Hedonic dataset of the metropolitan housing market—cases in South Korea

This dataset was generated for analyzing the economic impacts of subway networks on housing prices in metropolitan areas. The provision of transit networks and accompanying improvement in accessibility induce various impacts and we focused on the economic impacts realized through housing prices. As a proxy of housing price, we consider the price of condominiums, the dominant housing type in South Korea. Although our focus is transit accessibility and housing prices, the presented dataset is applicable to other studies. In particular, it provides a wide range of variables closely related to housing price, including housing properties, local amenities, local demographic characteristics, and control variables for the seasonality. Many of these variables were scientifically generated by our research team. Various distance variables were constructed in a geographic information system environment based on public data and they are useful not only for exploring environmental impacts on housing prices, but also for other statistical analyses in regard to real estate and social science research. The four metropolitan areas covered by the data—Busan, Daegu, Daejeon, and Gwangju—are independent of the transit systems of Greater Seoul, providing accurate information on the metropolitan structure separate from the capital city.

本数据集专为分析大都市区地铁网络对住房价格的经济影响而构建。交通网络的铺设与随之而来的可达性提升会带来多维度影响，本研究聚焦于通过住房价格体现的经济影响。作为住房价格的代理变量，我们选取韩国主流住宅类型——公寓（condominium）的交易价格作为观测指标。尽管本研究的核心聚焦于交通可达性与住房价格的关联，但本数据集亦可应用于其他相关研究场景。尤为值得一提的是，数据集涵盖了与住房价格紧密相关的多类变量，包括住房属性、本地生活配套设施、本地人口统计特征以及季节性控制变量。上述多数变量均由本研究团队通过科学方法生成。各类距离变量均基于公开数据在地理信息系统（Geographic Information System, GIS）环境中构建而成，其不仅可用于探究环境因素对住房价格的影响，亦可应用于房地产与社会科学研究领域的其他统计分析。本数据集覆盖的四大韩国大都市区——釜山（Busan）、大邱（Daegu）、大田（Daejeon）及光州（Gwangju）——均独立于首尔都会区的交通系统，能够提供脱离首都圈的精准大都市区结构相关信息。