The MIG research group focuses on applying advanced data collection and estimation methods to quantify and better understand the trends, patterns, drivers, and consequences of different types of migration considering its interactions with the social, economic, and environmental dimensions of sustainable development.
Migration is a key demographic component underlying population change. As a multifaceted process, it is influenced by various factors such as economic opportunities, social and political drivers, environmental changes, and conflicts. Due to its high volatility and complexity, migration is difficult to assess and forecast, thus requiring a combination of data sources and methods. The MIG research group employs innovative approaches to provide comprehensive estimates of internal and international migration and its underlying factors at global, national, and sub-national levels. A particular focus of the research group is exploring how climatic changes and environmental factors directly and indirectly influence migration, and how these effects differ across geographical locations and population subgroups. In addition, the research group offers valuable insights into the interconnections between sustainability, human development, and well-being, highlighting their relevance for migration processes worldwide.
07 September 2023
05 July 2023
24 January 2023
09 June 2023 Paris, France
05 June 2023 Ispra, Italy-webstreamed event
28 November 2022
07 September 2022
11 July 2022
Lutz, W. & Pachauri, S. (2023). Systems Analysis for Sustainable Wellbeing. 50 years of IIASA research, 40 years after the Brundtland Commission, contributing to the post-2030 Global Agenda. IIASA Report. Laxenburg, Austria: International Institute for Applied Systems Analysis (IIASA) 10.5281/zenodo.8214208. Niva, V., Horton, A., Virkki, V., Heino, M., Kosonen, M., Kallio, M., Kinnunen, P., Abel, G. , Muttarak, R., Taka, M., Varis, O., & Kummu, M...................... (2023). World’s human migration patterns in 2000–2019 unveiled by high-resolution data. Nature Human Behaviour 10.1038/s41562-023-01689-4. Andrijevic, M. , Schleussner, C.-F., Crespo Cuaresma, J., Lissner, T., Muttarak, R. , Riahi, K. , Theokritoff, E., Thomas, A., van Maanen, N., & Byers, E. (2023). Towards scenario representation of adaptive capacity for global climate change assessments. Nature Climate Change 10.1038/s41558-023-01725-1. (In Press) Durowaa-Boateng, A., Yildiz, D. , & Goujon, A. (2023). A Bayesian model for the reconstruction of education- and age-specific fertility rates: An application to African and Latin American countries. IIASA Working Paper. Laxenburg, Austria: WP-23-007 Heo, N., Chang, H.-C., & Abel, G. (2023). Investigating the distribution of university alumni populations within South Korea and Taiwan based on data from the LinkedIn advertising platform. Cities 137 e104315. 10.1016/j.cities.2023.104315.