Population Economics

Human Capital: Health, Education and Labour Supply over the individual Life Cycle

Over the past ten years the modelling of life-cycle behaviour has developed into one of the key themes of the research group on population economics. Our work on optimal life-cycle investments into human capital development has advanced the theoretical literature on life-cycle behaviour on a number of counts: First, we seek to model realistic patterns of mortality and survival and analyse what they imply for investments into human capital, under which we subsume both education and health. Conversely, we model in detail how individual health behaviour shapes the life-cycle pattern of health and mortality. Second, we explore how human capital investments are shaped by socio-economic factors that have received little attention so far: the anticipation of future descendants, the presence of spill-overs in the consumption of health care, the interaction of health investments, educational investments and retirement and the presence of temporal risk aversion.

In extensions to this research we have explored the relationship between the value of survival and the reproductive value within general population models. Life-cycle modelling also forms the backbone to macro-economic overlapping generation models in which we have studied health and pension policies as well as the impact of population change (see Population Change and the Macro-Economy). Our research has been part of the EU FP-7 project “Long-Run Economic Perspectives of Ageing Societies” (2009-2012).

In addition to this agenda, we are investigating empirically the determinants of the exceptional longevity of academicians as an elite group of the population.

Currently we are undertaking work within the following areas:

 

Effect of Mortality Change on Education and Labour Supply

Alexia Prskawetz, Miguel Sánchez-Romero

In many countries, life expectancy at birth has been increasing at the unprecedented rate of three months per year since the 19th century. This demographic process, which leads to population ageing, puts pressure on the future sustainability of institutions—from families to governments—and calls for changes to the pension system. More generally, the ongoing and rapid change in the socio-economic and demographic conditions is expected to transform the individual lifecycles (human capital investments, retirement age, etc).

The recent literature shows that mortality improvements at different stages of life have a differential effect on retirement and on the length of education. However, none of the existing economic models integrate the most relevant lifecycle decisions simultaneously in a way that the results are consistent with the empirical evidence.

This research area is devoted to shed light on how longevity improvements at different ages transform the individual lifecycle in a manner that is consistent with the existing data. Furthermore, the modelling takes account of different institutional settings. In particular, our goals are

·         to study the relationship between the differential effect of mortality on education and the length of work

·         to understand the differential impact that alternative institutional settings, e.g. pension systems, have on the labour supply decisions and income inequality when individuals differ by their life expectancy.

To do so, in this project we will integrate realistic mortality patterns in life-cycle models of consumption and labour supply with endogenous human capital formation. Moreover, we will numerically implement general equilibrium models with overlapping generations in order to analyse the effect of mortality on economic growth.

The results obtained will provide researchers and policy-makers a better understanding of the effect of changes in mortality on future lifecycle decisions and on modern economic growth.

 

Biological and Economic Approaches towards the Life-Cycle

Michael Kuhn

This project addresses the consistency in the modelling of behaviour along the life course between economics and evolutionary biology. For this purpose we develop a model of life history theory in evolutionary biology and an analogous model of life-cycle theory in economics and solve for the optimal intertemporal allocation of fertility, of investments in survival, and (for the economic framework) of consumption. After discussing general similarities and differences between the two approaches, we present a version of the economic model that allows for a direct comparison between the economic and evolutionary life-cycle allocations in order to develop conditions under which fertility and survival investments are consistent.

 

Exceptional Longevity of Elites

Maria Winkler-Dworak

Members of academies of sciences have been shown to exhibit a remarkably high life expectancy and are being considered as vanguard groups in the achievement of longevity. Following the social gradient of mortality, members of learned societies should indeed exhibit much lower death rates than most other social groups. As scientific elites, they not only surpass the highest educational levels, they also occupy (or have retired from) prestigious positions usually associated with high income. Moreover, election into a learned society signifies an outstanding contribution to science and bestows an elevated status within, and to some extent outside, the scientific community. In this research project, we analyse the mortality experience of members of various learned societies in Europe and compare their death rates to those of the corresponding national populations. The life expectancy of population groups living under favourable conditions indicates the upper bounds of longevity to which national populations may aspire, given current knowledge and medical technology; insights that inform the debate about any further extension potential of life expectancy. Additionally, we obtain further understanding of social differences in mortality when combining our results for elites with estimates for other social groups or national populations at the time.

The analysis has been supported by the Austrian Science Foundation (FWF) under contract no. P20408-G14 („Age-Structured Populations with Fixed Size”).