An Analysis of the Agglomeration Benefits of Transit Investment

Transit investments can affect the clustering of economic activity within a region, due to the changes in accessibility that transit can provide, either by increasing firm-based access to the central business district or increasing effective labor market size. This clustering can lead to what are known as agglomeration benefits that increase overall economic productivity and are external to the decisions taken by individual firms. Cost-benefit analysis of transit investments rarely account for such external benefits. Agglomeration benefits work through several mechanisms. Two mechanisms most likely relevant to transit are knowledge spillovers enabled by firm clustering near rail stops and better labor matching, due to higher labor market access caused by expansions of transit networks. The actual linkages are complex and are not well captured by simple econometric models. The researchers propose to examine these linkages using a structural equations modeling framework that can account for the direct and indirect effects of transit investment on external productivity benefits within a region. This work will build upon a Transit Cooperative Research Program (TCRP) funded study that the research team has been engaged in. As part of this work, the researchers have developed two large datasets to examine agglomeration impacts. The first is a nationwide dataset of metropolitan areas with measures of GDP, average wages, city size, central city and urbanized area employment density, transit capacity, road capacity, and human capital. The researchers analyzed this dataset using a two-step path analysis, relying on standard cross-sectional econometric techniques to account for endogeneity. They found potentially large and significant effects of transit capacity upon agglomeration and hence productivity. The main shortcoming of this work to date is the lack of control for various other potentially confounding variables that could influence population growth and employment density and may cause inaccurate coefficient estimates for transit capacity. The researchers' theoretical framework could alternatively be implemented using structural equation modeling to account for both direct and indirect effects, providing stronger evidence of a causal relationship from transit capacity to agglomeration and from agglomeration to productivity. The second dataset consists of firm-level data for two metropolitan regions with large and growing rail transit systems: Portland, Oregon, and Dallas, Texas. Analysis of these data has found interesting differences in how transit investments in the two regions are correlated with the distribution and density of employment by industrial classification. Current analysis has aggregated firm data to the block-level rather than analyzing specific firm-level data; this will be extended by developing models at the firm level to investigate firm births and deaths, within-firm growth, and other more detailed phenomena that enable a clearer understanding of dynamics associated with agglomeration near rail stops in the two regions. Although the dataset does not include explicit productivity measures such as revenues or wages, this analysis will enable a focus on industry structure and the process by which agglomeration can lead to new firm formation, a key indicator of potential increased productivity. The researchers expect both strands of the research to provide informative results that will greatly increase the value of the work they have already completed. Assessing the costs and benefits of proposed transit infrastructure investments depends on a better understanding of how regional and firm-level productivity might be affected. The research will also have implications for decisions about funding high-speed rail service. For the New York metropolitan region in particular, investigating how regional and firm-level productivity is affected by major transit improvements is a critical missing piece for quantifying the benefits of key links such as the ARC/Gateway project.


  • English


  • Status: Active
  • Contract Numbers:


  • Sponsor Organizations:

    Research and Innovative Technology Administration

    University Transportation Centers Program
    Washington, DC  USA  20590
  • Project Managers:

    Crichton-Summers, Camille

  • Performing Organizations:

    Center for Advanced Infrastructure & Transportation

    Rutgers University
    100 Brett Rd
    Piscataway, NJ  USA  08854-8058
  • Principal Investigators:

    Chatman, Daniel

    Noland, Robert

  • Start Date: 20111201
  • Actual Completion Date: 20130731
  • Source Data: RiP Project 29290

Subject/Index Terms

Filing Info

  • Accession Number: 01467839
  • Record Type: Research project
  • Source Agency: University Transportation Research Center
  • Contract Numbers: 49111-28-21
  • Files: RiP, USDOT
  • Created Date: Jan 3 2013 3:40PM