Economic Impact Case Study Tool for Transit (2016)

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7 C H A P T E R 2 The work scope for this study called for seven case studies to be developed as a pilot demonstration of the TPICS con­ cept for transit. These case studies are built upon the struc­ ture and process developed for SHRP 2 Project C03 (EDR Group et al., 2012). This process follows closely that which was used to develop highway case studies while identifying which adaptations are necessary to improve the highway pro­ cess for application to transit cases. The process of identifying potential case studies serves to provide a basis for estimat­ ing the feasibility of expanding the existing system of case studies to encompass a larger set of transit cases if desired in the future. 2.1 Identification and Selection Process The selection process for the seven pilots involved four steps, which are described in this section. This process pro­ vided a list of additional projects that could be studied in the future. This process may help in identifying more options for study at a later date. Case Selection Step 1: Define Criteria The first step was to develop a request for case study nomi­ nations. The project team initially developed a draft set of project criteria, which was reviewed by the project panel, and then incorporated the approved criteria into an announce­ ment seeking case study nominations. The announcement text can be seen in Figure 1. Compared with the previous work for SHRP 2 C03 in compil­ ing a highway database, the transit project used a more recent, and shorter time period. The reason for specifying the 2000– 2010 time period was to ensure a focus on projects that are old enough to have a high likelihood that post­project economic development impacts will be clearly completed and hence observable, yet are not so old that it is difficult to find local agency contacts who were in their jobs long enough to remem­ ber pre­project conditions and local factors affecting project outcomes. The latter consideration is particularly notable because multiple local interviews are required to provide infor­ mation regarding the role of the transit investment relative to other factors in affecting observed economic and develop­ ment outcomes. Thus, the specified time period was judged optimal for initial case studies as older or newer projects would be more likely to involve greater staff effort to complete the case studies. (Older projects could require more effort to find suitable interviewees; newer projects could require more effort to discern emerging trends not yet reflected in public datasets.) The project team recognizes, however, that in the future there may also be cases where there is sufficient infor­ mation available to enable the further addition of some older and some more recent projects. The issue of time period for future studies is discussed in Chapter 5. The solicitation for transit case nominations also utilized a smaller cost threshold than the highway­focused case studies after which they are formatted due to the expectation that transit projects are smaller than the major highway projects selected. The reason for the minimum $5 million investment size was to focus on projects that are large enough to have a reasonable likelihood of finding impacts. While it is indeed desirable to include projects that had disappointingly small economic development impacts (as well as those with sur­ prisingly large impacts), it was agreed that the pilot case studies should not focus on small projects that had little, if any, expectation of economic development impacts. As we will discuss in more detail later (in Chapter 5), for future case studies, we would recommend a higher threshold as few of the projects nominated or those subsequently investigated were so small. Case Study Selection and Compilation

8study team decided to provide a 1­year grace period and accept projects completed between 1999 and 2011. Six of the case study nominations fell outside of that period and, thus, were deleted from further consideration for this study. While these projects were taken out of the running for this TPICS for Transit pilot demonstration, they could still make for good case studies for an expanded TPICS sys­ tem in the future. The announced project date range was defined in the first place to minimize likely staff effort for case study data collection and interview completion. With a better funded effort in the future, those date requirements could be relaxed further. 2. Check for Inclusion in Prior SHRP 2 Study. While the ear­ lier SHRP 2 study focused on developing TPICS for high­ ways, it ended up developing nine case studies for highway/ transit intermodal facilities. Those projects, while also good candidates for inclusion in the new TPICS for Transit, already have case studies developed and, hence, are not candidates for new case study development. Thus, those nine projects were also deleted from further consideration for this study. 