Luca Crivelli, Gianfranco Domenighetti and Massimo Filippini
Mario Lucchini, Sara Della Bella and Luca Crivelli
In recent decades a great deal of research about the nature and causes of subjective well-being (SWB) has emerged. Economists, psychologists and sociologists have unravelled the socioeconomic and psychological determinants of SWB, often forgetting or underestimating the role of genetic factors in accounting for the relative stability in SWB over the life span. This chapter offers a contribution to the research in this field by providing a robust estimate of the role of genetic endowment in the explanation of the self-reported level of life satisfaction. The empirical analysis is performed by applying a model of variance decomposition (ACE multilevel model) to a large dataset that entails family data coming from waves 2010, 2011 and 2012 of the ISTAT-Multipurpose Survey on Households. The heritability estimate for satisfaction with life (that’s to say, the proportion of the phenotypic variance ‘explained’ by the additive genetic factors) is equal to 45 per cent, an estimate that appears to be in line with those obtained by studies on twins. The specificity component, which captures a combination of measurement error and unique environmental influences, is around 41 per cent, while the influence exerted by the shared environment is rather small but not marginal (14 per cent), in contrast to other studies that give zero weight to this component. These robust estimates suggest that informative genetic designs derived from behavioural genetics can support social sciences in their attempt to develop a more systematic understanding of SWB.
Luca Crivelli, Sara Della Bella and Mario Lucchini
Studies concerning the determinants of subjective well-being (SWB), conducted in several countries and based on different datasets and methods, have all shown that health is one of the strongest predictors of individual happiness. However, more work is necessary in order to determine whether this relationship is a truly causal one and to unravel the temporal dynamics of the effect of health on SWB. In this chapter we aim, first of all, to provide an accurate estimate of the effect of self-assessed health on SWB by using the Swiss Household Panel dataset and panel data models that enable us to get rid of unobserved heterogeneity, which represents the main obstacle in models trying to estimate causal effects. As a second objective, we focus on the study of the temporal dynamics underlying the emergence of happiness and the relationship between happiness and health. We are interested in clarifying: (a) whether people are able to fully adjust to past health circumstances as well as to past life events and (b) whether SWB is autoregressive. In other terms, we investigated the existence of general and specific habituation in SWB. In this chapter we applied a FE model in order to investigate specific habituation channels and a GMM model in order to understand whether life satisfaction (our indicator of SWB) is autoregressive. In conclusion our models confirm the strong association between health and SWB revealed by previous studies. Both the FE and the GMM model prove that current health is a strong predictor of SWB.