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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
×
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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
×
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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
×
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Suggested Citation:"Chapter 2 - Analysis Methodology." National Academies of Sciences, Engineering, and Medicine. 2019. Guidance for Calculating the Return on Investment in Transit State of Good Repair. Washington, DC: The National Academies Press. doi: 10.17226/25629.
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7 C H A P T E R 2 This chapter describes the methodology for calculating the return on investment (ROI) of transit agency projects and programs to maintain or achieve a state of good repair (SGR) for their physical assets. The methodology is intended for use by a transit agency attempting to justify SGR investments and/or to compare ROI of SGR investments with that of other invest­ ments, such as investments in system expansion. Note the methodology is informed by the literature review described in Appendix A. The remainder of the chapter • Provides an overview of the benefits and costs of investments made by a transit agency to achieve and/or maintain SGR; • Presents key concepts underlying the methodology; • Details the recommended methodology for estimating agency costs, user costs, travel demand, and social and environmental costs; and • Discusses metrics for summarizing the results of an ROI analysis. Overview of Benefits and Costs of Transit SGR Investment Continued investments to maintain transit assets in SGR allow for the safe and reliable operation of transit systems. If regular investments are not made, however, and asset condi­ tions deteriorate, the performance of the transit system is compromised. In the near term, a decline in the transit system’s performance affects existing users, who experience travel delays and reduced service reliability. Degrading and aging assets also cause maintenance costs to rise, increasing overall costs to the transit agency. Over time, as asset conditions continue to deterio­ rate, incident delays and unpredictable travel times become the norm rather than an occasional nuisance. Users tend to experience crowded conditions at transit stations and in the vehicle, resulting in negative perceptions about the transit travel experience. Transit becomes less attractive and transit ridership may begin to decline. Riders either forgo their trips or shift to other modes of transportation, often changing to the automobile to complete their trips. Figure 2­1 illustrates a conceptual ridership trend as asset conditions deteriorate. With new or near­new assets, the ridership trend in the figure shows a slow increase. At this stage, physical asset deterioration has no significant impact on the ridership trend. When asset condi­ tion declines and reaches a certain threshold due to deferred maintenance (shown as the trend line enters the Asset Deterioration section of the figure), ridership begins to decline as well. However, if the transit system is maintained in SGR, the ridership trend may continue to follow the initial trajectory. In this example, the trend continues increasing. For some transit agencies, the trend line may be flat—or even decreasing—depending on other factors such as population changes in the area. Analysis Methodology

8 Guidance for Calculating the Return on Investment in Transit State of Good Repair It should be noted that while the figure and the discussion above show a ridership decline because of asset deterioration and a lack of investment in SGR, this may not always be the case. This assumption is valid for choice transit riders, who can switch to other modes of transportation if the deteriorating conditions severely affect their experience. However, captive riders—those without another option for transportation—may continue to use the system regardless of the condition of the assets and the impacts on system performance. Improvements in condition may result in an increase in ridership, though this increase may also depend on the degree to which a transit system’s users are choice versus captive riders. Figure 2­2 shows the overall economic benefits and impacts of transit SGR. The arrow at the top of the figure indicates that the severity of the impacts increases as a transit system starts Figure 2-1. Conceptual ridership trend. Figure 2-2. Overall economic benefits and impacts of transit SGR.