3. Check for Low Passenger Activity Level. While all forms of transit may be candidates for case study development, the pilot demonstration should focus on projects that have a substantial level of service provided all day long with activity focused at specific sites so as to support significant economic development nearby. Many commuter rail stops and stations have activity concentrated during rush­hour periods, with relatively infrequent service at other times. As a result, the economic impact of most commuter rail stations or stops is relatively limited (e.g., a commuter rail station with take­out coffee and sandwich sales). For this reason, four of the five commuter rail projects were deleted from further consideration for this study. 4. Screen Out Upgrades to Existing Facilities. Projects with “state of good repair” goals typically have broadly diffused Case Selection Step 2: Distribution of Request for Nomination of Case Studies The second step was to distribute the announcement to applicable organizations. During May of 2015, it went out to the following groups: • Association of Metropolitan Planning Organizations (AMPO)—electronic newsletter; • APTA—distributed to bus and rail transit committees; • Project Panel for TCRP Project H­50; and • Standing committees of TRB, who distributed it to their members and friends lists— – ADD10 Committee on Transportation and Economic Development, – ADD30 Committee on Transportation and Land Use, – APO28 Committee on Public Transportation Planning and Development, – APO65 Committee on Rail Transportation System, and – APO45 Committee on Intermodal Transfer Facilities. The announcement was also forwarded by a panel member to FTA. Altogether, 61 nominations were received from a wide variety of respondents, including a list from FTA. Case Selection Step 3: Review of Nominated Case Studies The third step was to subject the 61 nominated case study projects to a formal review process in order to identify a short list of cases that are most relevant for this study. This involved exam­ ination of the extent to which the nominated cases met specified selection criteria and appeared to have economic impacts that could be measured. There were five elements to this review: 1. Check for Project Dates. While the formal announcement asked for projects completed between 2000 and 2010, the Figure 1. Announcement of case nomination need. Seeking Case Study Nominations: Transit Improvements that Trigger Economic Development APTA and TCRP (under Project H-50) are developing a pilot database of case studies documenting the actual economic development impacts of transit investments. This project will complement a similar set of highway economic impact case studies developed for SHRP2, called TPICS. Verifiable examples of actual, observed impacts are a key part of this project. We are looking for suggestions or nominations of potentially relevant case studies, which: involve projects completed no earlier than 2000 and no later than 2010 involved a project investment of at least $5 million had localized economic development occur (regardless of the catalysts for that investment and regardless of whether the project has been studied before for any purpose) have local agencies or individuals who can be interviewed regarding the project history and any economic development that followed the transit investment.

9 Another three station construction projects were deleted from further consideration because there was evidence indi­ cating that relatively little development had occurred to date within their vicinity. Again, they may still be reasonable can­ didates for a broader TPICS for Transit, but those cases would not be able to showcase the value of in­depth case study analy­ sis in this pilot demonstration. (See Chapter 5 for further dis­ cussion of sampling issues relevant to full roll­out of the case study database for transit.) Table 1 presents the 27 identified candidate projects that emerged from the case study nomination and review process, along with information on mode, location, timing, and cost. All 27 of these projects were considered good candidates for a fully developed TPICS for Transit system. Case Selection Step 4: Refinement of a Short List for Case Study Development The fourth and final step was to analyze the 27 remain­ ing transit projects in terms of their mix of project type, regional location, market setting, and project cost, as well transportation impacts, which make local economic impact measurement difficult. Hence, they are not con­ ducive for pilot case study examples. These include proj­ ects involving wide­area or system­wide reconstruction or upgrades of equipment. In those cases, there was no single location in which the improvements were focused and, therefore, no specific area where economic devel­ opment impacts would be most likely to occur. Another three projects were deleted from further consideration for that reason. 