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Interpolation methods for geographical data: Housing and commercial establishment markets

Author

Listed:
  • Jose M. Montero

    (Castilla-La Mancha University)

  • Beatriz Larraz

    (Castilla-La Mancha University)

Abstract

The estimation of commercial property prices in a touristic city can be explored through spatial interpolation methods, but in the presence of small sample sizes, auxiliary stochastic processes that are correlated with the prices of commercial establishments are needed. The aim of this paper is to compare the various estimates of commercial establishment prices in Toledo (Spain) provided by methods based on inverse distance weighting, 2-D shape functions for triangles, kriging and cokriging (the housing prices being the auxiliary stochastic process). The results indicate that kriging improves the classical interpolation methods and that cokriging has a clear advantage over kriging.

Suggested Citation

  • Jose M. Montero & Beatriz Larraz, 2011. "Interpolation methods for geographical data: Housing and commercial establishment markets," Journal of Real Estate Research, American Real Estate Society, vol. 33(2), pages 233-244.
    • Handle: RePEc:jre:issued:v:33:n:2:2011:p:233-244
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    Citations

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    Cited by:

    1. Jos魍ar𨁍ontero-Lorenzo & Beatriz Larraz-Iribas, 2012. "Space-time approach to commercial property prices valuation," Applied Economics, Taylor & Francis Journals, vol. 44(28), pages 3705-3715, October.
    2. Monica Palma & Claudia Cappello & Sandra De Iaco & Daniela Pellegrino, 2019. "The residential real estate market in Italy: a spatio-temporal analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2451-2472, September.
    3. Jeonghyeon Kim & Youngho Lee & Myeong-Hun Lee & Seong-Yun Hong, 2022. "A Comparative Study of Machine Learning and Spatial Interpolation Methods for Predicting House Prices," Sustainability, MDPI, vol. 14(15), pages 1-14, July.
    4. Gema Fernandez-Aviles & Roman Minguez & Jose-Maria Montero, 2012. "Geostatistical Air Pollution Indexes in Spatial Hedonic Models: The case of Madrid, Spain," Journal of Real Estate Research, American Real Estate Society, vol. 34(2), pages 243-274.
    5. José-María Montero & Román Mínguez & Gema Fernández-Avilés, 2018. "Housing price prediction: parametric versus semi-parametric spatial hedonic models," Journal of Geographical Systems, Springer, vol. 20(1), pages 27-55, January.
    6. Agnieszka Szczepańska, 2021. "Transport Accessibility in a Suburban Zone and Its Influence on the Local Real Estate Market: A Case Study of the Olsztyn Functional Urban Area (Poland)," Land, MDPI, vol. 10(5), pages 1-17, April.

    More about this item

    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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