Analysis Methodology 9 in a state of good repair and then deteriorates over time. As depicted in the figure, declining asset conditions may affect system performance, resulting in impacts to transit users, the transit agency, and society as a whole. There may also be additional economic impacts resulting from a change in SGR. The various types of impacts may occur beginning in the short term from declining asset conditions and/or long term as the short­term impacts lead to longer­term reductions in ridership. The degree to which this shift in modes occurs depends on a number of factors, not the least of which is the extent to which a transit system’s passengers are “choice riders” versus “captive riders.” User impacts shown in the figure include the following: • Effective Journey Time (EJT). This is an overall measure of the quality of a transit user’s trip incorporating the actual time required to make the trip, with adjustments for the quality of that time. EJT thus incorporates the following components: – Travel Time. For rail travel, deteriorating track conditions can result in lower operating speeds and longer travel times than originally designed. While tracks are repaired, trains may be required to run on a single track, further increasing travel time for passengers. Travel time can also be impacted by malfunctions in transit signal systems, necessitating the use of manual signaling for safe navigation and coordination among transit lines. For bus operations, travel time largely depends on traffic conditions and road conditions outside the control of the transit agency and thus largely unrelated to the state of repair of the bus fleet. However, in cases where buses operate on a transit agency’s dedicated guideway, the same relationship described above applies. – Reliability. Transit service disruptions due to aging and impaired assets cause inconsistent day­to­day transit travel times. In such cases, users have to build in larger time buffers for travel to ensure on­time arrival. It is important to note that a wide variety of other factors impact reliability as well, such as the level of congestion, operating practices, and other characteristics not directly related to SGR and, in many cases, outside of the transit agency’s control. – Incident Delay. As asset conditions deteriorate, the frequency and magnitude of malfunctions, mechanical issues, and required unscheduled maintenance activities within the transit system increase. Such incidents disrupt transit service, causing delays to passengers at the location of the incident. For rail passengers, this also causes delays at downstream transit stations as increased wait times cascade through the network. – Crowding and Discomfort. This can result from incident delays and increased travel time. Malfunctions and mechanical issues that arise as a result of deferred maintenance also lead to shorter rail consists and crowding of passengers. Long wait times at stations due to delay and reliability issues increase passenger discomfort as well. • Operating Costs. Transit users who shift from transit to automobiles experience an increase in operating costs. These include fuel costs, automobile maintenance, parking, and other expenses. • Perceptions of Safety and Other Factors. There may be a safety impact to transit users that shift from transit to automobile, to the extent that the likelihood of crashes and associated deaths, injuries, and property damage on regional roadways increases with more road users, increasing potential for traffic accidents. In addition, transit users remaining on a system that has fallen out of SGR may perceive the conditions to be unsafe or insecure. Transit users’ perceptions of safety, security, and other factors can be incorporated into the EJT measure described above. Operation impacts required to avoid a decrease in safety are included in the EJT measure as well.

10 Guidance for Calculating the Return on Investment in Transit State of Good Repair Although not shown on the figure, there may be additional health and recreational benefits resulting from increased transit use, to the extent that using transit leads to increased walking and cycling. For the transit agency, deteriorating asset conditions can result in increases in Capital Costs, as it may be more expensive to address deferred conditions. A transit agency may also incur increased Energy Costs from operating assets beyond their useful life, and Other Operating and Maintenance Costs may increase for operation of assets not in good repair. As ridership declines in the long term, there may be additional impacts to other parties besides the transit agency and transit passengers. These are referred to as “non­user,” or social and environmental, impacts. The impacts depicted in the figure include • Increased Emissions resulting from increased fuel consumption of transit vehicles and the mode shift from transit to automobiles; and • Increased Automobile Congestion, or the increase in travel time and operating costs to other automobile users besides those shifting to or from transit due to automobile traffic. The impacts discussed above (near­term and long­term impacts) have associated quantifi­ able costs that can be included in a benefit–cost analysis (BCA). The impacts that may