5. Check for Economic Impact. Of the remaining case study nominations, six more were removed from the list because their impact was primarily residential development with only small neighborhood retail activity. Only projects that had observable job and income effects (e.g., office, medical, or industrial activity impacts) were considered for the pilot case study examples. The reason was to main­ tain consistency with the original focus of the TPICS for Highways database, which sought to measure economic development impacts—that is, job and worker income generation. Table 1. List of 27 finalist candidate projects, with descriptive information. Project Name Mode City State Comple on Year Cost ($Ms) Central Phoenix LRT Corridor LRT Phoenix AZ 2008 $1,400 Orange Line BRT BRT Los Angeles CA 2005 $324 BART to Airport HRT San Francisco CA 2003 $1,483 Mission Valley East Extension LRT San Diego CA 2005 $506 North Hollywood Extension HRT Los Angeles CA 2000 $1,310 Denver Southwest LRT LRT Denver CO 2000 $177 WMATA Branch Ave Extension HRT Washington DC 2001 $900 WMATA Largo Extension HRT Washington DC 2004 $607 NoMa Gallaudet Red Line Staon HRT Washington DC 2004 $104 Atlanta North Line Extension HRT Atlanta GA 2000 $463 Boston Silver Line BRT Boston MA 2004 $374 Hiawatha Corridor LRT Minneapolis MN 2004 $715 LYNX Blue Line LRT Charloe NC 2007 $427 Hudson Bergen LRT LRT Jersey City NJ 2000 $2,200 Riverline LRT LRT Trenton NJ 2004 $1,100 Atlanc Terminal refurbishment LRT, HRT,BRT, Bus Brooklyn NY 2010 $108 Euclid Corridor BRT Cleveland OH 2007 $200 EmX Phase I BRT BRT Eugene OR 2007 $25 Interstate MAX LRT Portland OR 2004 $350 Gateway Transit Center LRT Portland OR 2006 $32 Tren Urbano HRT San Juan PR 2004 $2,280 North Central Corridor LRT Dallas TX 2002 $120 Green Line Downtown Plan Bus Atlanta GA 2002 $6 Dallas Area Rapid Transit (DART) LRT Plano TX 2002 $63 Univ. & Med Ctr. TRAX Extension LRT Salt Lake City UT 2002 $238 St. Louis/St. Clair MetroLink Extension LRT St. Louis MO 2001 $339 Kent Staon & Retail HRT Kent WA 2001 Note: LRT = light rail transit, HRT = heavy rail transit, BRT = bus rapid transit.

10 • Mix of regions: Mid­Atlantic/Northeast (2), Great Lakes/ Plains (1), Rockies/West (3), Southwest (0), and South­ east (1). Table 2 provides the list of the 7 projects with relevant characteristics. 2.2 Types of Projects Covered Transit cases required a different project type framework than the highway cases in the original TPICS database. The classifications described here were used during the case screen­ ing process as well as implemented for the online database. The new TPICS for Transit was designed to cover transit lines, transit stations, and transit service enhancements. They were classified by four modal groups: bus, BRT, LRT, and HRT. They were also classified by four operational categories: (1) opening of new line or service, (2) extension of existing line or ser­ vice, (3) new terminal facility, and (4) service improvement. This makes for 16 possible classification categories as shown in Table 3. (See Chapter 5 for discussion of possibilities for inclusion of additional types of transit projects in a full roll­ out of the case study database for transit.) These categories serve to guide users seeking to select case studies that are relevant to them. Each of the 16 categories should eventually have at least 5 cases for viewing and com­ paring results within the category. While it is easy to proliferate categories by defining additional dimensions or finer distinc­ tions among cases, it would be counterproductive because it would increase the likelihood that a user searching for relevant cases would come up with few or zero matching cases. There is no overlap between the new transit categories and the old highway categories with the exception of a highway project category called “intermodal road/transit terminals”— which covers projects that could also be used within an expanded transit case study database. as the existence of prior research documenting at least some aspect of their economic impact. Sections 2.2 and 2.3 discuss the types of projects and locations and settings that are covered by TPICS for Transit. Overall, the 27 projects show that there was some repre­ sentation by all types of modes (bus, bus rapid transit [BRT], light rail transit [LRT], and heavy rail transit [HRT]), among all regions of the United States, across a range of regions and mar­ kets, and with a wide range of costs. However, there was par­ ticularly strong representation by light rail projects (accounting for 50% of projects), and particularly weak representation by bus­only projects (only two projects). The study team sought to identify a short list of cases that would be most likely to be successful in terms of impact mea­ surement while preserving a reasonable mix of project types and locations. Preliminary research was conducted to deter­ mine the extent to which there are past studies that have already identified economic and/or development impacts. While there is no requirement that information be available from prior