Economic Impact Case Study Tool for Transit (2016)

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25 C H A P T E R 4 This chapter lays out basic guidelines regarding how the case study database and web tool are intended to be used by transportation planners once there are more cases in the sys- tem. It draws directly from the guidance documentation that was originally developed for highways under SHRP 2 (EDR Group et al., 2012), but adapts that material to be applicable for transit projects. Additional training material is described in Appendix B of this report. 4.1 Guide to Using the System to Aid Planning and Policy Case studies in the current TPICS for Transit database are intended to support project screening and sketch-level planning. (Other potential uses of case study data are dis- cussed in Chapter 5.) In this context, a robust database with more observations will allow users to investigate the range of impacts from various types of investments in different set- tings. There are several ways in which such a case study data- base may be used; however, case studies should not substitute for careful local analysis of transportation and economic (i.e., real estate market) conditions and expectations later in the planning process. The case study database can be useful early in the plan- ning process to temper unrealistically optimistic or pessimis- tic expectations for a project. This information could be used internally and also when communicating with the public. Another potential use is to help define supporting strategies to bolster the economic development impacts of a transpor- tation investment. Many of the case study narratives describe additional land-use policies and business-development incen- tives that have worked in conjunction with the transportation investment to stimulate investment and job growth. The database web search feature can also be used to screen a range of alternative transportation investment proposals or schemes that an entity might be considering and to help iden- tify those most likely to result in positive economic benefits. Used in this way, the tool can help in programming invest- ments in a transportation improvement plan, particularly if economic development benefits to a region are an important consideration in the transportation programming. The case study database may also be used as a tool (not the only tool, however) for screening alternative proposals for a single transportation project. In an “alternatives analysis,” planners may be evaluating a range of transit project options, and the system can then be used to provide an initial sense of the magnitude of economic development impacts that might accrue from each of these alternatives. However, since TPICS does not measure efficiency and productivity benefits and because each investment is unique, that tool is not intended to be used as the sole measure of potential impacts in this type of analysis. Value of Combining Qualitative and Quantitative Information Case studies provide rich information for understanding how different types of transportation investments affect a local or regional economy. A database of case studies can pro- vide significant information about how economic impacts vary by project type, mode, location, size, and other char- acteristics of the setting and project. However, due to the range of local factors that may be applicable, it is difficult to draw strong conclusions about expected impacts of future investments based solely on the empirical data analysis. The case narratives are a key component of the case study data- base that include additional detailed information on other factors that affected project outcomes—namely economic development. A large base of case studies is required to enable the above uses. Even on the highway side, the current 105 highway cases are spread over 10 types of projects located in many differ- ent regions and settings, meaning that there are likely to be between 0 and 2 cases fitting any specific combination of Guidance for Web Tool Use

26 The case study database also does not attempt to cover eco- nomic impacts associated with changes to safety, air quality, noise and vibration, neighborhood cohesion, environmen- tal justice, and many other types of benefits or dis-benefits that are often evaluated as part of the environmental impact assessment of transportation investments. While there have been attempts to measure the broader economic effects of some of these impacts, they tend to have minimal direct impact on local economic development. Potential Challenges in Use of a Case Study Database Just as the highways cases discovered, the type of develop- ment impacts that TPICS for Transit compiles are most effec- tively gathered over a small geographic area. Single station analyses are much easier to carry out than analyses of many stations along a lengthy new line. However, from the highway experience, we also know that project isolation was valuable in attributing impact to a transportation investment. Because all seven of the transit cases were in urban cores or relatively dense suburbs, in addition to road access, a wide variety of other factors played a role in economic development in proj- ect areas. Because of this, it is even more important to read the narratives to understand the various factors involved in the case of transit studies. In the urban transit context, other public policies such as land-use planning may play a much more important role in economic development than for the typical highway project. Case study narratives should describe the policy context in which an infrastructure investment was made based on pre- existing sources and interviews. Those interview processes informed the impact allocation made in each of these case studies, but users of TPICS for Transit should carefully con- sider whether the interplay between investment and policy will have the same effects in their areas. Tabulated impacts are based on those impacts realized as of the date of project completion. Many of the seven case studies revealed that significant investment was still expected to occur, even more than 10 years after project completion. These impacts may be discussed in the narrative, but are less apparent. Planned development that has been delayed by macro-economic factors, for example, could turn a poorly performing project into a success story. Unless these projects are revisited in the future, these impacts will not be included in the tabulated statistics, even after they may have materialized. Because the transit projects’ completions fall largely within the years 2000–2010, many had development that was affected by the Great Recession of 2007–2009, which limited financing options for new building development. The recession may have also influenced the pre- and post-study years’ data. These fac- tors are something to consider when interpreting the “success project, region, and setting. Clearly the much smaller num- ber of transit cases that were developed for this study cannot possibly offer the depth