Modelling & Forecasting Human Capital (Theme C)

In this research area the methods of multi-dimensional mathematical demography are applied for quantitatively capturing, reconstructing and forecasting the changing composition of populations by age, sex, level of educational attainment, religion and place of residence, as well as possibly health status and labour force participation. The modelling is done primarily by WIC Research Group 7 on Human Capital Modelling but with direct input from the various other research areas that deal with the forces of human capital formation and depletion.

Staff forming the Human Capital Data Lab (WIC Research Group 8) is closely interwoven with the forecasting and the modelling group, not only in providing the necessary base-line populations by all the required characteristics for all countries but also in collecting and estimating the broadest possible historical database with comparably harmonised data by level of education. These two research groups (7 and 8) also served the SSP (Shared Socioeconomic Pathways) modelling community in the context of climate change assessment. A specific focus of WIC Research Group 8 is the dissemination of data produced at WIC including data sheets as well as the development of internet tools for data explorations.

A specific line of research on Forecasting and Ageing (WIC Research Group 6) deals with redefining the concepts of age and ageing and assesses prospective age (one indicator of this is expected time to death) in comparison to the conventional chronological age (time since birth). It also considers various aspects of health and cognitive ageing. Because it has strong forward looking components it is situated at the interface between human capital depletion and modelling/forecasting in Figure 2.

The Wittgenstein Centre aspires to be a world leader in the advancement of demographic methods and their application to the analysis of human capital and population dynamics. In assessing the effects of these forces on long-term human well-being, we combine scientific excellence in a multidisciplinary context with relevance to a global audience. It is a collaboration among the Austrian Academy of Sciences (ÖAW), the International Institute for Applied Systems Analysis (IIASA) and the University of Vienna.