Interactions Between Transportation Capacity, Economic Systems, and Land Use (2012)

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12 C h a p t e r 3 Case Study Selection process The case study selection process was based on the application of criteria described in the preceding chapters. In addition, the project time period was considered insofar as it affected the availability of pre- and postconstruction impact data. The result was a multistage process designed to ensure a represen- tative mix of cases and meaningful range of project types for imputing economic impacts. Identification of Candidate Cases The first step in the case selection process was to assemble a list of candidate highway capacity projects. To accomplish this, the research team queried state transportation depart- ments for lists of highway projects that (1) represented new highways or major extensions, expansions, or performance enhancements to existing highways; (2) were completed at least 5 years ago; and (3) represented a significant magnitude of investment (defined as more than $10 million in cost). Altogether, 138 candidate projects were identified in this way. Some highway projects were originally considered by the study team but ultimately not included because of the project timing. Major highway projects are often planned 5 to 10 years in advance, require 1 to 10 years to complete, and subsequent economic development impacts can unfold over another 5 to 10 years after construction completion. Projects completed less than 5 years before were not considered because they were deemed too recent to allow determination of the full impact of the project. Projects completed more than 20 years before were dropped from consideration because of the dif- ficulty collecting data on preproject conditions and finding interviewees who could report on before and after land use and development changes and disentangle observed changes from extraneous factors over time. The second step was to identify previous economic impact studies of before and after conditions that could be candidates for updating and inclusion in the case study database. They were: • Major highway projects. Federal Highway Administration— 2005 study that included before and after evaluation of seven rural interstate highway projects. • Urban highway interchange projects. Pennsylvania Econ- omy League—2000 study that included before and after assessment of seven highway interchange projects. • Small town bypass projects. California DOT—2006 study that included before and after meta-analysis of 134 town bypass projects conducted by state DOTs in Virginia, Indiana, Wisconsin, California, and Montana. • Industrial access road projects. Appalachian Regional Com- mission, Public Works Program evaluations conducted in 1999 and 2007 that included before and after evaluation of 199 access road projects in 13 states; plus Oregon Depart- ment of Economic Development 2006 study that included before and after evaluation of 56 access road projects. Ranking Candidate case studies were ranked by age, level of data com- pleteness, and expected level of effort required for comple- tion of before and after data. Some cases were discarded at this point; they were nearly all bypass and access road projects identified in the previous literature of meta-analyses but deemed too old or with too little detail to be considered for case study updating. Remaining cases were evaluated in terms of the availability of economic impact data. Rankings were done based on the number of impact measures available, and that led to three tiers of cases: • Tier 1 cases (totaling 70) were recommended for initial data collection. This included 24 cases that had data from previously conducted before and after impact studies or were deemed to be easily updated so that before and after Case Selection and Data Collection

13 construction impacts could be developed quickly. It also included 46 cases in which there was a reasonable amount of impact data available and before and after construction impacts were deemed likely to be collectable given the level of detail and documentation available from other sources. • Tier 2 cases (totaling 21) were considered viable case studies, although they would involve a larger amount of research for impact measures and qualitative information. • Tier 3 cases (totaling 87) were deemed to be less suitable for case study because they lacked sufficient data for a case study because of a lower availability of project documenta- tion and information on construction costs and timing. Initially, 60 case studies were conducted; all were selected from Tier 1. Subsequently, additional funding became avail- able to add 40 more cases. They included 21 additional high- way cases selected from Tier 1 and Tier 2, plus 19 intermodal terminals that were added later. All these latter cases involved interchange between highway and rail modes, including “pas- senger intermodal facilities” (which were rail transit stations with highway access) and “freight intermodal facilities” (which were truck or train transfer facilities for freight con- tainers). The added cases were selected to maintain the same wide distribution among geographic regions and settings. process for Collection of empirical Data All of the case studies required empirical data on impact measures relating to economic development and land devel- opment. They also required empirical data on attributes of the projects and their settings. Specific types of empirical impact measures that are appropriate for the case studies are shown in the lists below, which were developed on the basis of recommendations in the 2001 FHWA guide Using Em- pirical Information to Measure Economic Impact of Highway Investments (1). Project Data The first type of data is the set of project descriptors: 1. Description of project (short paragraph); 2. Project type (highways, widening, bypasses, connectors, interchanges, bridges, beltway, access road, passenger intermodal, freight intermodal); 3. Project motivation (e.g., access, site development, labor or delivery markets, tourism, congestion mitigation); 4. Project cost (planned if available); 5. Construction start and end years; 6. Project sponsor (if applicable); 7. Case study author; 8. Postconstruction study date; 9. Project magnitude (length, lane miles); 10. GIS latitude and longitude coordinates; 11. Related links; and 12. Relevant attachments. Location Classification The next most critical set of project characteristics is the set of project location (setting) indicators because these factors (along with project type) provide the core options for an ini- tial search by a user of the T-PICS system. 1. Region; 2. Urban/rural class (Census designation); 3. Population density (population per square mile); 4. Economic distress (unemployment level relative to national average); 5. Employment growth rate (± percent annually); 6. Population growth rate (± percent annually); 7. Economic market size (population within 40 minutes); 8. Airport travel distance (minutes); 9. Travel distance to interstate (minutes); 10. Travel distance to major market (minutes); and 11. Extent of mountain terrain (land surface rating: 1 to 21). Impact Measures Each team member collected before and after economic impact data and interviewee reporting of project impacts for as many impact elements as was practical. The impact ele- ments are listed below. Through the local interview process, additional effort was made to estimate the portion of observed economic change that could be attributable to the highway project. 1. Per capita income; 2. Economic distress (unemployment level relative to national average); 3. Number of jobs in the area (direct and total jobs impacts); 4. Population; 5. Wages and other income (per capita or per worker; direct and total wage impacts); 6. Business sales (output; direct and total output impacts); 7. Population density; 8. Capital investment (dollars; direct and total investment); 9. Property values (aggregate total value change [dollars] in study area); 10. State, local, and federal tax revenues and costs (direct and total tax revenue); and 11. Annual average daily traffic count (AADT).