necessary of a database to start com- paring directly with proposed projects. These seven cases do, however, show the importance of collecting as much qualita- tive data as possible to help understand project impacts that may be compiled from quantitative data. Each of the seven projects fits into a broader picture showing the policy, trans- portation, and economic context of each location. Type of Impacts Economic development impacts can be measured in terms of changes in jobs, wage income, business revenues, and tax revenues generated or in terms of the value of business invest- ment. Impacts on land development that are associated with those same economic impacts can be measured in terms of square feet of development, value of investment, change in assessed property values, or change in the value of land or building sales. The current case studies relied heavily on the permanent employment impacts because municipalities and economic development officials collect data on and report on employ- ment impacts more frequently than on other impacts. These case studies focused on identifying the magnitude and pat- tern of economic development impacts associated with transit enhancement projects. When possible, they included changes in building construction (represented in terms of square foot- age) and land values. They do not directly measure the eco- nomic value of efficiency benefits such as travel time savings, operating cost savings, and reliability improvement as well as productivity growth associated with increased accessibility and efficiency of business operations. In theory, travel efficiency benefits and access enhancement benefits are the drivers of business expansion and investment, which in turn enable other economic development impacts. For a transit project with a small, local neighborhood of analysis, even changes a few miles away may not be identified through interviews with local officials and businesses, nor measured by local economic growth data. This is also a reason why the economic impact of residential construction is difficult to measure despite being a significant component of development around many transit projects: presumably, residents are relocating to these new neighbor- hoods to take advantage of some access or efficiency improve- ments, but the associated job and income impacts are diffuse and difficult to measure or attribute. To capture broader, regional economic impacts from changes in transportation efficiency, modal access, and neighborhood choice, other models and tools (beyond direct case study observations and interviews) are likely to be required.

27 of building construction, and value of investment in terms of construction cost. • Time Periods: typically, “pre-project” data is collected for the year before construction begins, while “post-project” data should be collected to correspond with the latest data available unless complete build-out of a project region was completed in an earlier year and there has been no development attributable to the project since then. • Employment: measured by place of work—that is, it rep- resents the number of people working at locations within the study area, regardless of where they live. It should not be confused with data on employment by place of resi- dence, which represents a measure of local labor force. Average worker income is similarly measured by place of work. This requires the use of different data sources than population data. Interview Data Collection Due to the small geographic areas that a transit improve- ment is expected to serve, determining impacts require local information (such as property values and building construc- tion information). The case studies should include infor- mation about causal factors affecting real estate project impacts (including supporting infrastructure, land-use poli- cies, and business programs). To obtain this local informa- tion, the researcher must conduct interviews with key public officials (e.g., local or regional planning agencies) and private- sector representatives (e.g., Chamber of Commerce or devel- oper types), as well as review available local documents. The outcome of the interviews should be a coherent narrative describing the planning, implementation, and results of the project. The questions do not need to be followed verbatim; they are simply guidelines for the types of information to be collected. Interviews are generally more effective if they are conversa- tional as opposed to asking a numbered series of questions. Therefore, interviews should begin with an explanation regarding purpose and use of the case study database and why there is interest in this specific project case. Questions should be amended or added based on issues identified from the background information. The interviews focused on filling in missing pieces of empirical information about project outcomes and additional explanatory insight into causal factors affecting those out- comes. A minimum of three interviews (one from each type below) should be conducted for each case study: 1. Staff of the transportation agency that built the project to provide project characteristics, pre/post transportation data, and information on notable aspects of project plan- ning and implementation; of a case” or later drawing comparisons with other similar proj- ects that were anchored at a different time. This temporal dif- ference makes comparisons between case studies difficult and must be considered when using the database to make planning decisions. 4.2 Guide for Collection of Additional Projects The usefulness of a database of transit case studies will clearly grow with the addition of more cases. The first step in developing a new case should be to review existing case studies to understand the type of data required, some of the main data sources, and how the information collected will be presented. In addition to the 7 transit cases, the 105 high- way case studies of projects throughout the United States can help in developing this knowledge of the case study structure. Preliminary and Quantitative Data Collection As a starting point for each case study, it is useful to gain an understanding of the context in which the project has been introduced and matured. An internet search should be under- taken to gain general knowledge of the project and the region in which it was built. Good places to start include wikipedia .com, aaroads.com, and state DOTs’ websites, as well as local economic development agencies’ websites. A web search of the project itself can also turn up environ- mental impact reports and other project-related documents, as well as newspaper articles about the project. It is also useful to search the name of the community and any development projects related to the investment of which you are aware. The literature search will provide the researcher with a general understanding of the project and can be used to help tailor interview questions to collect the best information for under- standing the project and its impacts and for relating the story of the project in the project narratives. Any useful documents or websites should be recorded for entry into the system. In addition to basic project details and context, online sources can provide background demographic and economic data on the local, countywide, and statewide basis needed to populate the database. The researcher may not be able to fill in all fields; that is acceptable, although he should try to fill in as much as possible. Data sources are listed in the Database Dictionary (see Appendix A). Additional definition clarifica- tions are provided below: • Impact Area: the neighborhood(s) or part(s) of the metro area that the project affects. • Impact Measures: employment, income, output/business sales, property values, tax revenues generated, square feet

