https://doi.org/10.5392/JKCA.2020.20.06.717 중공업 오염원이 부동산 가격에 대한 미치는 영향 중국 마안산시 중심으로 The Impacts of Heavy Industrial Pollution Sources on The Real Estate Price Evidence from Maanshan City, China 왕윤동, 장쯔신, 황수 건국대학교 부동산대학원 Rundong Wang([email protected]), Zhixin Zhang([email protected]) Shuai Huang([email protected]) 요약 현대사회의 환경오염 문제는 공업화에 따라 급격하게 변화하고 있기 때문에, 환경오염 문제는 다양한 분야 에 직간접적인 영향을 미치고 있다. 특히 중공업 오염원은 입지 선택과 부동산 가치에 주요한 변수로 작용될 수 있다. 따라서 본 연구에서는 중국의 대표적인 철강 도시인 마안산시에 있는13개 아파트 단지의 거래 데이 터에 기반하고 헤도닉 가격 모형 (HedonicPrice Model)을 이용해서 환경오염 중에 중공업 오염을 중심으로 부동산 가격에 대해서 미친 영향을 연구했고 결론을 내렸다. 연구 결과는 주택에서 오염원의 거리가 멀어 질수 록 주택 가격에 인상 효과가 있다. ■ 중심어 :∣중공업 오염∣헤도닉 가격모형∣주택가격∣중국∣ Abstract As the environmental pollution problem in modern society is rapidly changing with industrialization, the environmental pollution problem has a direct or indirect effect on various fields. In particular, heavy industry pollutants can be a significant variable in site selection and realestate value. Therefore, this study is based on transaction data of 13apartment complexes in Maanshan City, a representative steel city in China, and uses the Hedonic Price Model to study the effect on real estate prices, mainly on heavy industry pollution during environmental pollution. The conclusion shows that the farther away from the source of pollution, the higher values are. ■ keyword :∣Heavy Industry Pollution∣Hedonic Price Model∣Housing Price∣China∣ I. Introduction modernization has developed rapidly, which promoted the rapid growth of economic while 1. Background and Objectives resulted in serious environmental pollution. With accession to the World Trade Among the pollution problems, air pollution has Organization (WTO), China's industrial the greatest impact on human beings[1]. Clean 접수일자 : 2020년 05월 11일 심사완료일 : 2020년 06월 08일 수정일자 : 2020년 06월 02일 교신저자 : 황수, e-mail : [email protected] 718 한국콘텐츠학회논문지 '20 Vol. 20 No. 6 air once became a scarce resource in some areas. The impact of air pollution on the living environment has also become a widespread concern of scholars. Based on the data of Beijing urban area in 2000, Zheng found that for every 10ug/m³ of PM2.5 increased, the gap of housing price will increase by 150 yuan. Good air quality can raise housing prices Figure 1. The Location of Maanshan City because people want a better living environment[2]. The red part in [Figure 1] is Maanshan city. During the period of rapid industrialization in the 1950s and 1960s, China's heavy industries were built in relatively concentrated areas for Ⅱ. Literature Review efficiency[3]. Maanshan city is one of the old heavy industrial bases. The environment Environmental risk increasingly affected pollution caused by heavy industry is serious people's lives. Frequent environmental risk due to the high amount of pollutants and the incidents have gradually triggered public panic high toxicity of contaminants released from and resistance to environmental hazards, which heavy industry factories. has led to the "Not in My Backyard" (NIMBY) effect[6]. (Rong and Xie, 2015). Under the 2. Research Area influence of NIMBY, people tend to choose a location away from the source of pollution[7]. The data in this research is from Maanshan Some previous studies have discussed the city, Anhui province, China. Maanshan city is a impact of the environment on housing prices. steel-industry-based city. In 2018, the average Henderson（1995）studied how air pollution per capita GDP achieved 11246 dollars. The affects the Boston housing, which discovered average economic growth was at the top of the that high-income residents are more concerned whole province. Heavy industry accounts for about the environment surrounding their 91% of the entire industrial sector. The steel house[8]. Kim (2019) used 11498 sales of and ironworks are the symbols of Maanshan apartments in Busan Korean, found that city. The local finance contribution from this environmental improvement will increase industry accounts for 70% to 80% in its total housing prices[9]. Hanna (2006) used Toxic local fiscal revenue[4]. The steel manufacturing Release Inventory (TRI) and census data from industry led by Ma Steel Group and the related the 1980s for the six New England states, found sectors has brought substantial economic that communities exposed to high levels of income to Maanshan city[5]. But it has also pollution will have lower housing prices[10]. brought severe pollution to the environment. In China, Chen（2017）used PM2.5 air quality data form 286 county-level cities found that air pollution has a significant negative impact on housing prices[11]. Zhao (2018) used a panel 중공업 오염원이 부동산 가격에 대한 미치는 영향 중국 마안산시 중심으로 719 regression quantile method to analysis 35 large Ⅲ. Empirical Results and medium-sized cities in China, found that improvement of air quality has a positive effect 1. Data on housing prices[12]. Xiao (2019) used Maanshan city includes three districts and landscape data to find that Landscape three counties[16]. In this