上海非中心城区住宅用地出让的数学模型及分析

Mathematical Model and Analysis of Residential Land Leasing for Non-center Districts in Shanghai

目前我国房价总体呈上升势态,而土地出让是影响房价的主要因素.通过对上海某些区的规划进行分析并和土地管理局官员进行访谈,本文提出了住宅用地出让数学模型的基本假定,建立了上海非中心城区住宅用地出让的数学模型.基于上海2004–2015年非中心城区的住宅用地出让、地区生产总值(GDP)、区长任期、地铁站、高速公路、大学、重点高中、公园和工业园等数据,并通过ArcGIS得到了每块住宅用地的位置以及地块到市中心、区中心、最近地铁站、最近高速公路出入口、最近大学、最近重点高中、最近公园和最近工业园的距离数据.最终分析出上海非中心城区的区政府出让住宅用地的影响因素,以及这些因素是如何影响住宅用地价格及政府做出住宅用地出让的决定.可以看出,住宅用地面积、容积率、出让方式、是否用于建设安置房,以及住宅用地到市中心、区中心、最近地铁站、最近大学、最近公园和最近工业园的距离等因素对区政府做出住宅用地出让的决定以及住宅用地价格有影响.

At present,the house prices in China are rising,and land leasing is the main factor influencing house prices.Through the interviews with the officials of the departments of planning and land authority of some districts in Shanghai,this paper proposes the basic hypotheses for the mathematical model of residential land leasing,and presents the mathematical model of residential land leasing for non-center districts in Shanghai.Based on the data of residential land leasing,gross domestic product(GDP),tenure of district mayor,subway stations,highways,key high schools,parks and industrial parks of non-center districts in Shanghai from 2004 to 2015,the location of each piece of residential land and the distances of each piece of residential land to the city center,the district center,the nearest subway station,the nearest entrance or exit of highway,the nearest university,the nearest key high school,the nearest park and the nearest industrial park obtained using ArcGIS,the influencing factors of residential land leasing by the district government of non-center districts in Shanghai are analyzed,and how these factors affect residential land prices and decisions on residential land leasing made by the district government is analyzed.It is shown that the factors,such as the residential land area,floor area ratio,modes of leasing,whether the residential land used for resettlement houses,the distances between the residential land and the city center,the district center,the nearest subway,the nearest university,the nearest park and the nearest industrial park,affect the decisions on residential land leasing made by the district government and residential land prices.