studies, the existence of previously collected information does indicate that the pilot case study effort is most likely to be suc­ cessful in assembling impact data and generating an interest­ ing story. That is a consideration when only a small number of illustrative cases are to be completed for this pilot demonstra­ tion. Eleven projects were eliminated because no prior impact information was located. Based on this review, 7 cases were selected; 6 from the 16 remaining cases and 1 project that was identified after the review process. These recommended projects were selected because (a) they all have employment or development impact information already available, and most have both, and (b) they represent a broad and even mix of project types and locations: • Mix of mode types: BRT (3), LRT (1), and HRT (3); • Mix of investment types: new service (3), line exten­ sion (2), station facility (2); and Table 2. Projects selected for case studies. Project Name Mode* City State Year Completed Cost ($Ms) Investment Type Arapahoe at Village Center LRT Greenwood Village CO 2006 $18 Station Los Angeles Orange Line BRT BRT Los Angeles CA 2005 $305 New Service BART Extension to Airport HRT San Francisco CA 2003 $1,552 Extension NoMa Gallaudet Red Line HRT Washington DC 2004 $120 Station Atlanta North Line Extension HRT Atlanta GA 2000 $463 Extension Boston Silver Line BRT BRT Boston MA 2005 $625 New Service HealthLine/Euclid Corridor BRT Cleveland OH 2007 $200 New Service Note: LRT = light rail transit, HRT = heavy rail transit, BRT = bus rapid transit.

11 of regions used was reduced to five by creating three combined regions: Rockies/West, Great Lakes/Plains, and Mid­Atlantic/ Northeast. The description in Impact Area is flexible and pro­ vides additional information on local area of impact for transit cases compared with the county perspective used for highways. Market Setting The market context of a project’s location can be an impor­ tant impact factor because the size of the market served by a given project would be expected to influence the magnitude of its economic impact. Market size is reflected in the definition of a Metropolitan Statistical Area (MSA) concept as defined by the U.S. Office of Management and Budget and adopted by the U.S. Census. Every county that is part of an urban area with 50,000 or more inhabitants and is connected economi­ cally to the surrounding area (based on commuting patterns) is classified as part of a metropolitan area. While the county level of analysis was appropriate for highway impact analyses for identifying Urban/Class Levels in TPICS for Highways, the study team determined that this would not be appropriate for transit projects. Given that the spatial scale of a county is relatively large in comparison with a transit system, narrowed criteria were added for this study so that project locations 2.3 Classification of Project Settings The case studies for both highway and transit projects share a common set of project descriptor variables, as shown in Table 4. The differences are minor and basically limited changing impact area descriptors and activity level measures to be relevant for transit projects. Construction and Analysis Periods An initial study date was chosen to be 1 year before the construction start date. If the construction period was very long and data availability was significantly better for a differ­ ent year near the time construction was initiated, this year was substituted. This year affected the collection of setting data and pre­project conditions. The post­construction study date was selected to be as recent as data availability allowed to best correspond with impact information collected in interviews. Location Regions are defined on the basis of the U.S. Department of Commerce’s Bureau of Economic Analysis (BEA) regions— which divides the United States into eight regions. The number Table 3. Transit projects types and modes for transit cases. Project Type Mode New Service Extension of Line Terminal Facility Service Improvement Bus Bus Rapid Transit Light Rail Transit Heavy Rail Transit Table 4. Case study project information elements—descriptors. Case Study Data Existing Highway TPICS New Transit TPICS Analysis Period Initial Study Date and Post Construction Study Data Same Construction Period Start and End Years, Months Duration Same Project Location Impact Area (County), City, State, Region, Latitude & Longitude Same, except impact area is a sub-county area Market Setting Market Size, Urban/Class Level, Airport Travel Distance Same Socio-economic Setting Population Density, Population Growth Rate, Employment Growth Rate and Distress Level* Same Project Cost Planned Capital Cost (YOE$s), Actual Capital Cost (YOE$s), Actual Capital Cost (constant $s) Same Project Size Length (miles) (not applicable for interchanges) Same (not applicable for stations) Activity Level Average Daily Traffic Average Weekday Riders * Note that a lower distress level indicates an improved economic condition.

