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The Spatial Structure of Housing Prices in Madrid: Evidence from Spatio-temporal Scan Statistics

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Handbook of Scan Statistics

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Abstract

We apply spatio-temporal scan statistics on the distributions of asking price per meter squared for various segments of the housing market (attics, houses, flats of various sizes) in the city of Madrid for 5 years during the period 2008–2019. Our application shows how spatio-temporal scan statistics can be useful for assessing the dynamics of urban spatial structure analyzed through the lens of housing prices. The focus on the post-2008 period and the computation of prospective clusters allows to detect the winners and the losers of the 2008 real estate crisis and to uncover new trends during the post-crisis period. We show that the economic crisis in Madrid has had a strong impact on housing market with increased polarization between the center and the periphery and between the northern and southern areas of Madrid, with some heterogeneity depending on the neighborhood, on the market segment, and on the urban policies undertaken.

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Notes

  1. 1.

    Numerous studies compare the behavior of the statistic for different forms of the window (e.g., Huang et al. 2008) and the determination of the maximum optimal size (Kang and Jung 2017, Han et al. 2016).

  2. 2.

    Kulldorff (2001) discusses the limitations in using the spatial version of the scan test for each temporal period instead of using the spatio-temporal version of the scan statistic.

  3. 3.

    Defined here as the observations that are above Q3 + 1.5(Q3 – Q1) or below Q1 – 1.5(Q3 – Q1), where Q1 and Q3 are, respectively, the first and the third quartile of the distribution.

  4. 4.

    For ease of exposition, we present the results in terms of “high price clusters” or “low price clusters,” whereas they are strictly defined as clusters of high (respectively, low) prices per meter square in logs.

  5. 5.

    In what follows, the numbers in brackets represent the number of the district that can be visualized in Fig. 2.

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Acknowledgements

Fernando A. López is supported by the program Groups of Excellence of the Region of Murcia, Fundación Séneca, Science and Technology Agency of the region of Murcia project 19884/ GERM/15 and by Spanish Ministry of Economics and Competitiveness (PID2019-107800GB-I00/AEI/10.13039/501100011033)

Author information

Authors and Affiliations

  1. Department of Applied Economics, Universidad Autónoma de Madrid, Madrid, Spain

    Coro Chasco

  2. Nebrija University, Madrid, Spain

    Coro Chasco

  3. CESAER UMR1041, AgroSup Dijon, INRAE, Université de Bourgogne Franche-Comté, Dijon Cedex, France

    Julie Le Gallo

  4. Department of Quantitative Methods and Computing, Technical University of Cartagena, Cartagena, Spain

    Fernando A López

Authors
  1. Coro Chasco
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  2. Julie Le Gallo
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  3. Fernando A López
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Corresponding author

Correspondence to Julie Le Gallo .

Editor information

Editors and Affiliations

  1. University of Connecticut Dept. Statistics, Storrs, CT, USA

    Joseph Glaz

  2. University of Pireaus Dept. Statistics & Insurance Sciences, Piraeus, Greece

    Markos V. Koutras

Section Editor information

  1. Department of Statistics, University of Connecticut, Storrs, CT, USA

    Joseph Glaz

  2. Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece

    M. V. Koutras

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Chasco, C., Le Gallo, J., López, F.A. (2020). The Spatial Structure of Housing Prices in Madrid: Evidence from Spatio-temporal Scan Statistics. In: Glaz, J., Koutras, M.V. (eds) Handbook of Scan Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8414-1_58-1

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  • DOI: https://doi.org/10.1007/978-1-4614-8414-1_58-1

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