Housing, Price, (un)Affordability. Using Transactions Data to Analyze Neighborhood-based Dynamics of Affordability (Paris, Lyon, Avignon, France)

Résumé En

The context of the study stems from 3 decades of housing price increase, faster than the income of buyers, becoming an important driver of social polarization and household vulnerability. The novelty of the approach is to observe neighborhood change, comparing trajectories in 3 urban areas (Paris, Lyon and Avignon), by means of large datasets of individual transactions in Paris, Lyon and Avignon urban areas, to develop a spatial analysis of housing-based inequality in France.Research question: The contribution draws on a research agenda on French housing markets since the end of the 1990s, that explores the linkages of inflation with the ‘house price-credit feedback cycle’, a price regime that emerged with a shift towards asset-based welfare, the goal being to provide an empirically-grounded theorization of the socio-spatial inequalities that determine neighborhood choice and residential strategies.Methods: The paper will highlight some of the challenges in the analysis of datasets that differ substantially in their structure, exhaustiveness and content, with price references that do not always compare. Bridging heterogeneous data, the approach requires modeling and interpolation of highly disaggregated data (down to the address, and latitude-longitude coordinates), time series data (1996 – 2018 for transaction data), census and households INSEE data, and income data derived from tax rolls. Anticipated outcomes: The outputs of the study highlight the geographical structure of affordability, with spatio-temporal price to income ratios, debt-to-price analysis, and indicators on sellers and buyers, to analyze the local accumulation of wealth (and multi-ownership) as well as the spatial structure of affordability.