The Effect of Proximity to Urban Rail on Housing Prices in Ottawa

Hewitt, Christopher; Hewitt, W W

doi:10.5038/2375-0901.15.4.3

Cited by 28 publications

(25 citation statements)

References 20 publications

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“…Zhang et al [14] examine the capitalization of transit access in Beijing and find that the premium of metro rail transit is 248.31 yuan/m 2 for every 100 m closer to a metro station. Similar results are presented by Hewitt and Hewitt [15], Jun [16], Kim and Lahr [17] and Chatman et al [18]. However, Seo et al [19] claim that proximity to a light rail transit station has both positive (i.e., accessibility to a rail transit station) and negative effects (i.e., air pollution and noise).…”

Section: Introductionsupporting

confidence: 69%

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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: Introductionsupporting

confidence: 69%

“…These researchers' results demonstrate that MRT has the highest premium on housing prices, that LRT has a moderate premium, and that BRT has the lowest premium. Similar studies include Lewis-Workman and Brod [21], Zheng and Liu [22], Zhang et al [23], Zhang [24], Hewitt and Hewitt [15] and Kim and Lahr [17].…”

Section: Micro-level Studies On Housing Pricesmentioning

confidence: 78%

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

et al. 2016

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“…New reports continue to arrive from cases around the world. Examples of recent studies include those by Hewitt and Hewitt (2012) on Ottawa, Pan (2012) on Houston, Ko and Cao (2013), Kim and Lahr (2014) on New Jersey, Hurst and West (2014) on Minneapolis, Dziauddin et al (2014) on Kuala Lumpur, Macfarlane et al (2015) on Atlanta. While the Western study findings are not directly applicable to other countries in practice, the shared experiences are informative and the analytical procedures advanced by the studies are transferrable to different country/city settings.…”

Section: Review Of Related Studiesmentioning

confidence: 97%

Tailoring empirical research on transit access premiums for planning applications

Zhang

2016

Transport Policy

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“…Furthermore, the house value can decrease as a property is located farther away from a station (Hewitt and Hewitt, 2012) or increase because of reduced noise and pollution (Debrezion et al, 2005). Highway accessibility can reduce transportation costs (Forkenbrock, 1990) and generally has a positive effect on housing prices (Levkovich et al, 2016).…”

Section: Hypothesismentioning

confidence: 99%

Housing Price Differences Under the Development of New Towns: Using Taiwan as an Example

Chen

2017

Asian Economic and Financial Review

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Article History JEL Classification G11,R10, R23, R58The purpose of this study is to examine the housing price differences between new towns and old urban areas. In addition, related issues such as spread options, the anchoring effect, and the ripple effect are discussed. By investigating the static spread, dynamic spread, and new town theory, we test seven hypotheses and verify most of these hypotheses. Furthermore, the key causes of the spread are identified: For example, spread options for different residence types depend on risk attitudes; and the ripple effect and anchoring effect of neighboring areas are determined by regional compactness and market transparency. The findings and relevant factors addressed in study can serve as a reference for investment decision making as well as for governments to implement projects of new town development or old urban area revitalization.Contribution/ Originality: The paper's primary contribution is finding that the key factors cause housing prices differences between new towns and old urban areas. It can serve as a reference for investment decision making as well as for governments to implement projects of new town development or old urban area revitalization.

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The Effect of Proximity to Urban Rail on Housing Prices in Ottawa

Abstract: Increasingly, urban rail transit (URT) is seen as a desirable solution for transporta-

Cited by 28 publications

References 20 publications

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

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

Tailoring empirical research on transit access premiums for planning applications

Housing Price Differences Under the Development of New Towns: Using Taiwan as an Example

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