Warren Sanderson
Guest Research Scholar
Social Cohesion, Health, and Wellbeing Research Group
Population and Just Societies Program
Biography
Warren Sanderson rejoined IIASA in June 2008 as an Institute Scholar. He is also a Professor of Economics and Professor of History at Stony Brook University in New York State, USA. In addition, he is co-chair of the Department of Economics there. He holds a PhD in economics from Stanford University.Professor Sanderson first came to IIASA in 1980 and worked in the World Population Program. Since that time he has been a recurrent visitor to that Program. His research interests are in population-economic interactions. He has published in a variety of journals, including Nature, Science, Population and Development Review, Demography, Population Studies, and Population Index.
His recent research includes probabilistic population forecasting, measuring aging in ways that take life expectancy change into account, and the effects of education and other demographic changes on economic growth.
Last update: 10 JUN 2008
Publications
Sanderson, W. & Scherbov, S. (2023). The effect of the COVID-19 pandemic on life expectancy in the USA: An application of hybrid life expectancy. Biology Methods and Protocols 8 (1) bpad025. 10.1093/biomethods/bpad025.
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.
Sanderson, W.C. & Scherbov, S. (2023). Ageing and Dependency 1. In: The Routledge Handbook of the Economics of Ageing. Eds. Bloom, D.E., Sousa-Poza, A., & Sunde, U., pp. 506-519 London, UK: Routledge. ISBN 978-100081277-0 10.4324/9781003150398-33.
Scherbov, S. , Gietel-Basten, S., Ediev, D. , Shulgin, S., & Sanderson, W. (2022). COVID-19 and excess mortality in Russia: Regional estimates of life expectancy losses in 2020 and excess deaths in 2021. PLOS ONE 17 (11) e0275967. 10.1371/journal.pone.0275967.
Barmpas, P., Tasoulis, S., Vrahatis, A.G., Georgakopoulos, S.V., Anagnostou, P., Prina, M., Ayuso-Mateos, J.L., Bickenbach, J., Bayes, I., Bobak, M., Caballero, F.F., Chatterji, S., Egea-Cortés, L., García-Esquinas, E., Leonardi, M., Koskinen, S., Koupil, I., Paja̧k, A., Prince, M., Sanderson, W., Scherbov, S. , Tamosiunas, A., Galas, A., Haro, J.M., Sanchez-Niubo, A., Plagianakos, V.P., & Panagiotakos, D. (2022). A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the ATHLOS project. Health Information Science and Systems 10 (1) e6. 10.1007/s13755-022-00171-1.