When and How Much Did the Green Line LRT Increase Single-Family Housing Values in St. Paul, Minnesota?

Cao, Xinyu; Lou, Shengnan

doi:10.1177/0739456x17707811

Cited by 33 publications

(24 citation statements)

References 36 publications

(52 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ignoring the presence of spatial autocorrelation would lead to biased and inconsistent parameter estimates. The traditional, plain linear regression that cannot tackle spatial effects (e.g., spatial autocorrelation and spatial heterogeneity) is not as acceptable as it used to be in spatial data modeling [49][50][51][52][53].…”

Section: Methodsmentioning

confidence: 99%

Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination

2020

View full text Add to dashboard Cite

Understanding the relationship between tourism demand and retail property prices is of great significance to tourist destinations, especially shopping destinations. The increase in tourism demand may alter the implicit prices of certain retail property characteristics (e.g., age and accessibility to transit). This study examines how tourism demand (measured by tourist volume) affects retail property prices in the tourist precinct of a shopping destination, namely Hong Kong. The implementation of the policy Individual Visit Scheme (IVS) in 2003 in Hong Kong has substantially increased tourist shoppers from Mainland China, and it is used as a quasi-natural experiment of the increased tourist volume. Spatial and non-spatial hedonic pricing models are developed based on the ground-floor retail property transaction data of Causeway Bay, Hong Kong before and after the IVS (1993–2011). The findings of this study are as follows. (1) Accessibility to transit has a larger positive price effect after the implementation of the IVS. (2) The implicit price of accessibility to accommodation facilities is not significantly altered by the implementation of the IVS. (3) Age has a larger negative price effect after the implementation of the IVS. The first two outcomes are related to the economic concerns of tourist shoppers, while the last can be explained by their hometown experience. Finally, practical implications are discussed.

show abstract

Section: Methodsmentioning

confidence: 99%

Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination

2020

View full text Add to dashboard Cite

show abstract

“…Nowadays, there is solid empirical evidence that rail transit can lead to dynamic real estate development (Guthrie and Fan 2013), although this relationship has taken two decades to be fully acknowledged and accepted. Since 2010, studies have increasingly focused on TODs as market responses to transit development, especially on capitalization of transit proximity through land and housing premiums, and modeled and quantified such effects (Cao and Lou 2018;Duncan 2011aDuncan , 2011bGolub, Guhathakurta, and Sollapuram 2012;Higgins and Kanaroglou 2016;Mathur and Ferrell 2009;Park, Huang, and Newman 2016;Zhang et al 2018). Most studies use hedonic price models (see literature review on this topic by Bartholomew and Ewing 2011) with substantial efforts to control for negative externalities such as neighborhood opposition and air pollution, and to account for self-selection.…”

Section: Three "Ds" As Normative Frameworkmentioning

confidence: 99%

A Twenty-Five-Year Biography of the TOD Concept: From Design to Policy, Planning, and Implementation

Jamme

Rodríguez

Bahl

et al. 2019

Journal of Planning Education and Research

View full text Add to dashboard Cite

Promoting a new vision of community—walkable, affordable, environmentally sustainable—the urban design idea of transit-oriented development (TOD) extended the land use and transportation nexus. This review article offers a twenty-five-year retrospective of TOD literature, shaped by disciplinary, policy, and practice predilections. Although the “D” in TOD stands for the encompassing notion of “development,” most literature focused on land development in particular. Meanwhile, sustainable or community development ideas languished, and other Ds such as Density, Diversity, and Design served as an operational framework for outcome-based research. We conclude by urging renewed focus in TOD research on the original goal of developing inclusive and sustainable communities.

show abstract

“…Cervero and Duncan (2002) reported that being near commuter rail stations added commercial land values in a Californian county, and the value of land in the business district and other districts within 0.25 mile of a station was 23% and 120% higher, respectively. Cao and Lou (2018) confirmed that rail accessibility has a positive relationship with singlefamily house prices in St. Paul, the United States. Using a dataset of single-family houses transacted from 2000 to 2018, Zhang et al (2016) quantitatively evaluated the house price effect of urban rail transit using a dataset of 35 cities in China and determined that house prices increase by 2.33% for every 100% increase in rail transit mileage.…”

Section: Transit and House Pricesmentioning

confidence: 68%

Machine learning for inference: using gradient boosting decision tree to assess non-linear effects of bus rapid transit on house prices

et al. 2021

View full text Add to dashboard Cite

The adoption of bus rapid transit (BRT) systems has gained worldwide popularity over the past several decades. China is no exception as it has long been aiming at promoting public transportation. Prior studies have provided extensive evidence that BRT has substantial effects on house prices with traditional econometric techniques, such as hedonic pricing models. However, few of those investigations have discussed the non-linear relationship between BRT and house prices. Using the Xiamen data, this study employs a machine learning technique, namely the gradient boosting decision tree (GBDT), to scrutinize the non-linear relationship between BRT and house prices. This study documents a positive association between accessibility to BRT stations and house prices and a negative association between proximity to the BRT corridor and house prices. Moreover, it suggests a non-linear relationship between BRT and house prices and indicates that GBDT has more substantial predictive power than hedonic pricing models.

show abstract

When and How Much Did the Green Line LRT Increase Single-Family Housing Values in St. Paul, Minnesota?

Cited by 33 publications

References 36 publications

Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination

Impacts of Tourism Demand on Retail Property Prices in a Shopping Destination

A Twenty-Five-Year Biography of the TOD Concept: From Design to Policy, Planning, and Implementation

Machine learning for inference: using gradient boosting decision tree to assess non-linear effects of bus rapid transit on house prices

Contact Info

Product

Resources

About