28 tacts may be necessary to identify impact numbers based on a situation described by a prior contact. Case Analysis and Assembly Based on information collected in interviews and project- specific or local research, the most important analytical step in the case assembly process is the determination of economic impact. The attribution of causality for observed economic impacts is an important consideration. Not all new jobs, building development, tax revenue, and so forth are neces- sarily due to the transit project. There are many other fac- tors that may have come into play during the construction period that may have had nothing to do with the project. Interviewees may be hesitant to make statements regarding attribution, but questions which suggest percentages or magni- tudes may help acquire some information, which may be corrob- orated or contradicted by other sources. Sometimes quantitative attributions may be possible if there were other infrastructure improvements made at the same time as the transit project. Because of the local nature of transit-supported develop- ment, unlike highway cases, it was not reasonable to work from county or regional data in order to make impact calculations. All impact information should come from sources that directly address the project and project area—either documents or interviews—unless impact areas align well with publicly avail- able data for small, local geographies. For example, the Boston Silver Line case utilized zipcode-based County Business Pattern data because the 02210 zipcode aligned almost exactly with the affected area. Future case studies may be able to rely more heavily on zipcode-based county business patterns (CBPs) data and, especially, Longitudinal Employer-Housing Dynamics (LEHD) data from the U.S. Census (as was done in two of the seven cases). Potential cases with an initial study dates after 2002 would be conformable with the U.S. Census Bureau’s OnTheMap version of LEHD data. This could be a powerful tool for establishing local impact baselines. Validation with local sources and acquiring attribution figures are essential when using public data. Examples of useful documents include news stories and press releases, but also special local master planning documents or related studies, and local records of land valuations and tax receipts. Direct impacts in terms of jobs can also be estimated if the researcher obtains information on the square feet of new development built as a result of the transportation improve- ment. Sources such as the Urban Land Institute report on typical ratios of workers per 1,000 sq. ft. of occupied build- ing space. These estimates vary, but are typically in the range of 1.0 for warehouses, 2.1 for industrial space, 2.2 for retail space, 4.2 for office space, and 0.7 for hotels. A full understanding of the impacts of a transportation investment requires not only quantitative impact analysis, but 2. Staff of the local or regional planning agency to pro- vide information (and refer us to other appropriate data sources) on changes in local land use and development and the relative roles of the highway project in affecting it; and 3. Staff of a chamber of commerce or local economic develop ment agency to provide information on how the transit project affected business growth and investment and its role relative to other local initiatives and factors. Some questions help to gather more empirical data. If the researcher already has some project-related data, then ask the interviewee to validate or elaborate on it. When data is scarce before the interview, ask the interviewee whether they can assist with the missing data. It is always useful to get qual- itative information to reinforce (or, if necessary, to substitute for) empirical measures. Questions include the following: • What are the land use changes as a result of the project? • How has the project affected property values? • How have property sales or building permits been affected by the project? • Has there been any new construction activity as a result of the project? • How much of the neighborhood’s post-project economic performance can be attributed to the project? • How has the project affected the capacity for future development? • Do the impacts accurately describe the influence the project has had on the area? • What was the neighborhood’s motivation for the project? (Questions also need to collect information on neighbor- hood context and project motivations.) • What is the local community involvement in the project? • What were the roles of various stakeholders and public agencies in supporting or modifying the project? • What is the size of the project’s area of influence? • What were the key motivations driving the need for this project? • Were economic and land development considerations con- sidered or analyzed in project planning and implementa- tion? (Obtain a copy of any study that was done.) • Are there any other key analysis issues or performance measures used in the project prioritization and planning processes? • What are the societal or environmental implications of the project (i.e., emissions, safety, sprawl)? When possible, interviews should end with request for additional contacts if contact has not been made with at least one person in each of the three categories. If possible, additional interviews with businesses or other specific con-

