Authors: Renaud Le Goix*, Université Paris Diderot, Ronan Ysebaert, UMS RIATE CRNS, Universite Paris Diderot
Topics: Urban Geography, Spatial Analysis & Modeling
Keywords: Housing, Inequalities, Europe, Metropolitan Areas, Data, Affordability
Session Type: Paper
Start / End Time: 8:00 AM / 9:15 AM
Room: Grand Ballroom 1, Sheraton, IM Pei Tower, Second Floor Level
Presentation File: No File Uploaded
This paper seeks at informing and mapping the increased and unequal affordability gap, a critical issue for social cohesion in metropolitan areas in Europe. We present a framework towards the production of neighborhood-based data, with harmonized indicators, to examine the unequal spatial patterns of housing affordability in Europe. One problem is the unequal access to housing with regard to income and wealth. Another problem 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. Since the 2008 Global Financial Crisis (GFC) more specifically, the affordability crisis seems to have followed unprecedented pathways of accumulation and vulnerability for households in OECD countries : general price inflations has maintained, but with greater instability and volatility of local trends.
This research, conducted in 2018-19 by a European consortium, investigates spatial patterns of housing affordability in European Functional Urban Areas, comparing rents, property-buying, and measures of income, covering 9 case-studies in Poland, Spain, France, Switzerland. We cope with a data gap, i.e. a lack of harmonized spatial data to map and monitor affordability in Europe. We bring insights on how (1) institutional data, such as transaction 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 the analysis of affordability, and to compare within cities (between neighborhoods) and between cities, using various geographical levels of analysis (1km square-grid, municipalities, FUA).