Abstract
Our understanding of people’s well-being was, until very recently, inferred from observable objective indicators such as their income and education. These measures were then aggregated to generate an average that characterized the city or region. With the growing availability of sample survey data, we now have at our disposal an increasing range of subjective measures of well-being that capture quality of life assessments made by individuals themselves. It is these internal measures of subjective well-being from microdata that are now being widely used throughout the social sciences to study what we call well-being or “happiness.”
Contemporary interest in subjective measures of well-being stems from a wish to supplement market-based criteria such as GDP per capita with other more direct measures of societal well-being. Subjective measures are particularly useful in areas where the distribution of outcomes is not easily identified using other, especially market, criteria. The effect of investment in public infrastructure or the provision of green space or in fostering community networks or in redeveloping neighborhoods can be captured in responses to questions on well-being, preferably over time. These subjective measures, which have been shown to be highly correlated with clinical and other assessments of well-being, are likely to be of particular interest in regional science because of the way changes to places result from, or generate, a range of positive or negative externalities.
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Morrison, P.S. (2014). The Measurement of Regional Growth and Wellbeing. In: Fischer, M., Nijkamp, P. (eds) Handbook of Regional Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23430-9_16
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DOI: https://doi.org/10.1007/978-3-642-23430-9_16
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