result in a change in travel demand are captured in the EJT measure, and the extent to which travel demand changes determines the magnitude of other impacts (e.g., operating costs, emissions, and congestion). Financial impacts that are not included in a BCA but are still important impacts of deteriorating assets are those related to jobs and tax revenues. These can be quan­ tified through an Economic Impact Analysis (EIA). Key Concepts The methodology recommended for the calculation of ROI for transit SGR investments is an adaptation of traditional BCA. Application of BCA principles to ROI analysis is recommended for public projects in references such as the final report for National Cooperative Highway Research Program (NCHRP) Project 8­36, Task 62, Best Practice Methodology for Calculating Return on Investment for Transportation Programs and Projects (1), TCRP Report 78: Estimating the Benefits and Costs of Public Transit Projects: A Guidebook for Practitioners (2), and NCHRP Research Report 866: Return on Investment in Transportation Asset Management Systems and Practices (3). Key concepts applicable to an ROI analysis are summarized in NCHRP Research Report 866 and reproduced in Figure 2­3. 1. Benefits and costs should be expressed in dollar terms whenever possible. Those that cannot be quantified should be assessed qualitatively. 2. All benefits and costs should be measured relative to a counterfactual base case that is consistently defined. 3. Future benefits and costs must be discounted to their present values to allow comparisons across time. 4. Benefits and costs should be considered from a broad societal perspective and estimated separately for the transit agency, transit system users, and society. 5. The value of investments is assessed through comparisons of total benefits to total costs. Figure 2-3. Analytical methodology: key benefit–cost concepts. (Source: Adapted from NCHRP Research Report 866)

Analysis Methodology 11 A critical issue in analyzing ROI of SGR investments is defining a meaningful base case. Traditionally, BCA compares a case in which an investment is made to a base case of “no invest­ ment.” In such an analysis, it is generally taken for granted that needed maintenance, repairs, and rehabilitation work will be performed following an initial investment. Future SGR­related costs are an explicit input, if they are considered at all, and the possibility that a new investment may be allowed to fall into disrepair is generally not considered. This creates two problems: 1) a traditional BCA provides little insight concerning how to model costs and effects of SGR­related investments; and 2) the benefits of SGR may be understated, as maintaining SGR is essentially taken for granted. These issues can best be addressed through careful consideration of how the base and investment cases are defined and through using a consistent base case across analyses of multiple investments. Table 2­1 lists potential base and investment cases a transit agency may wish to consider. The basic approach recommended is to define a base case that represents current practice and an investment case that represents a change in approach, which may be either additional invest­ ments or a disinvestment. In the case of analyzing disinvestment, the analysis will typically show a disbenefit (increased cost) resulting over time from an initial savings in agency costs (from not performing needed work). Another issue with a traditional BCA is that the consideration of social and economic impacts is generally limited to direct costs. For instance, an analysis would generally consider travel time and vehicle operating cost savings yielded by a new investment but not the resulting job growth or economic impacts. The next section describes an approach to addressing these impacts through supplemental analysis building on the approach detailed in a report prepared for TCRP Project J­11, Task 7, titled “Economic Impact of Public Transportation Investment” (4). This report was originally prepared in 2009 and was then updated by the American Public Transit Association (APTA) in 2014 (5). Scenario Base Case Investment Case Potential Issues Programmatic SGR investment: program of investments needed to achieve and maintain SGR SGR-related investments are made consistent with current practice SGR-related investments are made consistent with an optimal strategy that minimizes transit agency and user costs over the long term Initial cost of achieving SGR may be high—analysis period needs to be appropriately long (e.g., 20 years to capture benefits) SGR investment deferral: needed investments are deferred for a defined period One or more SGR investments are deferred for a set period (e.g., 5 years) Deferral period should be clearly defined—a short deferral may have a modest impact, but if needed investments are continually deferred, the be used instead SGR disinvestment: all SGR investments are deferred indefinitely All investments are deferred for the entire analysis period Complete deferral may not be a reasonable alternative— need to carefully evaluate changes in ridership and maintenance costs to ensure use of consistent assumptions disinvestment scenario should Table 2-1. Potential base and investment cases for analyzing ROI of SGR investments.

