Study on the Parameter Estimation Methods for Location Model based on Spatial General Equilirbium

基于空间一般均衡的位置模型参数估计方法研究

• 批准号: 08455235
• 负责人: SHIMIZU Eihan
• 金额: $ 1.92万
• 依托单位: University of Tokyo
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (B)
• 财政年份: 1996
• 资助国家: 日本
• 起止时间: 1996 至 无数据
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-08455235/
• 关键词: location model; spatial econometrics; parameter estimation; multicollinearity; spatial autocorrelation; 一般均衡; 空間相互作用; 混合方程式

In order to evaluate the economic impacts of sets of interdependent major interregional infrastructure investment, such as transportation projects, location models based on Spatial Computable General Equilibrium (SCGE) models have been developed. One important issue remaining is the parameter estimation. Although Ordinary Least Squares Method (OLS) is widely used, it is not enough to estimate parameters of these location models. Aside from the problem caused by the simultaneous equations system, multicolinearity, spatial autocorrelation, spatial heteroscedasticity are also difficult ones. The purpose of this study is to describe these issues and methods for parameter estimation of the models. Firstly, we reviewed counter-measures for them, especially multicollinearity, and spatial autocorrelation and we described the theoretical relationships among them. Subsequently, we applied these methods to a land price model and location-choice model which are typical models for economic analysis of infrastructure planning and are also sub-models of the location model based on SCGE.We also did a practical comparison of them. This developed a kind of manual which provides a deeper understanding of regional modeling.

为了评估相互依存的主要区域基础设施投资集的经济影响，例如运输项目，基于空间可计算的一般平衡（SCGE）模型的位置模型已经开发出来。剩下的一个重要问题是参数估计。尽管普通最小二乘法（OLS）被广泛使用，但不足以估算这些位置模型的参数。除了同时方程式系统引起的问题外，多连续性，空间自相关，空间异质性也很困难。这项研究的目的是描述这些问题和方法的参数估计。首先，我们审查了它们的相反测量，尤其是多重共线性和空间自相关，并描述了它们之间的理论关系。随后，我们将这些方法应用于土地价格模型和位置选择模型，该模型是基础设施计划经济分析的典型模型，也是基于SCGE的位置模型的子模型。我们还对它们进行了实际比较。这开发了一种手册，可深入了解区域建模。