2021

Jason Hawkins (jason.hawkins@mail.utoronto.ca), University of Toronto
Khandker Nurul Habib, University of Toronto

The paper presents a model of location choices of business establishments in the Greater Toronto Area (GTA). The model is of the latent auction model, where the price and utility are jointly modelled in a random utility-maximizing framework. Structural relationships between establishments by their industry classification and type (i.e., headquarters, subsidiary, branch, or single location) are explored through a generalized nesting correlation structure. This structure provides a mechanism for differentiating between the branch and the single location establishments, having seemingly similar functions, but differing in their allocation between industry and type nests. Location choice models are estimated for the full population of establishments in the GTA at the level of individual buildings. The scope of the model allows us to provide a range of insights into the location choice behavior of establishments, which were previously infeasible due to data limitations. We find that professional service establishments tend to locate near passenger rail stations (i.e., subway and LRT), while industrial establishments tend to locate near major highway interchanges.

Ahoura Zandiatashbar, San Jose State University
Shima Hamidi, Johns Hopkins University

As universities, headquarters and medical centers are anchoring cities’ innovation productivity and transforming anchor-based urban revitalization models like “innovation districts”; cities are experiencing a growing competition for anchors (e.g. Amazon HQ2), emerging partnerships (e.g. the Cleveland Foundation), and conflicts (e.g. opposition against Bay Area’s tech companies’ private shuttles); in all of which, transit had a major role to play. Yet, there is little known about the direct and indirect impacts of transit (through anchors) on knowledge intensive (KIBS) firm locations and productivity. To address this need and the gap in empirical literature, this study employed Structural Equation Modeling (SEM) to grasp both direct and indirect impacts of transit on KIBS firm locations in 500 U.S. large cities. We conceptualize the indirect impact of transit through anchors as the mediator and measure it by developing an anchor index that represents the presence and size of major innovation anchors in each city. According to our findings, the positive impact of transit on KIBS firm location is through attracting anchor institutions to the city, which in turn, would lead to significantly higher likelihood of KIBS firm location in the city. In other words, transit attracts larger and more established anchors as well as more employees for them leading to a wider city’s talent pool; a critical driver of knowledge-intensive employers. This calls for a stronger attention to transit in cities’ anchor-based urban revitalization plans and partnerships between cities, metropolitan organisations, and anchors in the future plans for expansion of the transit systems.

Sanjeev Bhurtyal, University of Arkansas, Fayetteville
Madeline Giebler, University of Arkansas, Fayetteville
Suman Mitra, University of Arkansas, Fayetteville
Sarah Hernandez, University of Arkansas, Fayetteville

Highway bypasses divert through traffic around a city’s core in part to improve safety and reduce congestion. In small cities, highway related business along the bypassed highway might lose business, contributing to declining economic conditions in the city. There is a need to measure this negative externality to identify mitigating solutions. An established proxy for economic condition is residential property values. Statistical approaches, e.g., ordinary least squares (OLS), are commonly applied to measure the impact of highway bypasses on property values but fail to capture critical spatial relationships inherent in property values.  In this study, we adopt a hedonic pricing model with considerations for spatial dependencies to estimate the effect of a highway bypass on residential property values in a small city (population less than 25,000) in Arkansas. Neighborhood, network accessibility and disamenity variables are considered. The result of a log-log estimation of a spatial autoregressive model with autoregressive disturbances (SARAR) model on 1,751 properties shows that the residential properties closer to the bypass have lower land value compared to properties closer to bypassed highway, e.g., land value per acre of properties closer to the bypass decreases by 40% or by $15,850. This implies that the bypassed highway provides greater accessibility compared to bypass. A log-log OLS model underestimates the impact of the bypass on property values, e.g., land value closer to the bypass decreases by 24%. Estimates of highway bypass impacts can be used to guide transportation investment decisions made by state transportation agencies.

Robert Hibberd, University of Arizona
Arthur Nelson, University of Arizona

Employment-Worker Balance (EWB), a key to economic growth through agglomeration economies is  also a key to social equity. This is due to its ability to both increase workers’ access to employment and  firms’ access to a strong, diverse, and resilient workforce. Smart Growth advocates frequently identify Employment-Worker Balance as a key metric in compact urban design. Because of its potential synergistic effects with EWB, another key element of Smart Growth, Fixed-Rail Transit systems (FRT), needs to be studied for its effects on EWB: is the latter improved by the former, and for which job sectors and which workers? Principle Component Analysis will be used to produce a EWB Index that is able to map EWB across multifarious spatial contexts across the U.S., taking into its scope the multiple types of transit system modes, real estate types, and the many sectors of the economy that surround FRT stations.  The EWB Index will provide a tool for practitioners and researchers to utilize in regression analysis, and policy and decision support. The paper will follow up on this significant increase of available evidence to work towards further theoretical refinement of EWB.

