Employing Geographically Weighted Regression to Estimate the Property Value Increment Due to a Heavy Rail Rapid Transit Station and Simulating the Potential to Employ the Value Increment to Fund Transit and Affordable Housing

The last two to three decades have witnessed an increasing interest in public transit across various levels in the United States. Furthermore, the federal transportation and infrastructure acts have called for transportation-land use coordination. Moreover, federal funding programs, such as the Livable and Sustainable Communities Program and the New Starts Program, have provided much-needed financing for public transit projects. However, due to the significant funds needed to construct and operate public transit systems, federal funds are often inadequate, and fiscally constrained local and state governments are frequently unable to fill the funding gap. Any new revenue source that helps fund public transit projects is welcome in such a scenario. Value capture (VC) is one such source.

One VC tool, special assessment districts (SADs), captures public-infrastructure-led property value increases by levying a fee or assessment on properties within a SAD in proportion to the benefit received. Normatively, VC tools are based on the "benefits received" principle, which posits that the beneficiaries of a particular infrastructure/service should also pay for it. If the provision of or enhancements to public transit systems generate accessibility-related benefits to neighboring properties, these benefits get positively capitalized into higher property values—a windfall gain for private property owners. Hence, it is argued that these property owners should help fund public transit systems because they benefit from them. The first step in levying VC tools, such as SADs, is to empirically demonstrate that the public transit has indeed increased the value of the neighboring properties and to ascertain whether the magnitude of the impacts varies across the entire vicinity of the transit infrastructure, such as a transit station. For example, is the value increment 12% of the property value across the entire 0-2-mile band around a transit station, or is it 5% in one section of the band, 7% in the second, 15% in the third, and so on? Variability in property value increment would call for different property assessment rates in each section of the band. In practice, such fine-grained empirical estimations are rarely conducted, and public agencies make educated guesses about the likelihood and magnitude of the benefits. For example, they erroneously assume that the impact is likely limited to one side of a freeway or an arterial road or use existing neighborhood boundaries to delineate SADs. As a result, public agencies often only capture a very small proportion of the value increase.

This study will employ the Geographically Weighted Regression (GWR) approach to develop a hedonic price model to estimate the increases in the values of single-family homes due to the Bay Area Rapid Transit (BART) system's Berryessa Station located in San Jose, CA. Next, it will run financial simulations to estimate how much of this transit project and transit-oriented affordable housing could have been supported if a portion of the increment had been reinvested to fund them. Finally, based on the findings of this and existing studies, the study will provide an estimated range of property value increments due to metro rail stations.