The use of geostatistics to estimate missing data in a spatial econometric model of housing prices

I. Tamaris Turizo, J. Chica Olmo, R. Cano Guervos

Abstract


Housing prices have been the subject of many studies, and some of them have tried to determine the influencing structural and location factors through hedonic econometric models. One of the main factors considered in the literature on real estate appraisals is the location of the dwellings. For this reason, this study combines the spatial methodologies of geostatistics and spatial econometrics. On the one hand, this work uses geostatistics to estimate missing data to account for the lack of information in the sampled real estate websites. On the other hand, the explanatory factors of prices are determined through spatial conometrics. The combination of both methods facilitates estimating housing prices in Santa Marta (Colombia), solving the problem of missing data. In the modeling, the problems of spatial heteroscedasticity and multicollinearity are corrected. This combination of methods could be of great interest to company ies and public agencies related to real estate activity, which is sustained by the information available on these real estate websites.

Keywords


Hedonic model; geostatistics; spatial econometrics; housing prices; missing data; heteroscedasticity

Full Text:

PDF

DOI: http://dx.doi.org/10.7764/RIC.00044.21

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Revista Ingeniería de Construcción

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Link partner: dewagg luxury12 liveslot168 luck365 kingceme mantap168 koko303 harta138 joker99 gacor77 qq1221 qqdewa qqalfa qqpulsa qq88asia qqslot777 qqnusa slot5000 idngg vegas4d slotsgg gen77 luxury138 idncash qq8821 liga788 ingatbola88 harum4d luxury777 kaisar888 gem188 ligaplay88 laskar138 okeplay777 goyangtoto babetoto asian4d birutoto kong4d kenzototo warungtoto pokerseri autowin88 vegas77 slot gacor