Felipe Miguel Valdez Gómez de la Torre, Xuwei Chen
{"title":"Housing price determinants in Ecuador: a spatial hedonic analysis","authors":"Felipe Miguel Valdez Gómez de la Torre, Xuwei Chen","doi":"10.1108/ijhma-09-2023-0121","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThis paper aims to compare the efficiency of spatial and nonspatial hedonic price models in capturing housing submarkets dynamics for cities in developing countries. This study expects to contribute to a better understanding of the housing price determinants from both nonspatial and spatial perspectives. In addition, this paper fills a gap in the literature on the study of housing prices from a spatial perspective in Latin American cities.\n\n\nDesign/methodology/approach\nThis study uses a comparative analysis between an ordinary least squares regression and a geographical weighted regression, GWR. The study also assesses the performance of two distinct data sources: the city’s cadastral records and a real estate sales web portal.\n\n\nFindings\nThe results suggest that compared to the traditional regression model, the spatial regression models are more effective at capturing housing market variations on a fine scale. Moreover, they reveal interesting findings on the spatial varying, sometimes contradictory effects of some housing attributes on housing prices in different areas of the city, suggesting the potential impact from segregation.\n\n\nResearch limitations/implications\nThe availability of data on housing prices and characteristics in Latin American cities is fragmented and complex. The level of detail, granularity and coverage is not consistent over time. For this reason, this study combines and compares data sets from official and unofficial sources in an effort to close this gap. Likewise, the socioeconomic variables that come from the census must be carefully analyzed, knowing the historical context in which they were constructed, what they represent and their interpretation.\n\n\nPractical implications\nThis paper suggests that despite the improvement on the spatial models, the selection of a specific one should always be based on the diagnosis of it as it highly depends on the data used and the objectives of the study.\n\n\nOriginality/value\nThis study enriches the limited body of literature on spatial hedonic price models of housing in Latin American cities. It also shed light on the importance of spatial approaches to identify complex housing submarkets.\n","PeriodicalId":14136,"journal":{"name":"International Journal of Housing Markets and Analysis","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Housing Markets and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/ijhma-09-2023-0121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"URBAN STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
This paper aims to compare the efficiency of spatial and nonspatial hedonic price models in capturing housing submarkets dynamics for cities in developing countries. This study expects to contribute to a better understanding of the housing price determinants from both nonspatial and spatial perspectives. In addition, this paper fills a gap in the literature on the study of housing prices from a spatial perspective in Latin American cities.
Design/methodology/approach
This study uses a comparative analysis between an ordinary least squares regression and a geographical weighted regression, GWR. The study also assesses the performance of two distinct data sources: the city’s cadastral records and a real estate sales web portal.
Findings
The results suggest that compared to the traditional regression model, the spatial regression models are more effective at capturing housing market variations on a fine scale. Moreover, they reveal interesting findings on the spatial varying, sometimes contradictory effects of some housing attributes on housing prices in different areas of the city, suggesting the potential impact from segregation.
Research limitations/implications
The availability of data on housing prices and characteristics in Latin American cities is fragmented and complex. The level of detail, granularity and coverage is not consistent over time. For this reason, this study combines and compares data sets from official and unofficial sources in an effort to close this gap. Likewise, the socioeconomic variables that come from the census must be carefully analyzed, knowing the historical context in which they were constructed, what they represent and their interpretation.
Practical implications
This paper suggests that despite the improvement on the spatial models, the selection of a specific one should always be based on the diagnosis of it as it highly depends on the data used and the objectives of the study.
Originality/value
This study enriches the limited body of literature on spatial hedonic price models of housing in Latin American cities. It also shed light on the importance of spatial approaches to identify complex housing submarkets.