12 Guidance for Calculating the Return on Investment in Transit State of Good Repair Methodology for Cost and Demand Calculation Quantifying Agency Costs Transportation agency costs that may be impacted by SGR investments include capital costs of replacing transit assets, subsequent maintenance and rehabilitation costs (including costs of addressing asset road calls or failures), and fuel or energy costs. Failing to keep assets in SGR tends to result in higher costs to the transit agency and potentially to transit users. TCRP Report 157 (6) presents a comprehensive framework for calculating asset life­cycle costs applicable to the present research effort. Appendix E of that report describes three basic types of asset models: a model for revenue vehicles that leverages National Transit Database (NTD) data, as well as condition­based and age­based models for other transit assets that utilize defaults from FTA’s Transit Economic Requirements Model (TERM). These models were further modified and incorporated into the Transit Asset Prioritization Tool (TAPT) included with TCRP Report 172 (7). The modeling changes are documented in the Contractor’s Final Report for TCRP Project E­09A (8). All three of the models provide a prediction of agency life­cycle costs if optimal actions are performed to achieve and maintain SGR, as well as the additional cost incurred if needed work is deferred. A summary of the models is provided in Appendix C. The appendix highlights key assumptions and inputs and combines the discussions from the above sources. Note that user cost components of the models are omitted in the formulation, as the more recent research described in the next section provides an improved approach for characterizing transit user costs. Furthermore, note the agency cost models apply to all systems, regardless of mode, including bus and rail systems. Quantifying User Costs As discussed in the overview of benefits and costs of transit SGR section above, transit investment (or disinvestment) may result in a range of different user impacts. Quantifying user costs entails calculating a travel time that incorporates the changes in asset condition and determines the change in ridership associated with SGR investment or disinvestment. Relating Asset Condition to Service Quality and Calculating Travel Time The relationship between asset condition and service quality is established in TCRP Research Report 198 (9). This report describes the qualitative relationships between service quality and asset condition, defining dimensions of service quality based on TCRP Report 165 (10). In addi­ tion, it introduces the measure of EJT to integrate consideration of different aspects of service quality into a single overall measure that can demonstrate the impacts of changes in asset condition. EJT combines actual journey time with adjustment factors for different components of the journey, as well as for customer perceptions. The components of journey time are summarized in Table 2­2. Changes in asset condition impact EJT in two basic ways: they impact actual journey time; and they may impact customer perceptions, resulting in revisions to the adjustment factors for one or more components of the journey. Estimating Travel Demand With the travel times from the EJT calculation in hand, the impacts on transit patronage can be calculated. Computing transit ridership is the key element in determining the ROI of SGR investment. There are two approaches for computing transit ridership: 1) use a travel demand model, or 2) estimate arc elasticity of demand with respect to travel times.

Analysis Methodology 13 Approach 1: Travel Demand Model. If the transit agency has access to a detailed travel demand model, the recommended approach is to replace the transit travel times in the travel demand model with the travel time results from the EJT calculation. The travel times from the EJT calculation can be coded on the transit network, and the impacts of diverted transit trips to highway network can be addressed through longer highway travel times. This will yield the most accurate and detailed estimate of the potential ridership gains or losses due to SGR investment or disinvestment. Approach 2: Arc Elasticity of Demand. If the transit agency does not have access to a travel demand model, the use of the arc elasticity of demand with respect to travel times is recom­ mended. For each boarding­to­alighting stop combination, given the current level of ridership, the projected ridership can be calculated as follows: Q Q T T T T 1 1 1 1 (2­1)2 1 1 2 2 1  ( ) ( ) ( ) ( ) = h− − h+ h− − h+ Where: Q1 = Current ridership Q2 = Predicted future ridership T1 = Current travel time T2 = Predicted future travel time h = Elasticity (from Table 2­3) Transit demand elasticities tend to be higher over the long­term as travelers have more opportunities to make residential location and vehicle ownership decisions that negatively impact their potential transit use. According to Pratt and Evans (11), it usually takes about one to three years for passengers to fully adapt. However, one should keep in mind that all prior research was conducted on elasticities with respect to discrete­time events, e.g., fare increases or timetable changes. The case where a system deteriorates due to deferred maintenance, in which unreliability and travel times increase accordingly, is a gradual and continuous process. Nonetheless, it can be assumed that long­term ridership losses will be higher than short­term ridership losses and that the full effects of a deterioration of the system will only be measurable with a time lag that may be upwards of a year. Component Description Buffer Time Time passengers build into their travel time anticipating delays or unreliable service In-Station Conveyance Time Time required to navigate through a bus or rail station, including time walking, handling fare payment, traveling up or down stairs, and taking elevators or escalators Wait Time Time passengers wait at a stop or station In-Vehicle Time Time passengers spend on a vehicle to reach their destination Table 2-2. Journey time components. Short term (≤ 1 year) Long term (≥ 5 years) −0.4 −1.0 Table 2-3. Recommended elasticity values.

