Demographic metabolism at work

Wolfgang Lutz, International Institute for Applied Systems Analysis (IIASA)
Erich Striessnig, Wittgenstein Centre (IIASA, VID/ÖAW, WU)

Exactly half a century ago, Norman Ryder published his influential paper on “The Cohort as a Concept in the Study of Social Change” (Ryder 1965). In this paper, he introduces the concept of “Demographic Metabolism” which he uses to describe the massive process of personnel replacement driven by births, lives and deaths of individuals. Despite the fact that Ryder’s article already provides most of the necessary conceptual elements of a formal theory of social change with predictive power, such a theory had not yet been explicitly developed. In fact, the whole concept of demographic metabolism has not received much attention until recently, when the combination with the powerful analytical tools of multi-dimensional (multi-state) demography facilitated its operationalization (Lutz 2013). The purpose of this article, first of all, is to review and demonstrate the enormous potentials of the demographic metabolism approach for capturing and forecasting social change, exactly half a century after it had been first introduced. Secondly, we will highlight the application of this approach to the systematic reconstruction and projection of population projections by age, sex and highest level of educational attainment. Following this review section, the paper includes two entirely new applications of the theory: First, it is exemplified with the spread of European identity, secondly, it is applied to the question of the extent to which attitudes towards homosexuality in different countries of the world change from one cohort to the next. Based on this assessment, the paper will apply the demographic metabolism model to derive projections of the future prevalence of tolerance towards homosexuality in Japan, Spain and the US to 2040. The paper will conclude with a brief critical discussion and give an outlook to possible other fields of application of the presented approach.

  See paper

Presented in Session 30: Innovations in demographic methods