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Defining Housing Market Areas Using Commuting and Migration Algorithms: Catalonia (Spain) as a Case Study

Author

Listed:
  • Vicente Royuela

    (AQR-IREA Research Group, University of Barcelona, Avda Diagonal, 690, Barcelona, 08034, Spain, vroyuela@ub.edu)

  • Miguel A. Vargas

    (Facultad de Economía y Empresa, Universidad Diego Portales, Manuel Rodríguez Sur 253, Santiago, Chile, miguel.vargas@udp.cl)

Abstract

In the literature on housing market areas, different approaches can be found to defining them—for example, using travel-to-work areas and, more recently, making use of migration data. This paper proposes a simple exercise to shed light on which approach performs better. Using regional data for Catalonia, in Spain, housing market areas are computed with both commuting data and migration data. In order to decide which procedure shows superior performance, the uniformity of prices within areas is examined. The main finding is that commuting algorithms present more homogeneous areas in terms of housing prices.

Suggested Citation

  • Vicente Royuela & Miguel A. Vargas, 2009. "Defining Housing Market Areas Using Commuting and Migration Algorithms: Catalonia (Spain) as a Case Study," Urban Studies, Urban Studies Journal Limited, vol. 46(11), pages 2381-2398, October.
  • Handle: RePEc:sae:urbstu:v:46:y:2009:i:11:p:2381-2398
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    References listed on IDEAS

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    Cited by:

    1. Moises Lenyn Obaco Alvarez & Vicente Royuela & Xavier Vítores, 2016. "Computing functional urban areas using a hierarchical travel time approach," ERSA conference papers ersa16p238, European Regional Science Association.

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