12 factors that aided or impeded the project timeline, cost, or impact; 2. Project type—bus, BRT, heavy rail (commuter or inter­ city), or light rail or new service, service extension, expan­ sion, or operational improvement; 3. Location type—municipality, neighborhood; 4. Project motivation—e.g., urban growth management, job access, air quality non­compliance, and congestion mitigation; 5. Project cost—planned if available; 6. Construction period—start and end years; 7. Project size—passenger volume and capacity; 8. Transportation characteristics and impacts—pre/post­ transit system characteristics by mode, pre/post change in passenger volume and/or passenger­miles, comparison with previous modal options, if relevant; 9. Photo of the transportation facilities—if available; and 10. Suggested other contacts. In addition to local transit agency contacts, information was obtained or corroborated using FTA documents and the National Transit Database. (Note that the FTA is now compiling pre/post data on new starts, see www.fta.dot.gov/12907_9197.) Data Collection Step 2: Project Setting and Development Process Available public data sources were examined to obtain empir­ ical data (when available) to prove context and back­up the reported effects. The research analyst identified and attempted to contact at least three local informants: for example, a repre­ sentative of the local planning department, for the Chamber of Commerce, and for the economic development agency. Three perspectives were obtained to support completeness of data col­ lection and enable a “triangulation” of the appropriate valu­ ation of the project’s role in affecting the observed economic and development outcomes. The following was collected: 11. Location setting—area population level, density, employ­ ment, distress; could be classified as either within a “Principal City” or the suburban part of the MSA. Socio-economic Setting The economic distress metric used for this project is one of relative position in the initial study year (the year before project construction commenced). It is defined as the ratio of local unemployment to the U.S. level and must be at least 20% higher than that average to count as economically distressed. The 20% criterion was selected by the analysis team after observing that some counties have borderline conditions and flip back and forth between the distress and non­distressed categories from year to year. This helps to avoid distress classi­ fication changes associated with economic booms and down­ turns. Growth rates are calculated for the 5 years preceding the study period to provide context on the situation leading up to the project. 2.4 Information Collection Process Case studies required both empirical data and interview data to be compiled for the previously described settings and project characteristics data and the additional case study components of the TPICS databases listed in Table 5. The process for data collection had three major steps. Data Collection Step 1: Basic Project Description The research analyst reviewed existing published informa­ tion on the project to collect basic information and to gain some understanding to the project context. The analyst then contacted the transit agency (with a referral from APTA) to assemble additional details about the project. In some cases, this was referred to local planning department staff. The fol­ lowing is collected: 1. Description of project—short narrative, including name of project sponsoring agency and identification of Case Study Data Existing Highway TPICS New Transit TPICS Project Narrative Project motivation, history, impact factors, project role in outcomes <same> Further Documents Attachments and URL for external docs <same> Case Study Authorship Author name, organization, date <same> Pre/Post Conditions Local (municipal), county & state socio-economics Local (zipcode-based), county & state socio-economics, plus transportation conditions Project Impacts Direct and indirect economic impacts Direct impacts only Table 5. Case study project information elements—analysis.