Kristina Currans (curransk@email.arizona.edu), University of Arizona
Robert Hibberd, University of Arizona
Nicole Iroz-Elardo, University of Arizona
Arthur Nelson, University of Arizona

Fixed-route transit (FRT) systems have operated in the US for more than a century, and there exists dozens of studies that explore how the real estate market responses to individual systems and regions. Based on theories of Alonso, Mills, and Muth, we might expect to see the real estate market respond positively—i.e., higher rent prices—to improvements in local accessibility due to FRT systems, particularly for land uses that benefit from high-quality transit improvements. However, a recent meta-analysis suggests some confounding results and interpretation. In this paper, we developed a pooled, quasi-experimental and cross-sectional hedonic analysis to explore associations between proximity to FRT systems and land use. We consider three FRT system types (light-rail, bus-rapid, and streetcar transit) across over thirty metropolitan statistical areas for three land use types (multifamily, office, and retail). In this manuscript, we summarize the findings of nine large ordinary least squares regressions which include structural and locational controls, as common in the related hedonic literature. For light-rail and bus-rapid transit systems, we detected three or four patterns of associations with proximity to transit for multifamily and office land uses—mostly positive but to varying degrees and some negative. For streetcar systems, there is not an adequate sample size to detect structural differences in the market responses across regions; however, the results indicate generally positive associations with streetcar systems for the land uses studied. Implications and future research are discussed.

Sangwan Lee (sangwan@pdx.edu), Portland State University
Aaron Golub, Portland State University

A large body of literature and theories has revealed that the transportation accessibility can trigger at least modest premium on property values due to the improved accessibility and reduced travel costs, although the land-use impacts of public transit are highly context-specific. Since there is a handful of recent studies that examine the impact of the accessibility to emerging transportation modes on land use, however, this research examins the impact of the proximity to carsharing and bikesharing services on property values in New York City. We develop the Hedonic Regression with the level-log model and the Spatial Durbin Model with the Queen Contiguity Matrix. Notable finding is that as we hypothesized, the proximity to carsharing (Zipcar) and bikesharing (CitiBike) services are positively valued in real estate market in New York City and the relationships are logarithmic rather than linear. All else equal, 10 percent decrease in distance to the nearest Zipcar parking lots or CitiBike station leads to approximately 3 or 20 dollars increase in property value per square footage, respectively. For additional distance variables to transportation systems, properties near subway station, highway, and bike lane sold at a higher price, while the insignificant association found in the distance to the nearest bus stop. As the distance to ramp decreases, the property value decreases. We believe that this study fills the research gap in understanding the property value premium of the proximity to carsharing and bikesharing services, which helps private sector, policymakers, and community members to understand the “value capture” effects.

Ahoura Zandiatashbar, San Jose State University
Shima Hamidi, Johns Hopkins University

Clustering and active transportation infrastructures have an imperative impact on emergent economic development strategies for attracting high-tech firms. These firms form clusters to benefit from economies of scale; and in these clusters, are expected to favor walkable and transit accessible locations following the preferences of footloose workers of the creative class. Although this pattern could justify pro-walkability and -transit economic development strategies, such strategies loosely consider other countervailing factors. Accordingly, changes in logistics, land values, the rise of the e-economy and gig workers could shift the high-tech firms’ mobility preferences. This study addresses this ambiguity by analyzing and quantifying the location behavior of high-tech industries in high-tech clusters with respect to transportation infrastructures. Our analysis uses a firm-level micro dataset provided by Esri and Multinomial Logit Regressions to explore the relationship between high-tech firm locations and transportation amenities in the high-tech clusters. The results show that not all high-tech industries prefer dense, walkable, mixed use, and transit accessible locations. However, professional services (i.e. consulting, legal, computer services, or engineering and architectural services) which have the biggest share of high-tech employees are drawn to walkable and transit rich areas with proximity to CBDs, compared to other high-tech specializations. Meanwhile, auto-centric locations on the peripheries are home to aerospace and bio-pharmaceutical industries. In the light of these findings, it is critical for economic development officials to consider the major local high-tech sector(s) and the sectoral differences in their policy development in order to achieve a balanced growth.