Spatial variation of the determinants affecting urban land value in Thiruvananthapuram, India

B.V. Binoy, M.A. Naseer and P.P. Anil Kumar

International Journal of Housing Markets and Analysis, 2022, vol. 17, issue 3, 611-656

Abstract: Purpose - Land value varies at a micro level depending on the location’s economic, geographical and political determinants. The purpose of this study is to present a comprehensive assessment of the determinants affecting land value in the Indian city of Thiruvananthapuram in the state of Kerala. Design/methodology/approach - The global influence of the identified 20 explanatory variables on land value is measured using the traditional hedonic price modeling approach. The localized spatial variations of the influencing parameters are examined using the non-parametric regression method, geographically weighted regression. This study used advertised land value prices collected from Web sources and screened through field surveys. Findings - Global regression results indicate that access to transportation facilities, commercial establishments, crime sources, wetland classification and disaster history has the strongest influence on land value in the study area. Local regression results demonstrate that the factors influencing land value are not stationary in the study area. Most variables have a different influence in Kazhakootam and the residential areas than in the central business district region. Originality/value - This study confirms findings from previous studies and provides additional evidence in the spatial dynamics of land value creation. It is to be noted that advanced modeling approaches used in the research have not received much attention in Indian property valuation studies. The outcomes of this study have important implications for the property value fixation of urban Kerala. The regional variation of land value within an urban agglomeration shows the need for a localized method for land value calculation.

Keywords: Hedonic price modeling; GIS (Geographic information system); Geographically weighted regression; Real estate; Local regression; Statistical modeling (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijhmap:ijhma-09-2022-0135

DOI: 10.1108/IJHMA-09-2022-0135

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