14 Guidance for Calculating the Return on Investment in Transit State of Good Repair Currently, the most relevant and recent values for transit demand elasticity with respect to transit in­vehicle travel time are from Frank et al. (12), who calculated the elasticity to be −0.39 for home­based work tours and −0.23 for home­based non­work tours. These numbers were derived from a tour­based travel demand model estimated with data from the 1999 Puget Sound Regional Household Travel Survey. (Tours include outbound and inbound trips, and all stops in between.) The paper does not offer any interpretation of why the elasticities for off­peak travel are estimated to be lower than the peak­hour elasticities. The elasticity value of approximately −0.4 for peak­hour travel is in line with other estimates for demand elasticity with respect to generalized travel costs, but other studies have found that the elasticity of off­peak travel can be higher than the elasticity of peak­hour travel. Pending further research, the application of the peak­hour elasticity value across all time periods is recommended. Based on the context given by Frank et al., these numbers represent short­term elasticities. A literature review conducted by Litman (13) concludes that long­term transit demand elasticities tend to be two to three times as large as short­term elasticities, and research supporting the constant travel­time budget hypothesis and other studies on the elas­ ticity of demand with respect to generalized travel costs suggests a long­term elasticity of −1.0. This would correspond to the recommended short­term elasticity times a factor of 2.5, which is realistic. In summary, the elasticity values in Table 2­3 are recommended. Calculating Changes in User Costs Resulting from Changes in Travel Demand To the extent that an SGR investment results in new transit trips, or, alternatively, that disinvestment results in fewer trips, there is an additional change in user costs resulting. The shift of greatest concern is between transit and automobiles: new transit users in many cases have shifted from using a car to using transit, and lost trips are frequently cases where a transit user has opted to drive rather than taking transit. The report prepared for TCRP Project J­11, Task 7 (4) describes an approach for modeling the cost savings resulting from shifting from automobiles to transit. This report estimates that 56 percent of lost transit trips result in additional automobile trips. This value is based on on­board transit surveys of passengers to determine what mode they would use if transit were unavailable. This report also estimates the average trip has a distance of five miles. Various reports provide estimates of automobile user operating costs and value of time. Here, the U.S. Department of Transportation estimate of $12.50 per hour (in 2013 dollars) is used for personal time (14). Adjusting for inflation and using the Consumer Price Index (CPI), this equates to $12.88 per hour in 2016 dollars. The Internal Revenue Service estimate of 54 cents per vehicle mile (in 2016 dollars) is used for the operating cost of an automobile (15). The relative health and recreational benefits of additional walking or cycling that may be promoted by transit use is not included in this estimate. Calculating Social and Environmental Impacts Investments in transit may result in a range of social and environmental impacts and/or benefits. General resources for evaluating these effects include TCRP Report 78: Estimating the Benefits and Costs of Public Transit Projects: A Guidebook for Practitioners (2), the New Zealand Transport Authority Economic Evaluation Manual (16), and the Victoria Transport Policy Institute (VTPI) documents Evaluating Public Transit Benefits and Costs: Best Practices Guidebook (17) and Transportation Cost and Benefit Analysis Techniques, Estimates and Implications (18). An issue in applying common BCA practices is that these are oriented toward investments in new service. For instance, building a new bus rapid transit lane may have effects on land

Analysis Methodology 15 use, communities, and the environment, and so forth. However, such impacts are generally not projected in the case of analyzing SGR investments that change asset conditions without affecting the extent of transit service. For analyzing SGR investments, one would typically assume that the same transit service is provided in the base and investment case, and thus no change in social or environmental costs would be projected as a result of transit operations. However, if travel demand changes, there would be effects predicted as a result of mode shift described in the previous subsection. Specifi­ cally, a change in transit trips is predicted to correspond to a change in automobile travel, and thus a change in social and environmental costs from vehicle emissions. Various