Methodology for Determining the Economic Development Impacts of Transit Projects (2012)

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17 3. FRAMEWORK FOR ANALYSIS, AND SCOPE OF WORK Much research still needs to be conducted to fully understand the wider economic impacts of transit investments. Two important questions about agglomeration and transit are not well understood. The first is under what conditions transit projects might significantly increase accessibility and/or concentrate residential development or firm clusters. The second question is how those changes might lead to increases in economic productivity. Addressing these questions is essential to understanding the likely economic impacts of transit investments given the varied economies, infrastructure, and development conditions of particular cities. Existing empirical studies, for the most part, are unable to provide insight into the why and how—they are only able to demonstrate that with certain data sets and in certain places, there is a correlation between (for example) economic productivity and employment density or accessibility. The role of transit investments in increasing residential or employment density (either physical density, or “effective density”—i.e., employment accessibility) is essentially assumed in such studies. The UK guidance offers a useful roadmap for assessing some of the additional economic benefits of transit, in that the additional economic benefits of transit investments are only one small piece of a much more comprehensive multi-attribute assessment approach in the UK. The approach is explicitly designed to match national objectives with specific assessment criteria, including objectives of environment, accessibility, safety, economic, and transport integration with other policy sectors. Within the overall evaluation process, this type of framework could provide a useful means of integrating regional goals with other objectives; however, there are limitations to the UK approach. It assumes that physical densification is purely redistributive, it relies on firm-level data to which US analysts typically do not have access, and it treats modes as equivalents when they may not function similarly in particular agglomeration mechanisms. We discuss these issues in more detail below. Assessment: Improvements to research and practice In this section we discuss and critique existing research and practice in several topical areas, as follows: understanding agglomeration mechanisms; treating transit separately from other transportation modes; improving measurement and estimation methods; controlling for endogeneity; distinguishing net effects from redistribution; and considering development context, particularly regulatory constraints on development impacts. In the end, our analysis method addresses some, but not all, of these issues. Understanding agglomeration mechanisms There is much to explore about the agglomeration-related mechanisms of economic growth with respect to transit infrastructure, and reasons to be cautious about extrapolating estimates. Although there is plentiful empirical evidence that industrial productivity is higher in denser or more accessible areas, the specific reasons for such relationships are not well understood. We have instead several hypotheses that have, for the most part, not been adequately tested. For example, transit investments may increase the accessibility of workers to employment clusters, resulting in higher productivity from better job matching and quicker filling of vacancies. Transit investments may also enable metropolitan growth by allowing higher

18 occupancy of existing development without requiring additional construction of auto parking spaces. Distinguishing such different possible agglomeration economies is important, particularly if future development will not have the same characteristics as current development, or if a study area economy is significantly different from that to which estimates are to be applied. Treating transit separately Transit investments may enable agglomerations of firms and households, which may in turn increase productivity and economic output. But there is a need for research to explicitly examine the economic impacts of transit projects, as opposed to those of transportation generally, or highways specifically. Previous research has not explicitly investigated how transit leads to agglomeration and hence increases economic productivity. Current practice in the United States also does little to analyze these linkages. The best practical example of estimating impacts, the UK guidance, relies on a composite generalized cost measure which gives weights to the different modes according to current trip patterns. In places where auto trips dominate (as in most cities in the United States) this measure does not represent transit’s potential impacts on accessibility via agglomeration, and elasticity estimates applied based on such travel time estimates would be incorrect. Also, the UK method does not take into account how changes in development densification may increase agglomeration economies. The method measures only those effects of agglomeration economies depending on interactions that occur between existing firms and households over transit and roads. Higher employment accessibility may enable economies of scale in serving markets that require freight shipment, without increasing agglomeration externalities. That is, they may enable higher productivity not due to more interaction with firms, but higher productivity because reduced transportation cost enables a larger scale of production. Since “serving markets” in this case means sending trucks on roads, this kind of economy is less applicable to transit. Some of the agglomeration benefits of transit may be very localized—limited by walking distances, and dependent on intensification of development around transit corridors and/or near stations. Other potential economic benefits of transit investments are regional in scope, and are not as dependent on development intensification. Improving data and measures of dependent and independent variables Continued improvements in measures of key dependent and independent variables are needed to better understand and estimate the relationship between transit and agglomeration. There might be significant threshold effects of agglomeration on productivity; agglomerations (transit-induced or otherwise) might increase productivity only at sufficiently high density. This requires explicit threshold measures or other nonlinear measures. Most economic productivity measures implicitly include the value of reduced travel time. For example, net revenues are exclusive of wages which could be lower due to reduced travel time. The value of finished goods per worker might provide a measure avoiding the double- counting problem. Output per worker may also be the best measure from the national perspective, because it implies genuine additional economic growth (not just economic growth that would have occurred anyway, being transferred from one region or locality to another) and improved global economic competitiveness.