research, we chose proximity influences the impact of floor level the Huashan district and Yushan district as the on housing price significantly[13]. Chen (2020) primary research areas because there are more found that environmental pollution is a commercial property here than other districts. significant threat to the health of Chinese we visited each local property developer and residents and has caused substantial economic collected the data. finally, we collected 13 new losses[14]. For every 10% increase in apartment transaction data. The transaction environmental pollution, local housing prices time is from 2014-2016 but we collected the will fall by 1.12%. The decline in housing price data in 2017. All missing observations were leads to a decrease in total social wealth. Dai excluded from the sample data, and the (2020) used the hedonic price model to resulting unabridged sample is 6,698. The investigate the impact of environmental risk on address and opening date of each project can housing price in Nanjing China and showed be obtained from the author. that the higher ecological risks of chemical enterprises were associated with lower housing prices[15]. However, these studies have certain limitations in terms of research objects and perspectives. Compared with previous studies, this paper used survey data. Which means we collected the data directly. As well known, there is not a Figure 2. The Location of complete real estate registration system in Real Estate Projects and China. It is difficult to obtain data for a Factories particular property. We choose Maanshan city to study with the aim to find the impact of 2. Description of Variables environmental pollution on housing prices Butler (1982) pointed out that the hedonic more clearly. Because Maanshan city is one of price model should only include factors that the top ten iron and steel cities in China. There affect housing prices[17]. In this paper, the are many iron and steel factories and related dependent variable is the total price of housing. factories. The number of factories per square The distance to the pollution source is our meter is higher than in other general regions. In interest variables. According to previous studies, other words, all of these factories are massive other explanatory variables divided into three industry factories, which could bring more parts location, structure and neighbourhood effective results about the impact of the variables. Dai (2020). research environment on housing prices. 720 한국콘텐츠학회논문지 '20 Vol. 20 No. 6 2.1 Locational Characteristics can lead to substantive errors when assessing (Dubin & Sung 1990). Found that Locational individual properties and the market[23], in attributes are quantified through surrogate general, was validated by Linneman (1980). measures such as socioeconomic class, racial In this paper, we force the local government composition, aesthetic qualities, pollution services. The quality of public schools was levels, and proximity to local amenities. found to have a significant impact on real Transport accessibility is frequently associated house prices. School quality is more important with the ease of commuting to and from to residents than either crime[27][28]. facilities and is measured by travelling time, Therefore, in order to find the exact convenience[18]. So, at this part, we choose the relationship between housing prices and distance to the central hospital, city centre, and environment pollution, we need to control this high-speed railway station to depict the part in our model. So, we choose the distance locational of housing. to the nearest critical high middle, ordinary high middle school, critical junior school and 2.2 Structural Characteristics total bus routes which pass by the building project as the neighbourhood attributes control As Ball (1973) pointed out, if a house had variables. more desirable attributes than others did, the Baidu maps were used to estimate the valuation of these attributes would be reflected distances from each commercial property to in higher market prices for the house[19]. each factory. Chau (2003) said the single most crucial Residential architectural features are structural variable is the floor area[20]. Fletcher measured by using the residential actual et al. (2000) found that the number of rooms real-world data. The air quality data were and bedrooms are positively related to the sale obtained from the ministry of ecology and price of houses[21]. And the number of environment of China. bathrooms[22][23], the floor area[24][25] has a The air quality data measured a month before related to the housing prices too. Due to this the residential real estate sale, the number of reason, we choose the housing area, floor and days achieving better air quality days in a the number of bedrooms, living room, month, the number of days achieving light bathroom and elevators as the variables to pollution in a month, and the number of days depict the structural attributes.