Institut de Recerca en Economia Aplicada 2007 Documents de Treball 2007/7, 20 pages. Defining housing market areas using commuting and migration algorithms. Catalonia (Spain) as an applied case study By Vicente Royuela 1 , Miguel Vargas 2 . 1 Vicente Royuela Grup d'Anàlisi Quantitativa Regional-AQR (Universitat de Barcelona) Facultad CC. Económicas, Av. Diagonal, 690, 08034 Barcelona (Spain) Tel : +34 934021412, Fax number: +34 934021821.Email: vroyuela@ub.edu 2 Miguel Vargas Centre for Spatial and Real Estate Economics (CSPREE) The University of Reading Business SchoolandFaculty of Economics and Business, Diego Portales University, Chile. Manuel Rodríguez Sur 253, Santiago ChileTel +56(2)6762252Email: m.a.vargas@reading.ac.uk 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. Here we propose a simple exercise to shed light on which approach performs better. Using regional data from Catalonia, Spain, we have computed housing market areas with both commuting data and migration data. In order to decide which procedure shows superior performance, we have looked at uniformity of prices within areas. The main finding is that commuting algorithms present more homogeneous areas in terms of housing prices. Note: Vicente Royuela acknowledges the support of CICYT SEJ2006-07665 project and the Mobility grant of the Education and Science Ministry Ref PR2005-0253. 1