Unequal housing affordability across European cities. The ESPON Housing Database, Insights on Affordability in Selected Cities in Europe

Keywords: housing price, affordability, socio-spatial inequalities, functional urban areas, open access database
Session Type: Virtual Paper
Day: Friday
Session Start / End Time: 4/9/2021 08:00 AM (Pacific Time (US & Canada)) - 4/9/2021 09:15 AM (Pacific Time (US & Canada))
Room: Virtual 38

Abstract

This study seeks at informing and mapping the increased and unequal affordability gap, a critical issue for social cohesion and sustainability in metropolitan areas in Europe. We discuss a framework towards the production of neighborhood and local spatial data, structured with harmonized indicators, to examine the unequal spatial patterns of housing affordability across a selection of European cities.
One problem is the unequal access to housing with regard to income and wealth. Another being that this gap has widened during the last decades: since the 1990s, housing prices have on average increased faster than the income of residents and buyers. We characterize affordability with measures of price (property and rent) and income in a selection of European Functional Urban Areas (FUAs). The methodological goal was to cope with a data gap, i.e. a lack of harmonized spatial data to monitor affordability in Europe. T
his research, conducted in 2018-19 by a European consortium for the ESPON agency, investigates spatial patterns of housing affordability, comparing rents, property-buying, and measures of income, covering 4 countries and one cross-border region: Geneva (Switzerland), Annecy-Annemasse, Avignon and Paris (France), Madrid, Barcelona and Palma de Majorca (Spain) and Warsaw, Lòdz and Krakow (Poland). We bring insights on how (1) institutional data (s.a. transactions data), can be bridged with (2) unconventional data (“big data” harvested on line) to provide a cost-effective and harmonized data collection effort that can contribute to compare affordability within cities (between neighborhoods) and across cities, using various geographical levels (1km square-grid, municipalities, FUAs).