19 Accounting for endogeneity (the chicken-or-egg problem) The research needs to explore further the endogeneity of firm location with respect to agglomeration, and so far has done little on endogeneity of firm location with respect to transit infrastructure. Do more productive firms move to denser or more accessible places? Does greater accessibility or density lead to higher productivity? How does transit infrastructure influence these location and expansion decisions? How might transit infrastructure increase productivity and innovation? There have been few attempts at longitudinal analysis; almost all empirical work is cross-sectional. Distinguishing effects at different scales and for different groups The impacts of transit projects on the economy flow from accessibility changes— reductions in travel time—as well as reductions in the cost of travel. These changes are unevenly distributed within a region, leading to localized and possibly regional changes in demand for space, and hence increased demand for land development in some places with possibly decreased demand in other places. Redistribution of employment may occur in response to a transit investment, reducing employment accessibility in some areas, and perhaps also resulting in reduced productivity in those places. Thus there is a need to distinguish net regional or national economic benefits from local redistribution of economic activity. “Economic growth” is a tricky concept. Does it refer to more local capture of regional growth, to more regional capture of national growth, or to more national capture of global economic growth? These possibilities should be distinguished with study at different geographic scales. From the national perspective, it may be national growth that matters most. Considering development context There is a need in practice to understand the role of development regulations in enabling some kinds of agglomeration economies. Development regulations constrain supply development responses to demands, to a varying extent from jurisdiction to jurisdiction. Estimates of the land use impacts of transit projects are already addressed under FTA guidelines for the New Starts and Small Starts programs, and could be used as an input to estimates of agglomeration economies. But they are important inputs to additional economic impacts and may need to be included in the procedures for calculating those impacts. Empirical study approach Agglomeration impact estimates are readily carried out at the metropolitan level for the United States because data on GDP and wages are available for metropolitan areas. Agglomeration elasticities have been estimated for the United Kingdom, for a variety of industrial sectors, but similar estimates do not exist for the US. Thus, the first task we identified was to conduct a national study of metropolitan areas examining how changes in transit infrastructure affect productive output in urbanized areas, providing estimates of metropolitan- wide agglomeration economies caused by transit investments. The second part of the study approach was to investigate firm-level data, which are more precise than data aggregated to counties or higher spatial levels, and which enable an investigation of how transit affects the

20 distribution of economic activity. There is reason to believe that the economic impacts of transit investment may be the greatest for firms with walking access to stations, while possibly leading to reductions in economic output for firms farther away from transit. Finally, we selected and carried out three project-level case studies, to investigate the qualitative and context-driven aspects of the transit-agglomeration-productivity relationship, and better understand the local political, economic, and institutional factors that may play an important role. We focused on agglomeration economies and not the four other possible sources of additional economic impacts of transit, for several reasons. First, the literature suggests that agglomeration benefits are the largest of the additional economic benefits associated with transportation, and we expect that for transit they are even more important. Estimates of network effects and economic multiplier effects would double-count some of the impacts of travel time changes (such as higher ridership), while economic adjustments from relocation should be captured by agglomeration estimates. There is reason to believe that the tax-related labor participation benefits and the price-competition benefits used in the UK guidance are actually transfers, rather than additional economic benefits in a broader sense. Also, there are very few studies of either, and estimates rely heavily on intuition. Finally, improving competition between firms on price is not an impact that we expect to see for most transit investments in the United States, because the ability of consumers and firms to search for better-priced products may not be significantly expanded by transit.