Tailoring empirical research on transit access premiums for planning applications

- Devised empirical research aims supporting evidence-based planning and policy making.
- Identified transit catchment areas in Wuhan are greater than conventional beliefs.
- Estimated location-specific access premiums inform fine-tuning density bonus policy.
- A 0.5% value-capture rate could generate 153 million yuan from 2013 housing stock.

Existing studies on transit access premiums focus primarily on hypothesis testing and methodological sophistication. There is a disconnect between the study efforts and the practice of transit-oriented planning and policy making. This paper aims at building this connection through a case study of Wuhan, China. The study applies established conceptual frameworks and analytical procedures in the field to 1) examine the spatial extent of rail transit impacts on housing market; 2) estimate transit access premiums and their spatial distribution in the station area; and 3) simulate revenue streams to illustrate the potential of transit value capture. The empirical results show that in Wuhan the influence area extends to 700 m for light rail transit (LRT Line 1), 900-1000 m for metro rail (MRT Lines 2 and 4). The distance ranges differ from the conventionally accepted value of 400 m and the value of 500-600 m currently considered by Wuhan local planning agencies. This empirical knowledge enables transit planners to modify transit catchment areas for the interest of enhancing ridership forecasting and service planning.The Wuhan case study reports average transit capitalization rates of 2.87%, 3.71%, and 4.37% for LRT Line 1, MRT Line 2, and MRT Line 4, respectively. These capitalization rates translate to average premium values of 318.14, 383.02, and 400.23 yuan per-square meter within the corresponding influence areas for the respective three lines. This location-specific knowledge on housing market responses to transit access supports the local government to formulate and fine-tune location-specific plans and policies; for example, the density bonus regulation currently practiced by Wuhan municipal government. The simulation shows that a 0.5% capture rate could generate more than 153 million yuan from the existing housing stock (in year 2013) inside the influence areas of the three transit lines in Wuhan. In the full build-out scenario under Wuhan's current TOD density regulation, the captured value is 222 million yuan. The captured value could help reduce transit operation deficits. Planning practice and policy making should move from being experience-driven to evidence-based. Empirical research is essential to identify and provide the needed evidence for more efficient TOD regulation and value capture.