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Understanding the spatial statistical properties of a real estate listings point pattern in San José, Costa Rica

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  • Eduardo Pérez-Molina

Abstract

One should expect real estate sales, and properties listed as for sale, to be concentrated on market hotspots. Using data of real estate listings from San José, Costa Rica, this expected clustering is examined using point pattern processes of detached housing, apartments, and vacant lots. Non-stationary G and J functions describe the patterns and their interactions. Potential determinants of the point pattern were selected based on previous studies and theory. Their effect on the point pattern was estimated using an inhomogeneous Poisson model, with its intensity a lognormal function of the determinants. Results show detached houses, apartments, and lots are all clustered point patterns. The cross density (joint G function) of houses with apartments and with lots exhibits clustering, suggesting the patterns are related; however, the cross density of apartments and lots is no different from a Poisson distribution (they are not related). The inhomogeneous Poisson model with Euclidean distance to the central business district (CBD), nearest municipal center, and nearest main road, as well as elevation and slope, proved better than homogeneous Poisson models in explaining the point patterns of houses, apartments, and lots.

Suggested Citation

  • Eduardo Pérez-Molina, 2024. "Understanding the spatial statistical properties of a real estate listings point pattern in San José, Costa Rica," Environment and Planning B, , vol. 51(5), pages 1124-1136, June.
    • Handle: RePEc:sae:envirb:v:51:y:2024:i:5:p:1124-1136
    DOI: 10.1177/23998083231208230
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    References listed on IDEAS

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