Does high-speed rail accessibility influence residential property prices? Hedonic estimates from southern Taiwan

Andersson, David Emanuel; Shyr, Oliver Feng-Yeu; Fu, Chiang

doi:10.1016/j.jtrangeo.2008.10.012

Cited by 156 publications

(82 citation statements)

References 16 publications

(16 reference statements)

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“…Previous studies have focused on relationships between urban transit systems and housing prices (e.g., between housing prices and high speed railway systems [20], road and rail systems [20], rail accessibility levels [46][47][48], and highway and light rail accessibility levels [49]. However, nearly all of the studies presented above are case studies.…”

Section: Discussionmentioning

confidence: 99%

“…For the literature on transportation, some studies assess the effects of subway, light rail transit and other transportation facilities on housing prices. For example, Andersson et al [20] assess the implicit housing price of a new high-speed railway line (HSR) that connects seven metropolitan areas in Taiwan using a hedonic price function. Their results show that HSR accessibility has at most a minor effect on house prices.…”

Section: Micro-level Studies On Housing Pricesmentioning

confidence: 99%

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Do Urban Rail Transit Facilities Affect Housing Prices? Evidence from China

et al. 2016

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Urban rail transit facilities play a critical role in citizen's social activities (e.g., residence, work and education). Using panel data on housing prices and urban rail transit facilities for 35 Chinese cities for 2002 to 2013, this study constructs a panel data model to evaluate the effect of rail transit facilities on housing prices quantitatively. A correlation test reveals significant correlations between housing prices and rail transit facilities. Empirical results demonstrate that rail transit facilities can markedly elevate real estate prices. Quantitatively, a 1% increase in rail transit mileage improves housing prices by 0.0233%. The results highlight the importance of other factors (e.g., per capita GDP, land price, investment in real estate and population density) in determining housing prices. We also assess the effects of expectations of new rail transit lines on housing prices, and the results show that expectation effects are insignificant. These findings encourage Chinese policy makers to take rail transit facilities into account in achieving sustainable development of real estate markets.

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Section: Discussionmentioning

confidence: 99%

Section: Micro-level Studies On Housing Pricesmentioning

confidence: 99%

Do Urban Rail Transit Facilities Affect Housing Prices? Evidence from China

et al. 2016

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“…Senior (2009) found that Metrolink had no effect on house prices in Greater Manchester (Forrest et al, 1996), however, Ovenell (2007) was later able to identify a positive effect on the prices of properties located between 0.5 and 1 km from the Metrolink stations. Andersson et al (2010) studied the effects of accessibility to high speed rail in Taiwan and discovered that overall it had a very minor effect on property prices. This clearly contrasts with the results of Debrezion et al (2006) in Holland, where the effects of proximity to a railways station were more than double those found in Taiwan.…”

Section: Bibliographic Reviewmentioning

confidence: 99%

Modelling transport and real-estate values interactions in urban systems

Ibeas

Cordera

dell’Olio

et al. 2012

Journal of Transport Geography

115

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a b s t r a c tThis article presents hedonic Multiple Linear Regression models (MLR), spatial autoregressive hedonic models (SAR), Spatial autoregressive hedonic in the Error term Models (SEMs) and spatial Durbin hedonic models (SDMs) to estimate house price variations in metropolitan areas as a result of changing environmental and accessibility conditions. The goodness of fit of the different models has been compared along with a series of hypotheses about the performance of the specifications considering spatial relationships between observations. The case study for such analysis was the urban area of Santander (Spain). The models which considered spatial dependence between observations offered a greater degree of fit in a scenario showing strong spatial correlation in MLR residuals. The SEM model combined with a QueenContiguity matrix provided a good fit to the data and at the same time presented significant parameters with theoretically coherent signs. This model estimated increases of 1.8% for each additional transit line present in the areas of housing, as well as a reduction of 1.1% in their prices for each additional minute in travelling time to the Central Business District. Closeness to the train stations, however, implied reductions in house prices.

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“…However, in Taiwan, the Box-Cox hedonic pricing model suggests that accessibility to high speed rail has a minor impact on property prices [5]. Several Superfund sites in the United States have demonstrated the expected impact-Superfund sites negatively impact property values [6].…”

Section: Factors Affecting Property Pricesmentioning

confidence: 99%

Have Housing Prices Gone with the Smelly Wind? Big Data Analysis on Landfill in Hong Kong

2018

Sustainability

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Unlike many other places around the globe, Hong Kong is a small city with a high population density. Some housing units are built near the sources of an externality, such as a landfill site. As the blocks of buildings are particularly tall, many are walled buildings that block the bad odor from the landfill. Thus, the wind blowing from a landfill site may not affect the entire building estate. Some buildings are more heavily affected than others, partly because walled buildings built near landfills are rare. Only a few studies currently examine the correlation between wind direction and the prices of walled buildings. In this paper, we aim to bridge this research gap by illustrating Hong Kong as a case study. Most previous research studies only examine a few factors affecting housing prices. Modern big data is characterized by its large volume of data, which includes various types of data that analysts would not necessarily sample, but instead merely observe to track what happens. Therefore, another innovative point of our paper, is that we adopt a big data approach to study this issue. In this aspect, this paper is the first of its kind. There are 53,071 observations in the 1999 to 2014 dataset, with 2,175,911 data entries. Our results reflect that when more municipal solid waste is sent to the South East New Territories Landfill, residents' complaints in Tseung Kwan O increase. However, entire property prices in the region also increase, which rejects our hypothesis. We speculate that as more people become aware of the housing estate due to complaints, with only a limited number of housing units affected by the smell, since the wind usually only blows in certain directions, the "advertisement effect" originating from complaints about the bad smell boosts the property prices of the unaffected units. That is, people become aware of the existence of the property, visit the site, and discover that only specific units facing one particular direction are affected. Then, they purchase units that are unaffected by the smelly wind, leading to an overall increase in property prices. The study's results may provide a new perspective on urban planning, and possible implications for other cities in view of the constant increase in population and expansion of landfill sites.

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Does high-speed rail accessibility influence residential property prices? Hedonic estimates from southern Taiwan

Cited by 156 publications

References 16 publications

Do Urban Rail Transit Facilities Affect Housing Prices? Evidence from China

Do Urban Rail Transit Facilities Affect Housing Prices? Evidence from China

Modelling transport and real-estate values interactions in urban systems

Have Housing Prices Gone with the Smelly Wind? Big Data Analysis on Landfill in Hong Kong

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