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Environment, Land-use and Well-being

Environment, Land-use and Well-being. Finbarr Brereton, J Peter Clinch and Harut Shahumyan UCD Dublin.

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Environment, Land-use and Well-being

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  1. Environment, Land-use and Well-being Finbarr Brereton, J Peter Clinch and Harut Shahumyan UCD Dublin

  2. HAPPINESS(Happiness, Political Institutions, Natural Environment and Space)A Comparative Analysis of the influence of environmental conditions, environmental regimes and political context on subjective well-being

  3. Motivation Background Environment and Well-being The Economics of Happiness Environment and Happiness Methodology European Social Survey and CORINE land cover Geographical Information Systems Results and conclusions Outline

  4. Motivation Advance the understanding of the influence of land use and environment on welfare and the implications for policy Quality of life and land use are mutually inter-related (MEA, 2005) In large central cities, the literature shows that environmental and urban conditions operate jointly to reduce welfare (e.g. MacKerron and Mourato, 2009)

  5. Background Urbanization, expressed as the proportion of people living in urban places shows a value around 80% in most European countries. There is concern about the impacts of current patterns of urban development on environmental conditions and quality of life within urban-regions(Antrop, 2004). European Environment Agency (EEA) studies showed a significant increase of built surface at the expense of open space (EEA 2002; 2006) Green space is under pressure from various urban development processes such as densification and urban regeneration programmes (Pauleit et al. 2003).

  6. Environment and Well-being Environment is found to influence well-being Increases recovery rates among hospital patients with natural views (Ulrich, 1984) Noise is found to affect health (Haralabidis et al., 2008) Air Pollution: lead, particulate matter (Cifuentes et al., 2001) Long tradition in the Hedonic literature (Rosen, 1974, Roback, 1982 and Bloomquist et al., 1988). Constructing quality of life indices as the weighted averages of amenities in a particular area, usually a city region

  7. The Economics of Happiness Happiness (categorical) data have been used to understand the determinants of Subjective Well Being (SWB) Socio-demographic characteristics Socioeconomic and macroeconomic characteristics (Clark and Oswald, EJ 1994; Easterlin, JEBO 1995; Oswald, EJ 1997; Di Tella et al., AER 2001; Stutzer and Frey, EJ 2001; Blanchflower and Oswald, JoPE 2004; Stutzer, JEBO 2004; Clark et al., 2008 JoEL)…………..

  8. LS functions, some examples (from Alesina et al. JoPE 2001 and from van Praag and Baarsma, EJ 2005) The Economics of Happiness

  9. Environment and Happiness A more recent literature on the economics of happiness has begun examining the effect of environmental amenities on human welfare directly Frey and Stutzer, 2004 Van Praag and Baarsma, 2005 Welsch, 2002; 2006 Rehdanz and Maddison, 2005 Ferrer-i-Carbonell and Gowdy 2007 Luechinger 2009 etc… Using subjective well-being data toconstruct quality-of-life indices as an alternative to the conventional indices using weights derived from hedonic regressions, Moro et al. 2008

  10. Environment and Happiness Data constraints Previous studies were hindered by a lack of adequately disaggregrated data (Welsch, 2006; Rehdanz and Maddison, 2002), where data constraints at the local and regional levels restricted analysis to aggregated data at the national level, or to focusing on a particular localised area where richer data was available. Only a few papers to date have been able to capture the effects of environmental factors at the geographical level (local or regional) at which individuals actually experience them

  11. Environment and Happiness Luenchinger 2009 Air Quality in Germany Valuing Flood disasters MacKerron and Mourato 2009 Air quality in London city centre Brereton et al. 2008 Local amenities in Ireland These papers use Geographical Information Systems (GIS)

  12. Methodology Data LS scores, individual, social and economic data provided by Rounds 1-3 of the European Social Survey Land use data provided by CORINE land use dataset Question types “How satisfied are you with your life as a whole these days?” “Taken all together, how would you say things are these days - would you say that you are very happy, pretty happy, or not too happy?”

  13. European Social Survey

  14. Life Satisfaction in Europe

  15. Life Satisfaction in Europe

  16. CORINE Land cover • Pan-European land cover database carried out within each European member state; • Vector spatial dataset • Land cover digitized based on the interpretation of medium resolution satellite imagery and assigned a land use class based on a standardized land cover nomenclature defined by the EEA. • The minimum area mapped in the dataset is 25 hectares.

  17. CORINE Land cover

  18. CORINE Land cover

  19. CORINE Land cover - 2000

  20. CORINE Land cover - 2006

  21. CORINE Land cover • For the purposes of this study, the original 44 land use categories of the CORINE nomenclature were re-categorised for the regression analysis into the following classes: • Residential • Commercial and Industrial • Mines and Dumps • Green Urban Spaces • Agricultural Land • Forestry • Natural Areas • Water bodies

  22. Geographic Information Systems (GIS) • GIS is a powerful computing tool that allows the visual representation of spatially referenced data. • Represents data as countable numbers of points, lines and polygons in two-dimensional space (Goodchild and Haining, 2004) • Link various datasets using spatial identifiers (Bond and Devine, 1991). • It represents a base for spatial data analysis and provides a range of techniques for analysis and visualisation of spatial data. • It provides tools for integrating, querying and analysing a wide variety of data types, such as scientific and cultural data, satellite imagery and aerial photography, as well as data collected by individuals, into projects, with geographic locations providing the integral link between all the data. • GIS is widely-used as a planning and analysis tool and provides a powerful set of tools for spatial analysis and modelling.

  23. Geographic Information Systems (GIS) • GIS requirements • Collection, assimilation and pre-processing of spatial datasets • GIS data layers • Land use; Administrative boundaries • Constructed variables at NUTS level • European Nomenclature of Territorial Units for Statistics (NUTS) is a geocode standard for referencing administrative divisions of countries for statistical purposes developed by the European Union.

  24. Preliminary Results Significance Level: *** = 1%, ** = 5%, * = 10%

  25. Conclusions • Land use influences well-being • Well-being is lower in more urbanised, central city locations and increases as the typology becomes more rural • Green areas + sig. • Agricultural areas - sig. • Water bodies + sig.

  26. Caveats • Minimum mapping area in the CORINE land cover database is 25 hectares • Low sample size in some NUTS regions • Ongoing Work • Aggregate the NUTS based on local association • More disaggregated land use classes • Country models • Multi-level modelling

  27. Thank you

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