Mi Diao

Residential Property Values and the Built Environment: Empirical Study in the Boston, Massachusetts, Metropolitan Area

By taking advantage of two recent data sets with exceptional spatial detail, this research is a comprehensive and spatially disaggregate study of the relationship between the built environment and residential property values in the Boston, Massachusetts, metropolitan area. The study computes 27 built environment variables at a 250 m × 250 m grid cell level, uses factor analysis to extract five built environment factors to mitigate multicollinearity, and integrates built environment factors into hedonic price models. Spatial regression techniques are applied to correct spatial autocorrelation. Residential property values are found to be positively associated with accessibility to transit and jobs, connectivity, and walkability and negatively related to auto dominance. Built environment effects depend on neighborhood characteristics.

Selectivity, Spatial Autocorrelation, and the Valuation of Transit Accessibility

Capturing the increase in land value attributable to transit accessibility has become an increasingly examined alternative to fund the transit system, one which demands reliable estimates of the impact of transport improvement on property values. In the context of value capture, this study presents a new method to value transit accessibility. We integrate the Heckman selection model and spatial econometric techniques to account for two issues that are often overlooked in the conventional hedonic price analysis: sample selection and spatial autocorrelation. The modelling framework is applied to the city of Boston to assess the impact of the subway system on single-family property values and gauge the potential for value capture. We find that failing to correct for sample selection and spatial autocorrelation results in significant bias in valuing transit accessibility. This bias might distort estimates of the value-added effect of transit infrastructure investment and misguide policy design for value-capture programmes.

Inferring individual daily activities from mobile phone traces: A Boston example

Understanding individual daily activity patterns is essential for travel demand management and urban planning. This research introduces a new method to infer individuals’ activities from their mobile phone traces. Using Metro Boston as an example, we develop an activity detection model with travel diary surveys to reveal the common laws governing individuals’ activity participation, and apply the modeling results to mobile phone traces to extract the embedded activity information. The proposed approach enables us to spatially and temporally quantify, visualize, and examine urban activity landscapes in a metropolitan area and provides real-time decision support for the city. This study also demonstrates the potential value of combining new “big data” such as mobile phone traces and traditional travel surveys to improve transportation planning and urban planning and management.

Intra-city access to inter-city transport nodes: The implications of high-speed-rail station locations for the urban development of Chinese cities

In the high-speed-rail (HSR) construction boom of China, although some cities have upgraded old train stations in inner cities to be compatible with HSR, more cities have built new HSR stations on undeveloped land in the urban periphery. This study investigates the impact of intra-city access to inter-city transport nodes and explores the implications of HSR station locations for the accessibility and residential property values in Chinese cities connected by bullet trains. We find that for the cities with HSR stations in suburbs, the gains in inter-city travel brought by HSR are largely offset by the prolonged intra-city travel time to reach the stations, thus limiting frequent usage of HSR for daily commuting. The inner-city HSR station in Hangzhou shows a positive impact on residential property value in the vicinity, while the suburban HSR station in Guangzhou has not been observed to raise the residential property values noticeably in the short term despite the government’s intention to stimulate development in surrounding areas. The research findings show the need for better connections of HSR stations with the city to magnify the accessibility provided by HSR and careful integrated planning to promote desirable urban development outcomes in station areas.

Negative Externalities of Rail Noise and Housing Values: Evidence from the Cessation of Railway Operations in Singapore: Negative Externalities of Rail Noise and Housing Values

The governments of Malaysia and Singapore reached a landmark agreement in May 2010 to end the operations of nearly 80‐year‐old railway lines and stations in Singapore. In our study, the cessation of the railway services operated by Keretapi Tanah Malaya (KTM), a firm owned by the Malaysian government, with effect from July 1, 2011 is used in a quasi‐experiment design to test the effects of the removal of train noise externalities on real estate values. Based on the nonlanded private housing transactions data from January 2005 to June 2013, we find that average prices for houses located within a 400‐m boundary from the railway lines increased by 3.5% relative to prices for houses located outside the 400‐m boundary after the cessation agreement has been announced. The removal of train noise externalities increases housing prices in the affected area by 13.7% on average in the postcessation period of the KTM railway services. Realized economic benefits associated with the railway services cessation were estimated at S

Information Infrastructure for Research Collaboration in Land Use, Transportation, and Environmental Planning

0.36 billion based on houses sold in the post cessation period of the KTM railway services.

Are Inner-City Neighborhoods Underserved? An Empirical Analysis of Food Markets in a U.S. Metropolitan Area

This paper presents the framework and implementation of a flexible, loosely coupled information infrastructure to facilitate collaborative research on land use, transportation, and environment (LUTE) modeling. The framework combines off-the-shelf open source applications such as Apache, PostgreSQL, MapServer, OpenSSL, and MediaWiki, with proprietary tools such as ArcGIS Server and Flex, and uses minimal custom code to provide web services for distributed modeling and realistic evolution of data, models, and research. The approach has been developed to assist research collaboration for the transportation systems focus areas of the Massachusetts Institute of Technology–Portugal program, but it can be appropriate for other collaborative efforts that could benefit from federated systems for LUTE modeling across local and regional agencies and university partners.

Vehicle miles traveled and the built environment: evidence from vehicle safety inspection data

Food accessibility in socioeconomically disadvantaged neighborhoods has caused increasing concern because of its potential impacts on public health and neighborhood development. This article proposes a new approach to test whether and to what extent inner-city neighborhoods are “underserved” in food markets controlling for multiple factors that may influence food supply levels. An improved measure of market potential is developed. Using the Boston metropolitan area as an example, we demonstrate that inner-city tracts have significantly lower levels of food store sales than non-inner-city tracts. The research helps to sort out the impact of multiple factors on food environment and contributes to more informed policy design to improve food access and revitalize inner-city neighborhoods.

Are Singaporean Cabdrivers Target Earners

This study examines the linkage between household vehicle usage and their residential locations within a metropolitan area using a newly available administrative dataset of annual private passenger vehicle safety inspection records (with odometer readings) and spatially detailed data on the built environment. Vehicle miles travelled (VMT) and a set of comprehensive built-environment measures are computed for a statewide 250 × 250 m grid cell layer using advanced geographic information systems and database management tools. We apply factor analysis to construct five factors that differentiate the built-environment characteristics of the grid cells and then integrate the built-environment factors into spatial regression models of household vehicle usage that account for built environment, demographics, and spatial interactions. The empirical results suggest that built-environment factors not only play an important role in explaining the intraurban variation of household vehicle usage, but may also be underestimated by previous studies that use more aggregate built-environment measures. One-standard-deviation variations in the built-environment factors are associated with as much as 5000-mile differences in annual VMT per household. This study also demonstrates the potential value of new georeferenced administrative datasets in developing indicators that can assist urban planning and urban management.

Public Transit Riders’ Preferences: Evidence from Smart Card Transactions in Singapore

We use a unique administrative dataset of over 10,000 taxi drivers in Singapore to study the labor supply decisions of these drivers. Our study uses a high frequency dataset to test whether cabdrivers exhibit reference-dependence preferences. We estimate cabdrivers’ day and day-of-the-week hours and income targets using ex-post data, and find that the targets have a strong and positive impact on cabdrivers’ probability of stopping work. Cabdrivers with high cumulative hours and/or cumulative income for the day are more likely to stop work earlier when they reach their hour and income targets. We also find that cabdrivers’ income targets are independent of ex-post positive and negative daily income shocks, and that their targeting behavior is persistent. The results support the idea that rational expectations underpin reference-dependence in the labor supply decisions of cabdrivers in our sample.