Driving Factors of the Industrial Land Transfer Price Based on a Geographically Weighted Regression Model: Evidence from a Rural Land System Reform Pilot in China
Zhiheng Yang,
Chenxi Li and
Yongheng Fang
Additional contact information
Zhiheng Yang: Institute of Regional Economics, Shandong University of Finance and Economics, Jinan 250014, China
Chenxi Li: School of Public Administration, Xi’an University of Architecture and Technology, Xi’an 710055, China
Yongheng Fang: School of Public Administration, Xi’an University of Architecture and Technology, Xi’an 710055, China
Land, 2020, vol. 9, issue 1, 1-21
Abstract:
More and more studies on land transfer prices have been carried out over time. However, the influencing factors of the industrial land transfer price from the perspective of spatial attributes have rarely been explored. Selecting 25 towns as the basic research unit, based on industrial land transfer data, this paper analyzes the influencing factors of the price distribution of industrial land in Dingzhou City, a rural land system reform pilot in China, by using a geographically weighted regression (GWR) model. Eight evaluation factors were selected from five aspects: economy, population, topography, landform, and resource endowment. The results showed that: (1) Compared with the traditional ordinary least squares (OLS) model, the GWR model revealed the spatial differentiation characteristics of the industrial land transfer price in depth. (2) Factors that have a negative correlation with the industrial land transfer price include the proportion of cultivated land area and distance to the city. Factors that have a positive correlation with the industrial land transfer price include the population growth rate, economic growth rate, population density, and number of hospitals per unit area. (3) The results of GWR model analysis showed that the impact of different factors on the various towns of different models had significant spatial differentiation characteristics. This paper will provide a reference for the sustainable use of industrial land in developing countries.
Keywords: industrial land; price; geographically weighted regression model; driving factors; rural land system reform pilot (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
https://www.mdpi.com/2073-445X/9/1/7/pdf (application/pdf)
https://www.mdpi.com/2073-445X/9/1/7/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:9:y:2020:i:1:p:7-:d:303924
Access Statistics for this article
Land is currently edited by Ms. Carol Ma
More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().