Happy places or happy people? A multi-level modelling approach to the analysis of happiness and well-being

Publication type

Research Paper


Publication date

June 1, 2008


This paper aims to enhance our understanding of substantive questions regarding self-reported happiness and well-being through the specification and use of multi-level models. To date, there have been numerous quantitative research studies of the happiness of individuals, based on single-level regression models, where typically a happiness index is related to a set of explanatory variables. There are also several single-level studies comparing aggregate happiness levels between countries. Nevertheless, there have been very few studies that attempt to simultaneously take into account variations in happiness and well-being at several different levels, such as individual, household, and area. Here, multilevel models are used with data from the British Household Panel Survey to assess the nature and extent of variations in happiness and well-being to determine the relative importance of the area (district, region), household and individual characteristics on these outcomes. Moreover, having taken into account the characteristics at these different levels in the multilevel models, the paper shows how it is possible to identify any areas that are associated with especially positive or negative feelings of happiness and well-being. Whilst most of the variation in happiness and well-being is attributable to the individual level, some variation in these measures is also found at the household and area levels, especially for the measure of well-being. Before controlling for explanatory factors, the district of Wycombe had the highest well-being, but having controlled for explanatory variables, Newcastle-upon-Tyne has the highest unexplained well-being. On the other hand, the district with the lowest feelings of well-being is Bracknell Forest; Slough - both before and after controlling for explanatory factors.




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