Using data from the OECD Regional Well‐Being Index – a set of quality‐of‐life indicators measured at the sub‐national level – we construct a set of composite well‐being indices. We analyze the extent to which the choice of five alternative aggregation methods affects the well‐being ranking of regions. We find that regional inequality in these composite measures is lower than regional inequality in real GDP per capita. For most aggregation methods, the rank correlation across regions appears to be quite high. It is also shown that using alternative indices instead of GDP per capita would only have a small effect on the set of regions eligible for aid from EU Structural Funds. The exception appears to be an aggregation based on how individual dimensions relate to average life satisfaction across regions, which would substantially change both the ranking of regions and which regions would be eligible for EU funds.
A frequent criticism of GDP states that events that obviously reduce welfare of people can nevertheless increase GDP per capita. We use data of natural disasters as quasi experiments to examine whether alternatives to GDP (Human Development Index, Progress Index, Index of Economic Well-Being and a Happiness Index) lead to more plausible responses to disasters. Applying a Differences-in-Differences approach and estimates from various panels of countries we find no noteworthy differences between the response of real GDP per capita and the responses of suggested alternative welfare measures to a natural disaster except for the Human Development Index.
Nicht nur vor dem Hintergrund des Klimawandels wird die Ressource Wasser immer wichtiger. Um den Herausforderungen zu begegnen, ist eine sozioökonomische Wasserforschung notwendig. Doch wie können die dabei generierten sozioökonomischen Erkenntnisse in die Praxis einfließen?
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AbstractWe discuss properties of alternatives or complements to GDP as a measure of welfare at business cycle frequencies. We argue that these figures are not useful to measure the welfare costs of business cycles. First, data is not available at an appropriate quality and frequency. Second, since the suggested time series sometimes correlate negatively with each other composite indices will lead by construction to very low welfare costs of business cycles. Third, cross-section and quasi-panel evidence based on different samples of countries reveals no impact of the stance of the business cycle on some suggested welfare measures. JEL-Classification: D06, E01, E32, I31
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