13 All transit impacts were documented in immediate station areas. A buffer distance was not predetermined to apply to all projects so that local context could be considered. Impact col­ lection for TPICS for Transit relied more on interviews with local contacts and local sources than highway case studies because of the geographic scale of the cases. Because of the small geographies involved, little data is available through nationally available public sources that could be consistently used across projects. While highway projects utilized national databases to estimate impacts, for transit cases, this informa­ tion was only used to describe for pre/post conditions and not attributed to the project unless local sources specifically corroborated effects. The highway cases utilized county­level economic multi­ pliers that reflect wider regional impacts of major projects on business suppliers and worker income re­spending. The transit project cases do not use these factors to estimate indirect effects. The reason that these were excluded is that the transit projects are typically at a smaller scale than highways and are not neces­ sarily expected to have major impacts at a county­wide level. Because of the sub­county nature of most transit impacts, we did not utilize IMPLAN data to calculate project specific impacts on wages and business sales, but included this infor­ mation in the requests from local contacts. This led to fewer of the transit studies including this impact category. Project Documentation The research analysts assembled information from Steps 1 through 3 to prepare a succinct narrative concerning the project. Following the format of TPICS for highways, the case study documentation is be organized into six sections, including the narrative and • Project Characteristics—preceding Items 1–7, • Project Setting—preceding Item 11, 12. Pre/post economic statistics—pre/post change in employment, wages, business sales, property values, tax revenues—based on published databases; 13. Observed economic and development impacts— attributable to the project (same items as 12. Pre/post economic statistics above, plus observed square feet of development or private investment $); 14. Perception of the transit project’s role—in causing the observed economic and development impacts; 15. Identification of factors—that aided or impeded the project timeline, cost, or observed economic and devel­ opment impacts; and 16. Photos of development around the project site—if available. In addition to local planners, business groups, and eco­ nomic development agents, speaking to specific businesses and other government agencies such as departments of rev­ enue was sometimes helpful. Significant portions of setting and economic data were obtained from national data sources such as the Census Bureau, Bureau of Economic Analysis, and Bureau of Labor Statistics. Specific data products include the County Business Pattern’s zipcode­based tabulations; BEA’s CA1, CA4, and CA25N Reports; the Statistics of U.S. Busi­ nesses; the Census of Government’s State and Local Finance information; and the Local Area Unemployment Statistics series from BLS. Data Collection Step 3: Impact Analysis The impact measures for transit projects are confined to the direct development–induced changes, and reflect outcomes that are attributable to the projects as shown in Table 6. It is also important to note that the relevance of the various impact measures listed below, and the capability to effectively mea­ sure them varies depending on the scale of the project. Table 6. Case study economic impact measures. Outcome Measure Existing Highway TPICS New Transit TPICS Direct Employment Effect Change in direct jobs at project site and vicinity <same> Direct Economy Effect Change in wages & business sales calculated using IMPLAN data, or from local sources <same> Regional Economy Indirect impact multipliers (county level) -- Not applicable -- Private Investment Added sq. ft. of development, or $ of private investment in development <same> Capitalization of Private investment Change in property values <same> Fiscal Impact of Private Investment Change in state & local tax revenue generated in this area <same> Attribution of Credit to the Project % share of impact that is attributable to the project <same>

14 the role any of the projects has had on increasing transit use may help in gauging its importance with regard to develop­ ment. Many of these projects also provided major transporta­ tion efficiency benefits that were not a focus of the case studies. The BART extension to SFO, for example, serves a very high volume of travelers between the airport and other parts of San Francisco, saving people time, money, and hassle. However, these users provided little or no development impetus in the area around the new stations and, consequently, any economic impact related to their use was difficult to capture and beyond the scope of these case studies. Using station entrances and exits at new locations can provide good insight into the eco­ nomic role of a station in attracting new residents or employees, except in cases where stations have high numbers of transfers from outside the system, such as at SFO or when a station has significant