Abstract: |
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. |