![MDM](/sites/default/files/styles/thumbnail/public/2022-05/dreamstime_s_79756601.jpg?itok=Pde0SN_M)
Through its research, the MDM Group aims to advance demographic modeling methods to assess and forecast population dynamics with a focus on demographic and spatial heterogeneity under different socioeconomic scenarios at the global, national, and sub-national level.
The MDM Group’s research focus is at the core of the IIASA strategic plan in rigorously incorporating the human-centered system model into systems analysis by considering the feedback mechanisms between human and other social, economic, and natural systems. The group has a strong focus on population forecasting using a scenario-based approach allowing for aligning future demographic components with socioeconomic scenarios such as the Shared Socioeconomic Pathways (SSPs) originally developed for the climate change research community. Apart from updating global projections of population, human capital, and other relevant dimensions using scenarios, the group also carries out innovative, policy-relevant research at the local and regional level, for instance, assessing social vulnerability to COVID-19 at a small spatial scale.
Models, tools, datasets
Projects
Staff
News
![SSP Human Core background](/sites/default/files/styles/thumbnail/public/2024-03/dreamstime_xl_167196730.jpg?itok=9Xw61pu_)
07 March 2024
Populations of the future: updated tool helps to visualize projections
![SAS visit](/sites/default/files/styles/thumbnail/public/2024-02/IMG_5432.jpg?itok=TQGXfpB-)
27 February 2024
Slovak delegation from the Institute of Economic Research visits IIASA
![University](/sites/default/files/styles/thumbnail/public/2024-02/Master%20Global%20Demography_%28c%29Pixabay%20Brian%20Merrill.jpg?itok=ASTYmu7Q)
22 February 2024
Master's Programme "Global Demography"
Events
Focus
![Europe population](/sites/default/files/styles/thumbnail/public/2024-06/dreamstime_l_79535764.jpg?itok=ZNry9rC3)
24 June 2024
Predicting EU migration trends: merging traditional and social media data
IIASA researchers Dilek Yildiz and Guy Abel highlight the benefits of a new statistical model that combines traditional data sources like the census with real-time Facebook data to estimate EU migrant populations, offering valuable insights for policymakers.
![A crowd of wooden figures surrounded by measuring tape representing information statistics, measurement of the number, trends of population growth.](/sites/default/files/styles/thumbnail/public/2024-06/dreamstime_m_150267675.jpg?itok=DzqgqNCM)
18 June 2024
Human capital growth persists with upcoming population decline
The world's population has surged from 1 billion in 1800 to just above 8 billion today, but demographers predict this growth will halt by the end of the 21st century. IIASA researcher Guillaume Marois explains how a new human capital-weighted population metric is reshaping our understanding of global population dynamics and economic potential.
Publications
Marois, G. , Crespo Cuaresma, J., Zellmann, J., & Reiter, C. (2024). A dataset of human capital-weighted population estimates for 185 countries from 1970 to 2100. Scientific Data 11 (1) e612. 10.1038/s41597-024-03466-y. Yildiz, D. , Wiśniowski, A., Abel, G. , Weber, I., Zagheni, E., Gendronneau, C., & Hoorens, S. (2024). Integrating Traditional and Social Media Data to Predict Bilateral Migrant Stocks in the European Union. International Migration Review 10.1177/01979183241249969. Gietel-Basten, S., Marois, G. , Torabi, F., & Kabiri, K. (2024). Reframing policy responses to population aging in Iran. Genus 80 (1) e8. 10.1186/s41118-023-00210-z. González-Leonardo, M., Neville, R., Gil‐Clavel, S., & Rowe, F. (2024). Where have Ukrainian refugees gone? Identifying potential settlement areas across European regions integrating digital and traditional geographic data. Population, Space and Place e2790. 10.1002/psp.2790. González-Leonardo, M., Rowe, F., Potančoková, M. , & Goujon, A. (2024). Assessing the Differentiated Impacts of COVID-19 on the Immigration Flows to Europe. International Migration Review e01979183241242445. 10.1177/01979183241242445.