There has been a rapidly growing number of studies of the geographical aspects of happiness and well-being. Many of these studies have been highlighting the role of space and place and of individual and spatial contextual determinants of happiness. However, most of the studies to date do not explicitly consider spatial clustering and possible spatial spillover effects of happiness and well-being. The few studies that do consider spatial clustering and spillovers conduct the analysis at a relatively coarse geographical scale of country or region. This article analyses such effects at a much smaller geographical unit: community areas. These are small area level geographies at the intra-urban level. In particular, the article presents a spatial econometric approach to the analysis of life satisfaction data aggregated to 1,215 communities in Canada and examines spatial clustering and spatial spillovers. Communities are suitable given that they form a small geographical reference point for households. We find that communities’ life satisfaction is spatially clustered while regression results show that it is associated to the life satisfaction of neighbouring communities as well as to the latter's average household income and unemployment rate. We consider the role of shared cultural traits and institutions that may explain such spillovers of life satisfaction. The findings highlight the importance of neighbouring characteristics when discussing policies to improve the well-being of a (small area) place.
DOCUMENT
Understanding how experiences unfold requires measuring participants' emotions, especially as they move from location to location. Measuring and mapping emotions over space is technically challenging, however. While a number of technologies to record and spatially resolve emotion data exist, they have not been systematically compared. We present emotion data collected at a natural and military heritage site in the Netherlands using three different methods, namely retrospective self report, experience reconstruction, and physiology. These data are applied to three corresponding mapping methods. The resulting maps lead to divergent findings, demonstrating that spatial mapping of emotion data accentuates differences between distinct dimensions of emotions.
MULTIFILE
Understanding how experiences unfold requires measuring participants' emotions, especially as they move from location to location. Measuring and mapping emotions over space is technically challenging, however. While a number of technologies to record and spatially resolve emotion data exist, they have not been systematically compared. We present emotion data collected at a natural and military heritage site in the Netherlands using three different methods, namely retrospective self report, experience reconstruction, and physiology. These data are applied to three corresponding mapping methods. The resulting maps lead to divergent findings, demonstrating that spatial mapping of emotion data accentuates differences between distinct dimensions of emotions.
MULTIFILE