estimates have been developed monetizing vehicle emissions, including the following pollutants: • Carbon monoxide (CO); • Greenhouse gases (GHG); • Nitrogen oxide (NOx); • Particulate matter (PM), which may be further subdivided based on size; • Secondary organic aerosols (SOA); • Sulfur dioxide (SOx); and • Volatile organic compounds (VOC). Other environmental impacts of automobile travel include noise and water pollutions, and these are included in some of the estimates of emissions costs. In the VTPI Guidebook (17), Litman conducts a comprehensive review of different emissions cost estimates and in Table 28 recommends an overall pollution cost of 6 cents per vehicle mile (in 2007 dollars) considering air, noise, and water pollution. This resource also recommends an overall pollution cost of 10 cents per vehicle mile (in 2007 dollars) for diesel buses meeting 2004 standards, which equates to 40 cents per gallon assuming an average fuel efficiency of 4 miles per gallon. Adjusting for inflation using the CPI, these values equate to 7 cents per mile for automobile pollution costs and 46 cents per gallon for diesel fuel pollution costs in 2016 dollars. It is important to note that when an automobile driver shifts to transit, this results in reduced costs for other drivers by reducing congestion. The VTPI report on cost and benefit analysis techniques (18) differs in estimates of congestion costs. It concludes with estimates of average congestion costs (in 2007 dollars). Its estimate for the average period for the average car is 3.5 cents per vehicle mile. This includes travel time and vehicle operating and safety costs from the traffic congestion caused by each additional vehicle mile. Adjusting for inflation using the CPI, this equates to 4 cents per mile in 2016 dollars. Calculating Economic Impacts Frequently, decision makers are interested in the new jobs a given investment will generate or increased economic activity following an investment. The approaches described in the previous subsections can help support analysis of such economic measures, but fully addressing the economic impacts of a given investment or program of investments requires a separate EIA. What is the difference between EIA and BCA? As described in the TCRP Project J­11, Task 7 report (4), “Economic impact analysis focuses specifically on measurable changes in the flow of money (income) going to households and businesses, including both productivity and spending effects. That is different from benefit–cost analysis, which considers the valuation of both money and non­money benefits.” The report also notes that while EIA excludes some factors quantified in BCA, it also includes other factors not considered in BCA, such as indirect and induced economic growth. In its

16 Guidance for Calculating the Return on Investment in Transit State of Good Repair Economic Analysis Primer (19), the FHWA cautions that the value of the indirect economic effects calculated in an EIA “is not additive to the BCA­measured direct effects—rather, the former value is a restatement or capitalization of the latter value.” In other words, one cannot simply add the benefits predicted from BCA to those calculated from an EIA and present these as a total benefit; the two types of analysis are measuring some of the same things but presenting them in different ways. Another important issue to consider in conducting an EIA is the geographic scope of the analysis. Generally, an EIA is regional in its scope and includes both generations of new economic activity (e.g., increased business activity resulting from a reduction in congestion) and transfers (e.g., creation of jobs in a given region through increased capital spending, which may represent a transfer of spending from another location). When a broader geographic scope is considered, transfers may cancel each other out partially or entirely. Thus, it is important to carefully define and clearly state the geographic scope of an EIA. While the prospect of performing a separate EIA may appear daunting, the TCRP Project J­11 report provides a template for performing an EIA for transit, as well as summary results for supporting analysis of the benefits of SGR analysis. The 2014 update of the report describes an analysis of two different scenarios: a “Current Trend” analysis approximating the continuation of current spending and ridership trends and a “Double Ridership Growth” scenario in which increased capital spending of $14 billion per year is expected to yield an approximate doubling in ridership at the end of a 20­year period. Two basic types of impacts are considered: travel cost reduction impacts that result from increased transit ridership in the “Double Ridership Growth” scenario relative to the “Current Trend Scenario” and spending impacts that result from increased capital and operations expenditures. Of the two