基于特征价格模型的郑州市住宅价值评估研究

发布时间：2018-05-31 00:41

本文选题：郑州市 + 住宅房产　；参考：《石河子大学》2017年硕士论文

【摘要】：改革开放以来我国房地产行业快速发展,不仅是一线大都市房价居高不下,二线城市和三线城市的房产市场也是异常火爆。2016年我国房地产市场的主格调是去库存,央行多次降息来撬动房地产市场,消化已建的房产。郑州市在这场房价的涨潮中异常活跃,从2015年10月开始房价一直处于上升状态,截止到2016年12月份房价总体上升4.11%,在全国各市中上涨幅度排名第五,二手房交易量75243套,成交面积699.56万平方米。面对如此巨大的房产交易量,传统的单项资产评估方法很难满足需求,再加上呼之欲出的房产税,将会使房产评估趋于常态化,定期评估缴税将会带动更大的评估需求。本文所研究的特征价格模型是针对批量评估的一种方法,通过构建房产特征变量与房产价格之间的方程可以批量化的评估,待评估房产基本信息输入特征模型即可得到需要评估房产的价格。特征价格模型是以计量经济学为基础,不仅可以提高评估的效率,而且可以提高评估的准确性,它克服了传统评估的主观性。但目前学者对特征价格模型的研究主要集中在一线大城市,对二三线中型城市研究较少。本文以郑州市为例研究特征价格模型对二三线城市的适用性,并分析影响郑州市住宅房产价格的主要因素。本文首先分析了郑州市住宅房地产市场的现状,并通过查阅文献实地调研等方式初步确定影响郑州市住宅房地产价格的因素,然后运用特征分析法将初步确定的特征因素分类、整理、量化。文章主要通过线性回归的方式将房产价格作为因变量,将影响房产价格的特征因素作为自变量进行回归分析,建立特征因素与房产价格之间的函数关系。在分析了郑州市住宅分布以后,笔者一共抽取郑州市100个小区,700套房产信息进行回归分析。文中共采用了三种函数形式建立回归模型,通过比较三种函数模型的检验值,确定适合郑州市具体情况的函数方程即要建立的特征价格模型。为实际检验所建特征价格模型的适用性,笔者抽取50套住宅信息带入模型评估出价格与房产真实价格作对比,以验证模型的准确性。通过对特征方程的分析得出影响郑州市住宅房产价格的主要因素,并系统的总结在运用这一方法时所要注意事项。本文以郑州市为例对特征价格模型进行研究得出如下相关结论,第一,特征价格估价法不仅可以用于一线城市的房产估价,对二三线城市也有较强的适用性。第二,最终确定了三种函数形式中对数函数模型拟合度最好,解释效果,可以作为房产评估的特征方程。第三,本文通过回归分析建立了郑州市房产价格分析体系,最终确定了距离商圈的距离、文体设施、学区房、临近公园绿地、楼层、朝向、教育设施配套、临近大学为影响房价的关键因素。同时文中为房产评估机构提供新的评估方法以及此方法在评估应用中的一些建议。
[Abstract]:Since the reform and opening up, the real estate industry in China has developed rapidly, not only the housing prices in first-tier cities remain high, but also the real estate markets in second-tier cities and third-tier cities are extremely hot. The main theme of the real estate market in China in 2016 is to go to inventory. The central bank has repeatedly cut interest rates to leverage the real estate market, digesting already built real estate. Zhengzhou has been extremely active in this upsurge in house prices, which has been on the rise since October 2015. By December 2016, house prices had risen by 4.11 overall, ranking fifth in all cities in the country, with 75243 second-hand housing transactions. The transaction area is 6.9956 million square meters. In the face of such a huge real estate transaction volume, the traditional method of single asset evaluation is difficult to meet the demand. In addition, the property tax will make the property evaluation become more and more regular, and the periodic assessment tax will lead to greater assessment needs. The characteristic price model studied in this paper is a method for batch evaluation, which can be evaluated in batches by constructing the equation between the real estate characteristic variables and the real estate price. The price of the property needed to be evaluated can be obtained by the input feature model of the basic information of the property to be evaluated. The characteristic price model is based on econometrics, which can not only improve the efficiency of evaluation, but also improve the accuracy of evaluation. It overcomes the subjectivity of traditional evaluation. But at present, the research on the characteristic price model is mainly focused on the first tier cities, and few on the second and third line medium-sized cities. This paper takes Zhengzhou as an example to study the applicability of the characteristic price model to the second and third tier cities, and analyzes the main factors affecting the real estate prices in Zhengzhou. This paper first analyzes the present situation of Zhengzhou residential real estate market, and preliminarily determines the factors that affect the price of Zhengzhou residential real estate by consulting the literature on the spot, and then classifies the initially determined characteristic factors by means of characteristic analysis. Sort, quantify. In this paper, the property price is regarded as the dependent variable by linear regression, and the characteristic factors which affect the real estate price are taken as independent variables to make regression analysis, and the functional relationship between the characteristic factors and the real estate price is established. After analyzing the residential distribution in Zhengzhou, the author extracts 700 sets of real estate information from 100 residential areas in Zhengzhou for regression analysis. In this paper, regression models are established in three functional forms. By comparing the test values of the three functional models, the characteristic price model, which is suitable for the specific conditions of Zhengzhou City, is determined. In order to verify the applicability of the characteristic price model, the author takes 50 sets of housing information into the model to evaluate the price and the real estate price, so as to verify the accuracy of the model. Through the analysis of the characteristic equation, the main factors influencing the real estate price in Zhengzhou are obtained, and the matters needing attention in the application of this method are systematically summarized. This paper takes Zhengzhou as an example to study the characteristic price model and draws the following conclusions: first, the method of feature price valuation can not only be used in the property evaluation of first-tier cities, but also has a strong applicability to the second-third-tier cities. Secondly, it is determined that the logarithmic function model is the best in the three function forms, which can be used as the characteristic equation of real estate evaluation. Thirdly, this paper establishes the real estate price analysis system of Zhengzhou by regression analysis, and finally determines the distance from the commercial area, cultural and cultural facilities, school district house, adjacent park green space, floor, orientation, and educational facilities. Nearby universities are key factors affecting housing prices. At the same time, this paper provides a new evaluation method for the real estate appraisal organization and some suggestions in the application of this method.
【学位授予单位】：石河子大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F299.23

【参考文献】