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Quality of Life in regions, cities and for sub-populations

Quality of Life in regions, cities and for sub-populations. By Lewis Dijkstra Deputy Head of the Economic Analysis Unit, for DG Regional and Urban Policy. Why measure QoL in regions and cities?. It is captures people's daily life better, which boosts confidence in official statistics

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Quality of Life in regions, cities and for sub-populations

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  1. Quality of Life in regions, cities and for sub-populations By Lewis Dijkstra Deputy Head of the Economic Analysis Unit, for DG Regional and Urban Policy

  2. Why measure QoL in regions and cities? • It is captures people's daily life better, which boosts confidence in official statistics • It corresponds to important policy levels: • States, regions or provinces • Ministry for urban/rural areas • Mayors of cities • It captures more variation • Does it make sense to compare a country of 80 million to a country with 400 000 inhabitants or 300 km2 to 500 000 km2?

  3. Policies: spatial and/or individual • Income • Poverty • Health • Affordability of services • Quality of work • Discrimination • Crime • Noise • Air pollution • Access to services and amenities • Employment opportunities

  4. Regions and cities • Regions • Cities, towns & suburbs, and rural areas • Cities and their commuting zones • Other typologies • NUTS 1,2 or 3 • Revised degree of urbanisation • Revised Urban Audit • Geo-coding

  5. Degree of Urbanisation identifies three types of areas: Cities (densely populated) Towns and suburbs (intermediate) Rural areas (thinly populated)

  6. Degree of Urbanisation identifies three types of areas: Cities (densely populated) Towns and suburbs (intermediate) Rural areas (thinly populated)

  7. Sub-populations • Gender • Age • Foreign origin (visible minorities) • Household type • Employment status • Education • Sexual orientation • Religious affliation

  8. Data sources • Full coverage • Crime data • Register data • Census • National and regional accounts • GIS data • Samples • LFS • SILC • EQLS • Eurobarometer • Gallup

  9. Spatial scale Full coverage • Geographical flexibility: from neighbourhood scale upwards • Geo-coding Samples • Geographical scale depends on sample size • Multi-year average • Small area estimations

  10. Conclusions • Spatial dimension is critical to capture quality of life • Sample size of many surveys insufficient. A bigger SILC sample in large countries is needed. • Geo-coding of registers and survey respondents will add a lot of value. • Develop other techniques including small area estimations and data matching

  11. For more information InfoRegio:ec.europa.eu/inforegio

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