park­and­ride volumes. The study team accord­ ingly focused on station area ridership counts and only made use of line ridership numbers for those cases that involved a new line with new stations. Table 8 provides an overview of the economic develop­ ment impacts of these seven pilot projects. Through research and interviews, nearby development projects were identified. When possible, the researchers used interviews to ascertain the portion of permanent employment change that was considered to be attributable to the transit project. Overall Findings Overall, the case studies showed wide variation in the num­ ber of jobs that were attributable to the transit projects and development around it. The most significant development and new employment following the opening of transit facili­ ties is seen in the NoMa Station and Boston Silver Line cases, where transit service improved access to underdeveloped land close to urban cores that would not have been able to develop as densely if they relied only on private vehicle commuting. Much less significant development occurred around stations and lines that passed through already developed residential • Project Impacts—preceding Items 13 and 14, • Pre/Post Conditions—preceding Items 8 and 12, and • Project Images—preceding Items 9 and 16. The narrative contains the names of the Research Analyst, Organization, Interview Informants, and external documents used and provides related web links and/or document attach­ ments. The next section reviews the online database in which cases are documented. 2.5 Case Study Results Site-Specific Findings Results of the seven pilot case studies are shown in full in Appendix C. A brief summary of key findings is provided here. In general, the case studies focused on measuring the economic development of areas adjacent to the transit sys­ tem investment sites or corridors. The focus was specifically on identifying the extent to which new jobs emerged (and new development occurred) in station areas that can reason­ ably be linked to new transit service. An effort was made to adjust the job impact estimates to net out effects of other fac­ tors that may have also helped generate employment in the station vicinity. The job numbers were also defined to ignore temporary infrastructure jobs, and they focused specifically on direct effects—that is, they did not account for multi­ plier effects such as additional indirect (supplier) or induced (worker spending) impacts on jobs in a broader surrounding region. Displacement effects (spatial relocations of business) occurring within walking distance of a transit station were netted out of the totals, although it was not possible to fully account for broader spatial shifts. Other real estate investment developments (usually a precursor to some if not all the job attraction) were also investigated and, when possible, data on dollars of investment and property values was also compiled. Table 7 provides information on transit facility utilization for the seven pilot projects in order to offer some perspective on the transportation impacts of the projects. Understanding Table 7. Transit facility utilization. Project Name Previous Local Service Volume Impact at Completion Most Recent Utilization Volume Arapahoe at Village Center 13,350 (1) 20,350 (1) Los Angeles Orange Line BRT 22,000 (3) 28,000 (3) BART Extension to Airport 3,000 (2) 8,000 (2) 21,000 (2) NoMa-Gallaudet Red Line 0 (4) 2,000 (2) 9,000 (2) Atlanta North Line Extension 8,750 (1) Boston Silver Line BRT 0 (4) 3,650 (3) 16,000 (3) HealthLine/Euclid Corridor 9,000 (3) 12,500 (3) 16,000 (3) Notes: (1) station daily entrances; (2) station daily exits; (3) line daily ridership; (4) local bus routes are busier today than prior to improvements, but are excluded from utilization figures for new facilities.

15 examples of multiple strengths. Not surprisingly, some char­ acteristics are correlated; for instance, a supportive business community is likely to be able to encourage more open zoning rules. Key observations are as follows: • A supportive business community can have an impor- tant influence on obtaining the maximum economic value from the transit investment. The NoMa–Gallaudet station in Washington, D.C., provides a clear example. Busi­ ness development organizations in this close­in region not far from Union Station were able to make a strong case for WMATA to add an inner city station at a time when the region was focused on a rail extension to Dulles Air­ port and the outer suburbs. The federal government also took advantage of the new station to locate some offices. Similar examples of strong business support can be found in Denver where the T­Rex project was built to provide service to the region’s Tech Center. Cleveland’s HealthLine along Euclid Avenue got its name from the hospital and health center at one end of the line rather than the origi­ nally proposed generic name of the Silver Line. This helped promote the major business activities located along the line and served to differentiate the operation from other transit services. In Atlanta, the business community in and around the Perimeter Center was a strong advocate for the extension of MARTA. • Zoning flexibility can be key and was mentioned in most