There is a growing body of literature that has analysed cross-sectional data which shows that there is a strong relationship between the current characteristics of the individual and their wellbeing. However, policymakers need to know about how these characteristics arose in order to determine the point in the life-cycle when interventions would be most cost effective. To answer this question, a life-course model is needed that captures in a quantitative way the impact of different influences (at different points in time) upon subsequent wellbeing.

Our previous research has identified that adult life satisfaction is mainly dependent on seven other contemporaneous dimensions of a person's adult characteristics. These are a person's education, employment, and earnings, plus their mental health, physical health, family status and criminal records. However, our central interest is in how these seven measures are determined and thus on how we can influence them (and thus wellbeing). We know that both a person's family background and childhood development will be important. But, little is known about the relative importance of specific components of a person's family background and childhood development. There is also little understanding about the timing of when these components begin to matter. Our primary research aims to address both of these areas.

Thus, in our primary research project, we will first test the hypothesis that a person's family background and childhood development affect adolescent mental health, by responses to Strenghts and Difficulties Questionnaire (SDQ), the Short Mood and Feelings Questionnaire (SMFQ) and by the Development and Wellbeing Assessment (DAWBA), mainly through their effect on our seven other contemporaneous dimensions. If our hypothesis is confirmed, we will then seek to isolate the causal effect of a number of specific components of a person's family background and childhood development, which are caused by exogenous mechanisms such as the raising of the school leaving age (RoSLA) and life events, to identify their relative importance and also how they interact with time.

In our second project, we would like to investigate the early determinants of psychological resilience which can be broadly defined as the person's ability to withstand exogenous negative shocks in life. There is a growing body of literature over the last decade on the causes and consequences of human's psychological resilience, especially people's ability to bounce back from significant bad life events (Rayo and Becker, 2007; Graham and Oswald, 2010; Perez-Truglia, 2012). This recent surge of interest is fuelled by the releases of new longitudinal evidence of hedonic adaptation to negative life events, including adaptation to unemployment, disability, and bereavement (Clark et al, 2008; Oswald and Powdthavee, 2008). Yet little is known, either by economists or psychologists, why certain individuals are better than others at bouncing back from a bad life event and why they are initially hurt less by such a shock.

Thus, in our second project, we wish to test the hypothesis that a person's psychological resilience can be determined early on in childhood. To do this, we would first need to measure the emotional trauma from bad shocks in their life events. We would then try to find the important determinants of this estimated measure of psychological resilience in children. We believe our research using ALSPAC data can provide us with new scientific evidence on whether or not the components of long-term well-being (e.g., individual's ability to cope with bad life shocks) are determined early on in childhood, or more specifically before the child was born.

Finally, in our third project we wish to use the ALSPAC data to develop a dynamic factor model of child and adolescent well-being. More precisely, we wish to look at the development of cognitive, non-cognitive and health capabilities in a dynamic framework where abilities are the result of parental environments and investments at different stages of childhood and adolescence(Cunha et al, 2010). We believe that the unique wide range of cognitive, non-cognitive and health measurements in the ALSPAC data will allow us to refine our current understanding of the dynamics of child development.

References:

Clark, A.E., Diener, E., Georgellis, Y. and Lucas, R.E. 2008. Lags and leads in life satisfaction: a test of the baseline hypothesis. Economic Journal, 118(529), F222-F243.

Cunha, F., J.J. Heckman, and Susanne M. Schennach (2010) "Estimating the technology of cognitive and noncognitive skill formation" Econometrica, Econometric Society, vol. 78(3), 883-931, 05.

Graham, L. and Oswald, A.J. 2010. Hedonic capital, resilience and adaptation. Journal of Economic Behavior & Organization, 76, 372-384.

Oswald, A.J., and Powdthavee, N. 2008. Does happiness adapt? A longitudinal study of disability with implications for economists and judges. Journal of Public Economics, 92(5-6), 1061-1077.

Perez-Truglia, R. 2012. On the causes and consequences of hedonic adaptation. Journal of Economic Psychology. In press

Rayo, L. and Becker, G.S. 2007. Evolution efficiency and happiness. Journal of Political Economy, 115(2), 302-337.