[论文解读] The Association Between SOC and Land Prices Considering Spatial Heterogeneity Based on Finite Mixture Modeling

Woo Seok Kang, Eunchan Kim+1 more|arXiv (Cornell University)|Nov 15, 2022

Housing Market and Economics被引用 29

一句话总结

论文使用有限混合建模揭示 SOC 与土地价格之间关系的空间异质性，识别出四个具有不同 SOC–人口统计–土地价格关联的簇。

ABSTRACT

An understanding of how Social Overhead Capital (SOC) is associated with the land value of the local community is important for effective urban planning. However, even within a district, there are multiple sections used for different purposes; the term for this is spatial heterogeneity. The spatial heterogeneity issue has to be considered when attempting to comprehend land prices. If there is spatial heterogeneity within a district, land prices can be managed by adopting the spatial clustering method. In this study, spatial attributes including SOC, socio-demographic features, and spatial information in a specific district are analyzed with Finite Mixture Modeling (FMM) in order to find (a) the optimal number of clusters and (b) the association among SOCs, socio-demographic features, and land prices. FMM is a tool used to find clusters and the attributes' coefficients simultaneously. Using the FMM method, the results show that four clusters exist in one district and the four clusters have different associations among SOCs, demographic features, and land prices. Policymakers and managerial administration need to look for information to make policy about land prices. The current study finds the consideration of closeness to SOC to be a significant factor on land prices and suggests the potential policy direction related to SOC.

研究动机与目标

• 了解社会基础设施（SOC）如何在空间异质性下与本地土地价格相关。
• 使用有限混合建模（FMM）识别具有显著 SOC–人口统计–土地价格关系的空间簇。
• 确定簇的最佳数量并解释在每个簇中 SOC 近邻如何影响土地价值。
• 在考虑 SOC 近邻与空间异质性的情况下为土地价格管理提供政策指导。

提出的方法

• 应用有限混合建模以同时识别簇并估计协变量效应。
• 将 SOC、社会人口特征和空间信息作为预测变量纳入。
• 确定最佳簇数量（经发现为四个）并估计簇特定系数。
• 分析在各簇中 SOC、人口特征与土地价格之间的不同关联。

实验结果

研究问题

• RQ1 在考虑 SOC 与土地价格的情况下，区域内的最优空间簇数量是多少？
• RQ2 在每个识别出的簇中，SOC、人口特征与土地价格如何相关？
• RQ3 在考虑空间异质性时，近邻 SOC 是否显著影响土地价格？
• RQ4 簇特定的 SOC–土地价格关系会带来哪些政策方向？

主要发现

• 区域内存在四个簇，每个簇与 SOC–土地价格的关联不同。
• 簇特定系数显示在不同簇中 SOC、人口统计与土地价格之间的关系各异。
• 近邻 SOC 被识别为影响土地价格的显著因素。
• 空间异质性影响 SOC 与土地价格之间的关系，提示有针对性的政策含义。