of the case studies, including Atlanta; Washington, D.C.; Cleveland; and Denver. Of course, a successful zoning strategy also requires underlying development demand. • Connections to the rest of the regional transportation network can also be important. The ability to provide access across the region adds important potential develop­ ment energy. These connections need not rely exclusively on transit, however. Denver’s T­Rex included roadway improvements as well as a “call and ride” service to improve last mile access to the light rail line. Atlanta’s transit con­ nection to the Perimeter Center also benefited from nearby highway improvements. areas, such as the Los Angeles Orange Line and San Francisco BART airport extension. The HealthLine is part of a larger effort to revitalize inner city Cleveland that has increased its impact. The Arapahoe at Village Center Station, like the Atlanta North Line Extension’s two stations, largely serves corporate campus­ style office facilities on the urban fringe, which results in lower total development figures than transit services in denser parts of metro areas. A crowded commercial real estate market in D.C. also encouraged development around the NoMa Station, whereas consistent double digit vacancy rates in places like L.A. post­project slowed the demand for new commercial properties around stations. The recession in 2008 appears to have seriously slowed the development impacts of many of the studied transit projects. Even in areas such as the NoMa neighborhood where these effects were less pronounced, only half of planned develop­ ment has been completed in the 11 years since the station opened. This indicates that impacts may continue to grow into future years as planned projects “come off hold.” Fifteen years after the completion of Atlanta’s North Line Extension, companies continue to cite transit access as an important fac­ tor in their decisions to locate in Sandy Springs, Georgia— the city served by the new stations. Studying the economic development impact of transit is challenging because, in one sense, development may be most clearly considered a direct result of infrastructure improve­ ments if they occur within walking distance of stations, which is why a ¼­mile radius was typically considered. This guide­ line does not, however, preclude the potential for some tran­ sit investments to support or enable development benefits in locales elsewhere in the transit network, particularly insofar as the transit projects enhance connectivity and access to wider neighborhoods. Factors Affecting Local Development Impacts No single characteristic guarantees a strong positive eco­ nomic impact. Indeed, most of these case studies provide Table 8. Economic development impacts. Project Name Major Economic Sectors Affected Nearby Devel. (Sq. Ft.) Jobs Attracted Arapahoe at Village Center High Tech and Financial 775,000 1,005 Los Angeles Orange Line BRT Retail 1,300,000 825 BART Extension to Airport Services and Visitors None observed 0 NoMa Gallaudet Red Line Fed & Non-Profit Office 8,000,000 10,000 Atlanta North Line Extension Corporate Headquarters 500,000 750 Boston Silver Line BRT Class A Office 10,000,000 3,350 HealthLine/Euclid Corridor Healthcare, Education 380,000 1,360 Notes: (1) station daily entrances; (2) station daily exits; (3) line daily ridership; (4) local bus routes are busier today than prior to improvements, but are excluded from utilization figures for new facilities.

16 actually occur. They also show that economic development impacts are not always correlated with ridership changes. For instance, some projects with relatively high ridership (e.g., Los Angeles Orange Line and San Francisco BART to Air­ port) had relatively little immediate economic development impact, while others with lower ridership had more economic development impact (e.g., Washington’s NoMa–Gallaudet Station). The implication is that project impacts can look dif­ ferent depending on whether one focuses on ridership out­ comes, on economic development outcomes, or both. A much stronger and more nuanced base of insights will be gained as a broader set of case studies becomes completed later on. The next two chapters lay out the database, web tool design, and data collection processes that can be utilized to enable the assembly and use of a broader set of case studies in the future. Factors that slowed economic development impacts were the lack of conditions identified above as helping to stimu­ late local development—for example, there was a lack of local business interest in redeveloping areas surrounding new sta­ tions located along the BART line to San Francisco airport and the Orange Line in Los Angeles. In the latter case, strong local preference to continue the current style of suburban residen­ tial housing led to a focus of development opportunities at the existing business centers at either end of the line (rather than along the middle of the line). Altogether, these types of case study observations serve to provide both planners and interested stakeholders with a dose of reality—portraying both the opportunities to make a dif­ ference in economic development and the factors that must realistically be confronted to make desired new development