Table of Contents

Handbook of Research Methods and Applications in Happiness and Quality of Life

Handbook of Research Methods and Applications in Happiness and Quality of Life

Handbooks of Research Methods and Applications series

Edited by Luigino Bruni and Pier Luigi Porta

Offering a thorough assessment of the recent developments in the economic literature on happiness and quality of life, this Handbook astutely considers both methods of estimation and policy application. The expert contributors critically present in-depth research on a wide range of topics including culture and media, inequality, and the relational and emotional side of human life. Accessible and far-reaching, it will prove an invaluable resource for students and scholars of welfare and economics.

Chapter 9: Genetic and environmental contributions to life satisfaction

Mario Lucchini, Sara Della Bella and Luca Crivelli

Subjects: economics and finance, economic psychology, welfare economics, research methods, research methods in economics


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.

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