Spatial and time effect of subway on property prices

Trojanek, Radosław; Głuszak, Michał

doi:10.1007/s10901-017-9569-y

Cited by 67 publications

(41 citation statements)

References 38 publications

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“…The explanatory variables of housing prices have been widely discussed in the housing literature. Bangura, Lee and Al-Masum discussed the ability of market fundamentals in explaining housing prices from the macroeconomic perspective [15][16][17], while Trojanek and Yamagata examined the importance of housing attributes in explaining housing prices from the microeconomic perspective [18,19]. In recent years, a great deal of research has studied the impacts of environmental elements on housing price.…”

Section: Introductionmentioning

confidence: 99%

Measuring Impacts of Urban Environmental Elements on Housing Prices Based on Multisource Data—A Case Study of Shanghai, China

Chen

Yao

Zhu

et al. 2020

IJGI

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Diverse urban environmental elements provide health and amenity value for residents. People are willing to pay a premium for a better environment. Thus, it is essential to assess the benefits and values of these environmental elements. However, limited by the interpretability of the machine learning model, existing studies cannot fully excavate the complex nonlinear relationships between housing prices and environmental elements, as well as the spatial variations of impacts of urban environmental elements on housing prices. This study explored the impacts of urban environmental elements on residential housing prices based on multisource data in Shanghai. A SHapley Additive exPlanations (SHAP) method was introduced to explain the impacts of urban environmental elements on housing prices. By combining the ensemble learning model and SHAP, the contributions of environmental characteristics derived from street view data and remote sensing data were computed and mapped. The experimental results show that all the urban environmental characteristics account for 16 percent of housing prices in Shanghai. The relationships between housing prices and two green characteristics (green view index from street view data and urban green coverage rate from remote sensing) are both nonlinear. Shanghai's homebuyers are willing to pay a premium for green only when the green view index or urban green coverage rate are of higher value. However, there are significant differences between the impacts of the green view index and urban green coverage rate on housing prices. The sky view index has a negative influence on housing prices, which is probably because the high-density and high-rise residential area often has better living facilities. Residents in Shanghai are willing to pay a premium for high urban water coverage. The case of Shanghai shows that the proposed framework is practical and efficient. This framework is believed to provide a tool to inform the decisions of housing buyers, property developers and policies concerning land-selling and buying, property development and urban environment improvement.

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Section: Introductionmentioning

confidence: 99%

Measuring Impacts of Urban Environmental Elements on Housing Prices Based on Multisource Data—A Case Study of Shanghai, China

Chen

Yao

Zhu

et al. 2020

IJGI

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“…Structural and locational attributes could have been considered by house buyers as a vital factor in property transactions [17]. Having examined these features, it is justifiable to say that the market value of a property is influenced not only by its direct characteristics (such as the size and shape of a plot, the age of a building, construction type, technical condition [18]), but also factors that involve its broadly defined surroundings [19]. Studies of the determinants of housing prices in developed markets often take into account environmental components [20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

The Impact of Aircraft Noise on Housing Prices in Poznan

et al. 2017

Self Cite

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Abstract:In the paper, we analyzed the impact of aircraft noise on housing prices. We used a dataset containing geo-coded transactions for 1328 apartments and 438 single-family houses in the years 2010 to 2015 in Poznan. In this research, the hedonic method was used in OLS (ordinary least squares), WLS (weighted least squares), SAR (spatial autoregressive model) and SEM (spatial error model) models. We found strong evidence that aircraft noise is negatively linked with housing prices, which is in line with previous studies in other parts of the world. In our research, we managed to distinguish the influence of aircraft noise on different types of housing. The noise depreciation index value we found in our study was 0.87% in the case of single-family houses, and 0.57% regarding apartments. One of the reasons for the difference in the level of impact of aircraft noise may be the fact that the buyers of apartments may be less sensitive to aircraft noise than the buyers of single-family houses.

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“…Higher real estate prices gradually decrease along with further distance from metro stations, which can be quantified. In Warsaw (Poland), an increase in the distance from the metro stations influences a decrease in housing prices by 3% per kilometer (TROJANEK, GLUSZAK 2018). Studies show that the drop of real estate value is related to the accessibility to central business districts.…”

Section: Discussionmentioning

confidence: 99%

Hidden Public Value Identification of Real Estate Management Decisions

Kazak

Simeunović

Hendricks

2019

Real Estate Management and Valuation

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Seeing as how cities nowadays have to face many challenges (such as: urban traffic management, revitalization, and adaptation to climate change.), different kinds of urban policies and actions are undertaken. Many of these actions result in changes that influence real estate, mostly by improving the conditions of public services. However, implementation of such urban policies is connected with significant costs that have to be covered by public funds. Therefore, the question arises how we can analyze the assumed benefits from the increase of real estate value? Which tool could allow stakeholders to search for potential added value? The aim of this paper is to present the methodological approach to improving the communication between stakeholders for the visualization of relations between public actions and potential benefits. The analyses cover benefits that can occur both in public and private budgets. The focal point of this paper is the presentation of causal loop diagrams as a tool that could be incorporated for public value identification on specific investments. The application of the suggested approach is visualized on two examples of urban redevelopment activities. Causal loop diagrams are prepared for the construction of a metro system and implementation of a water retention facility. The results show that both types of urban redevelopment actions have an impact on the creation of value, which can be observed both in public and private benefits. However, not all kinds of activities impact an increase in the market value of real estate and can be measured as incomes in budgets.

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Spatial and time effect of subway on property prices

Cited by 67 publications

References 38 publications

Measuring Impacts of Urban Environmental Elements on Housing Prices Based on Multisource Data—A Case Study of Shanghai, China

Measuring Impacts of Urban Environmental Elements on Housing Prices Based on Multisource Data—A Case Study of Shanghai, China

The Impact of Aircraft Noise on Housing Prices in Poznan

Hidden Public Value Identification of Real Estate Management Decisions

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