Hedonic pricing model of assessed and market land values: A case study in Bangkok metropolitan area, Thailand. Issue 1 (March 2020)

• Record Type: Journal Article
• Authors: Malaitham, Sathita; Fukuda, Atsushi; Vichiensan, Varameth; Wasuntarasook, Vasinee
• Is Part Of: Case studies on transport policy. Volume 8:Issue 1(2020)
• Page Start: 153
• Page End: 162
• Publication Date: 2020-03
• Subjects: Assessed land value -- Actual land value -- Hedonic study -- Spatial effect -- Developing countries; Transportation and state -- Case studies -- Periodicals; Transportation -- Planning -- Case studies -- Periodicals; Transportation -- Research -- Case studies -- Periodicals; 388.05
• DOI: 10.1016/j.cstp.2018.09.008
• Languages: English
• ISSNs: 2213-624X

Abstract

Highlights: Market value of land lots within 1.5 km of stations are expensive nearly 3 times higher than the assessor's database. Spatial non-stationarity exists in the given area. Contour map reveals the spatial variations vary substantially. A short walk to stations can significantly add worth to the land value. Abstract: Bangkok Metropolitan Area, the capital of Thailand, is known as one of the world's most traffic-congested cities. Lots of transport-related projects to alleviate traffic congestion especially rapid transit system always require an amount of land. Therefore, several privately owned lands have to be acquired by the government agencies due to the lack of available spaces in an urban area. However, the assessment of compensation for a compulsory land acquisition is determined on the basis of the assessor's database that often values each of properties lower than expected. In this paper, the assessed prices data and the offering prices for sale data of Bangkok are analyzed with the use of regression framework through the hedonic pricing model. The spatial non-stationarity to examine the variations of the implicit effects to property value is also included bases on the geographically weighted regression (GWR) technique. The results show that the determinants of property value are myriad and varied over space, i.e. spatial non-stationarity exists in the study area. The obtained results indicate that the difference between two data is extremely large. These results provide the basic information to compute the fair compensation for the landowners and allow the government agencies to tax the direct beneficiaries of their investments in advance so as to finance infrastructure projects.