A spatial microsimulation approach to the analysis subjective happiness and well-being

This paper presents a spatial microsimimulation modelling approach to the analysis of subjective well-being and happiness. The modelling approach builds on relevant research on the measurement and analysis of mental health, subjective well-being and happiness measures as well as on past and on-going spatial microsimulation work by developing and using a spatial microsimulation methodology to define personal happiness and quantify and estimate its degree for different types of individuals, living in different areas. It is argued that since the degrees of well-being vary significantly between different individuals (different people are made happy by different things, life-courses etc.), microsimulation may be an ideal methodology to study and quantify happiness at the individual level. First, a review of pertinent literature on the measurement and analysis of subjective measures of well-being and happiness is presented and a case for a spatial microsimulation approach is made. The paper then shows how a spatial microsimulation method was used to link the British Household Panel Study (BHPS) to Census small area outputs (building on on-going work on how this link can be satisfactorily achieved), adding a geographical dimension to the existing happiness research based on this dataset. In particular, in the context of the research presented here, a spatial microsimulation model is developed and used to estimate the geographical distribution of individual contentment and well-being at different spatial scales. The BHPS data is combined with UK Census Small Area Statistics data on the basis of socio-economic variables that are deemed to be important in determining subjective well-being and happiness. The next step is to demonstrate the potential of spatial microsimulation for the analysis of geographical patterns of subjective happiness and well-being for various population sub-groups living in different localities, using spatial microsimulation. The paper then discusses the potential implications of the model outputs for public policy. It also revisits the assumptions that underpin the spatial microsimulation and discusses further the strengths as well as limitations of spatial microsimulation models for happiness research.