• Media type: E-Book
  • Title: More than the sum of their parts : valuing environmental quality by combining life satisfaction surveys and GIS data
  • Contributor: Silva, Jérôme [Author]; Brown, Zachary [Author]
  • imprint: Paris: OECD, 2013
  • Published in: OECD: OECD statistics working paper ; 20130001
  • Extent: Online-Ressource (23 S.); graph. Darst
  • Language: English
  • DOI: 10.1787/5k4840hfpwkb-en
  • Identifier:
  • Keywords: Umweltbewertung ; Zufriedenheit ; Europa ; Environment ; Economics ; Amtsdruckschrift ; Arbeitspapier ; Graue Literatur
  • Origination:
  • Footnote: Zsfassung in franz. Sprache
    Systemvoraussetzungen: Acrobat Reader
  • Description: While environmental economics studies using stated life satisfaction data have been gaining attention, much of this body of work remains exploratory. In this study we contribute to this emerging body of research by combining OECD survey data from four European countries on life satisfaction and perceptions of environmental quality with independent (i.e. mechanical) measurements of air quality and urbanity, from the European Environment Agency, to provide a broad picture of the environmental determinants of life satisfaction, and monetary valuation of air quality improvements. We also estimate that the value of a 1% reduction in air pollution (measured as mean annual PM10 concentrations) is worth the same on average as a 0.71% increase in per capita income. We find that environments which respondents perceive as noisy and lacking in access to green space have a significantly detrimental impact on life satisfaction. However, controlling for these negative factors (air, noise, and lack of green space), we also find a large positive residual impact of urban environments on life satisfaction. The use of independent, GIS-based measures of urbanity (proportion of urban surface area around households), as opposed to survey-based stated perceptions of urbanity, increases the precision of estimated air quality impacts on life satisfaction. Taken as a whole, our analysis highlights the need for conducting LS-based environmental assessment and valuation exercises using a broad array of independent data sources, in order both to obtain unbiased regression estimates and to facilitate interpretation of these estimates.