29 because it is not reported in a centralized source or consistently from one state to another. Within the United States, and even within states, there is no single agency charged with economic intervention or provision of financial/business attraction incentives. In fact, such efforts often come from multiple levels of government with varying degrees of coordination. Further- more, economic development intervention and support poli- cies are heterogeneous, ranging from streamlined permitting processes, to shovel-ready sites, to tax credits and direct cash transfers. Sometimes such support is tracked either formally or informally by an economic development agency, but because support can come in so many forms and from so many differ- ent entities, it can be difficult for a researcher to identify all of the agencies with relevant information. The interview process can help with this task, but if the infor- mation is scattered across numerous agencies, the level of effort needed to obtain complete information can become substan- tial. Because of the small geographies for which transit impacts are relevant, even agencies with sophisticated GIS-based data- base systems may find it overly time consuming to do special- ized data runs; others have very basic systems, while others with more basic systems would find it completely infeasible. Although planning and land-use context information is often available in database form, it is not generally available as time-series data. A researcher interested in a particular project can obtain current land-use information from the planning department covering the project area. If the project crosses city or county lines, the researcher may have to visit several planning departments. It is also unlikely that the plan- ning department can provide land-use data covering previ- ous periods, making before/after changes to land use difficult to determine other than anecdotally. Data tracking total commercial space before and after a project typically lacks a centralized source and lacks consis- tency. Commercial real estate broker firms often collect data for the larger real estate markets reflecting total space, rents, and vacancy levels by product type. However, they do not typically maintain time-series data and are likely to charge a fee for any information. Even if they do agree to share data on commercial space figures, market and sub-market definitions used by the data source may not match those relevant to the project of interest. Data covering property values and property taxes can be obtained from a centralized source, but neither assessed value nor tax collections data are defined consistently across juris- dictions. First, obtaining property value from the tax assessor is problematic because each jurisdiction assesses property value differently. Therefore, it is not enough for a researcher to simply collect property value data from a local assessor’s office; the researcher also needs to understand the local system concerning how property values are assessed (i.e., full, partial, or statutorily) and how often assessed values are updated. also a distillation of project context findings from interviews, local data sources, and prior studies. The narrative should be a relatively brief (three to five page) story of how the project came about and its impacts on the local area. The structure should be in the following order: 1. Synopsis: Create a one-paragraph summary of the project history and its outcomes, including a description of the project, its location, dates of construction, project cost, and impacts in terms of jobs or types of businesses attracted. 2. Background: Describe the local project context, including a brief economic history of the region, population, and employment trends; a description of major transporta- tion routes and facilities that serve the area; and travel time to nearest commercial airport and other transportation features. 3. Project Description and Motives: Describe the project (i.e., type, cost, etc.) and why it was built, including motiva- tions of the different involved parties. 4. Transportation Impacts: Discuss implications of the project on local transportation such as changes in average annual daily trips, travel-time savings, or other factors. 5. Demographic, Economic, and Land-Use Impacts: Discuss pre- and post-construction data and impacts attributed to the project such as new firms attracted and retained and changes in employment changes, land use, and land development. 6. Non-Transportation Factors: Discuss other factors that influenced project outcomes (e.g., supportive policies and incentives); if several factors combined with the transpor- tation investment to create a climate for economic growth, then transportation investments can only be attributed a portion of that growth. The allocation of causality for each project should be discussed with interviewees. 7. Resources and Citations: List the studies and links to websites used in the case study. 8. Interviews Conducted: List the organizations participating in the interview process. The narrative should supplement the case study data tables and should provide explanations and additional information as well as being a relatively complete, free-standing document on the project. Challenges While much of the requested data for case studies can be relatively straight forward to collect, the availability of some data elements varies from project to project. The level of effort needed to collect each data element also varies by project type and scale, although certain elements are particularly elusive. Economic development policies, interventions, and support are a perfect example of information that is difficult to collect

30 Total dollars of investment are also difficult to compile because there is rarely any reason to collect this information in a centralized location. Except in cases where a local group or agency has taken special interest in this figure, the researcher may need to identify several of the major development proj- ects and may need to reach out to developers to begin assem- bling this type of information. All of the above must be considered in the context of the larger data collection effort. The researcher organizing each of the above may be collecting dozens of other pieces of data from a broad range of sources, sometimes from multiple juris- dictions and sub-jurisdictions for many projects across the country, all under time and budget limitations. Because of the variety of data sources, it may be efficient for a single researcher or team of researchers to collect data on multiple cases at once so that they may become familiar the data sources and for- mats involved. This research is also preparation for conducting the corresponding number of interviews as it provides project context and can facilitate the dialogue with key contacts. Analysis of property tax data can also be problematic because property tax rates are subject to change from year to year. Thus, in addition to property tax associated with a particular prop- erty or total property tax for a jurisdiction, the researcher needs to know the prevailing tax rate for each time period for which data are collected to ensure that fluctuations are the result of actual changes in underlying property value and not simply a change in tax rates. Many jurisdictions also have varying tax rates based on property type or even use intensities. Broker interviews can be used to get a general sense of cur- rent property values, but few brokers track property values over long periods of time. Data on property values also were rarely available in a data form that could be compared across time. Many of the agencies housing this information have not converted to electronic databases; some may have electronic records available, but only for the most recent property assess- ment, and only searchable by very specific criteria. Any new development typically replaced the records of the preceding property value.