一种新的利用网络爬虫技术的土地价格指数编制方法

研究目标：目前有关中国土地价格指数的研究没有考虑不可观测特征的影响，本文给出一种可以控制不可观测特征的土地价格指数编制方法。HTH]研究方法：通过结合传统的特征价格模型和重复交易模型，提出固定地理单元并利用组内差分以控制地块不可观测特征，提出了一种新的土地价格指数编制方法。HTH]研究发现：HTF]STBZ]WTBZ]以上海为例讨论了分类土地价格指数，研究发现从2008~2015年，上海同质住宅用地价格上升了359.92%，同质工业用地和商服用地价格的涨幅分别为101%和107%。HTH]研究创新：利用网络爬虫技术收集微观土地交易数据，为指数的编制提供了数据基础。HTH]研究价值：该方法能够捕捉地块所在的特殊位置对于其价格的影响。

A New Land Price Index Model Based on Web Crawler

Research Objectives: The current results about Chinese land price index can''t capture the effects of unobserved variables on land price, and the aim of this paper is to fix the problem. Research Methods: By combining the traditional hedonic model and repeated sales model, our paper proposes a new land price index method that controls unobserved variables by fixed geography unit and within group difference. Research Findings: The land price index of Shanghai is calculated as an example, The index shows the price of constant-quality residential land rises by 359.92% from 2008 to 2015, and the total increase of constant-quality industry and commercial land price is 101% and 107%. Research Innovations: The land parcel transaction data is collected by web crawler, which offers a rich information for the calculation of land price index. Research Value: The result also shows our index model can capture the effect of land special location on price.