14 Wherever applicable, the data were collected at the local (metropolitan or smaller), county, and state area level. Case Study Interviews Although a significant part of the empirical impact data were collected via public sources (as listed), some types of impacts required local information. The case studies also include information about causal factors affecting project impacts (including transportation programs and nontransportation considerations). To obtain this local information, the case studies relied on interviews with local private-sector and public-sector participants and observers, as well as a review of available local documents. The product of the interviews was to obtain additional information on impact measures and develop a coherent narrative describing project planning, implementation, and results. Types of Interviewees The interviews focused on filling in missing pieces of empiri- cal information about highway impact outcomes, and addi- tional explanatory insight into causal factors affecting those outcomes. A minimum of three interviews (one from each type below) were conducted for each case study. 1. Staff of the transportation agency that built the project. To provide project characteristics, before and after transpor- tation data, and information on notable aspects of project planning and implementation. 2. Staff of the local or regional planning agency. To provide information (and refer us to other appropriate data sources) on changes in local land use and development, and relative roles of the highway project in affecting it. 3. Staff of a chamber of commerce or local economic develop- ment agency. To provide information on how the highway project affected business growth and investment, and its role relative to other local initiatives and factors. Interview Questions A number of questions were asked to gather more empirical data. If the before and after data were already available, the project team asked the interviewee to validate or elaborate on the data. When data were not available, interviewees were asked to provide the data. In both cases, it was useful to get qualitative information to either reinforce or substitute empirical measures. The questions included the following: • Describe the land use changes as a result of the project. • How has the project affected property values? (before and after measures) • How have property sales or building permits been affected by the project? (before and after measures) • Has there been any new construction activity as a result of the project? (before and after measures) • How much of the before and after impacts are attributed to the project? (go through the list of available impacts data) • Do you have other before and after measures available? (go through a list of impact measures that you do not have) • Do the direct impacts and total economic impacts accu- rately describe the influence the project has had on the area? (go through the list of economic impacts) Special Aspects of the Project Setting and Planning These questions focused on planning and development issues to provide more context for the project’s existence and impact. • What were the key motivations driving the need for this capacity improvement project? • Describe the societal or environmental implications of the project. (emissions, safety, sprawl) • How has the project affected the capacity for future development? • Describe the local community involvement in the project. • What were the roles of various stakeholders and public agencies in supporting or modifying the project? • Describe the size of the project’s area of influence. • What were the economic and land considerations in proj- ect planning and implementation? • How were economic and land development considerations analyzed? (try to get a copy of any study that was done) • How were these considerations communicated to the public? • Describe any other key analysis issues or performance measures used in project prioritization and planning processes. Lessons Learned A final set of questions was included to help in gathering ideas for future research on transportation projects. • What impact measures or procedures do you think need to be addressed better or differently in the future? • What types of impact data do you think are missing or unreliable? • Do you agree with how the impact measures were estimated?

15 Organization of Data for analysis The information gathered for each case study was organized in a manner that could be entered into the electronic database and become accessible for users to view. For each project that a user selected, the following data were compiled: • Characteristics of the project. Description of the project, project type, length, AADT, years constructed, and so forth. • Intermodal volume. For passenger and freight intermodal projects, a description of freight volume or passenger move- ment at the project location. • Characteristics of the project setting. Description of the project setting, including the urban/rural, economic dis- tress, and so forth. • Before and after conditions. Data showing the before and after measures for the region’s economy. • Case study narrative. The full project narrative developed from the interviews. • Project impacts. A table of the specific economic impact findings for the project along with the relevant areas of impact. reference 1. Economic Development Research Group and Cambridge Systemat- ics. Using Empirical Information to Measure Economic Impact of Highway Investments. 2 vols. Prepared for FHWA, U.S. Department of Transportation, 2001.