the other participants.
  The director or a relevant senior person will be invited for the first 1.5 days, and a junior researcher with the required technical skills will be appointed for the whole 5-days workshop.
  We will continue to work with the country teams in developing the national, SSP and SDG narratives. Participants are encouraged to visit our team at the ADRI at IIASA and vice-versa if needed. This collaboration will help identify and solve issues related to data and methods, and will be the basis to reconvene in a Second Workshop to present and discuss first results within the next one year.
Expenses: All expenses related to the Workshop will be covered by the ADRI.
Possible Participants: This workshop will be the first in a series with the focus initially on the following 8 countries: Bangladesh, China, India, Indonesia, Iran, Nepal, Philippines and Thailand.
Timeline
31th December, 2016: Deadline of the application. Please send an application (a letter of interest signed by director or senior person in the institution) along with CV of prospective participants to Samir KC (kcsamir@gmail.com / kc@iiasa.ac.at) or Yingji Wu (wuying1991.08@163.com).
By 7th January, 2017: Finalize the participants list
By 6th April, 2017: Prepare data (Co-ordinated by Markus Speringer)
7-11th April, 2017: Workshop (lead by Samir KC with Markus Speringer and Marcus Wurzer)
Reference
 
KC, Samir, and Wolfgang Lutz
 2014      The Human Core of the Shared Socioeconomic Pathways: Population Scenarios by Age, Sex and Level of Education for All Countries to 2100. Global Environmental Change: in press.
 
Lutz, Wolfgang, William P. Butz, and Samir KC, eds.
 2014      World Population and Human Capital in the 21st Century. Oxford, UK: Oxford University Press. http://ukcatalogue.oup.com/product/9780198703167.do.
 

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