Spatial Analysis of Clustering of Foreclosures in the Poorest-Quality Housing Urban Areas: Evidence from Catalan Cities
Aaron Gutiérrez 1,*
and Josep-Maria Arauzo-Carod 2
and Josep-Maria Arauzo-Carod 2
1
Department of Geography, Rovira i Virgili University, 43480 Vila-seca, Catalonia, Spain
2
Department of Economics (CREIP-QURE), Rovira i Virgili University, 43204 Reus, Catalonia, Spain
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(1), 23; https://doi.org/10.3390/ijgi7010023
Received: 6 December 2017 / Revised: 10 January 2018 / Accepted: 11 January 2018 / Published: 12 January 2018
Abstract
This paper uses data on housing stock owned by financial entities as a result of foreclosures to analyze (1) the spatial logic of Spain’s mortgage crisis in urban areas, and (2) the characteristics of the types of housing most affected by this phenomenon. Nearest-Neighbor Index and Ripley’s K function analyses were applied in two Catalan cities (Tarragona and Terrassa). The results obtained show that foreclosures tend to be concentrated in the most deprived neighborhoods. The general pattern of clustering also tends to be most intense for smaller and cheaper housing. Our findings show that home foreclosures have been concentrated in only a few neighborhoods and precisely in those containing the poorest-quality housing stock. They also provide new evidence of the characteristics and spatial patterns of the housing stock accumulated by banks in Catalonia as a result of the recent wave of evictions associated with foreclosures. View Full-TextKeywords:
foreclosures; evictions; clustering; Nearest-Neighbor Index; Moran’s I; Ripley’s K; Catalonia
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Gutiérrez, A.; Arauzo-Carod, J.-M. Spatial Analysis of Clustering of Foreclosures in the Poorest-Quality Housing Urban Areas: Evidence from Catalan Cities. ISPRS Int. J. Geo-Inf. 2018, 7, 23.
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ISPRS Int. J. Geo-Inf.
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