types of impacts included in the TCRP Project J­11 analysis, the travel cost reduc­ tion impacts are relevant for analysis of SGR investments provided these yield relative changes in ridership, including analysis of both SGR investments that may increase ridership and dis­ investment that may result in reduced ridership. The key issue is whether a ridership change is predicted; while there could be an economic impact resulting from changes in travel cost even if there is no change in ridership, it would be difficult to apply the approach used for the TCRP Project J­11 analysis in this case. On the other hand, the spending impacts projected are less applicable to an SGR analysis. The impacts would be modest in the case where an initial capital investment yields costs savings over time and negative in the event that SGR investment results in a net reduction in transit agency costs. Regarding the cost reduction impact, the analysis predicts the operating cost reduction resulting from travelers shifting from automobiles to transit. This leads to a reduction in their travel costs—estimated based on typical values for trip length and operating cost components— and a reduction in travel costs on the highway system resulting from the modal shift. The highway system cost reduction is estimated on a nationwide basis comparing simulation results for scenarios performed in the FHWA Highway Economic Requirements System (HERS) and is split between personal and business travel. The increase in transit ridership is predicted to result in an additional benefit from reduction in vehicle ownership. The business productivity impact resulting from the travel cost reduction is estimated using the econometric model Trans­ portation Economic Development Impact System (TREDIS) developed by EDR Group. These effects together yield an overall economic impact from cost reductions, which may be presented as a dollar value, job equivalent, or in terms of increased tax revenue. For calculating spending impacts, the TCRP Project J­11 analysis uses the econometric model IMPLAN to predict the overall economic impact from increased capital and operations spending. The report presents this as a dollar value, as well as in terms of the increased gross domestic product (GDP), job equivalent, and increased tax revenue.

Analysis Methodology 17 Table 2­4 summarizes the specific effects considered in the TCRP Project J­11 analysis, distinguishing between cost reduction and spending impacts. Metrics for Communicating the Return on Investment Communicating the ROI of SGR investment is an important final step in the analysis process. The basic summary measures that can be used to communicate the results of a BCA include the following: • Net Present Value (NPV). This is calculated as the present value of the benefits of SGR investment (i.e., the entire stream of benefits discounted to the present) minus the present value of the costs (including initial capital costs and ongoing maintenance and operating costs discounted to the present). • Benefit/Cost Ratio (BCR). This is calculated as the present value of the benefits divided by the present value of the costs. • Internal Rate of Return (IRR). This is the discount rate at which benefits and costs break even (are equal). If the IRR is greater than the discount rate used for the ROI analysis, then the SGR investment is economically viable. In addition to the above metrics, narrative descriptions of the impacts of SGR investment on the user, agency, environment, etc. should be included to highlight the impacts that are difficult to quantify. There may be benefits that cannot be measured in monetary terms but should still be described qualitatively when communicating ROI. If an EIA is performed, it yields the following additional measures, noted in Table 2­4: • Total Economic Impact. The total value of the economic impact, in dollars, given a particular investment or set of investments. Type of Impact Effect Value Projected in EIA ($ 2012) Notes Cost Reduction Personal savings to public transportation passengers $6.8 billion/yr. ~$1.69 per new trip Personal savings in auto user operating costs $6.2 billion/yr. ~$1.59 per new trip Personal savings in auto ownership costs $5.4 billion/yr. ~$1.35 per new trip Business savings from labor market access enhancement $5.0 billion/yr. ~$1.25 per new trip Business savings from auto/truck operating cost reduction $5.1 billion/yr. ~$1.31 per new trip Total Economic Impact $28.5 billion/yr. ~$7.19 per new trip Wages $21.8 billion/yr. ~$5.50 per new trip Job Equivalent 410,820 jobs 1 job per ~9,649 new trips Corresponding Tax Revenue $4.4 billion/yr. ~$1.11 per new trip Spending Impact Total Economic Impact $23.8 billion/yr. $3 per $1 spent Wages $18.2 billion/yr. $1.30 per $1 spent Job Equivalent 309,560 jobs 21.8 jobs per $1 million spent Corresponding Tax Revenue $6.0 billion/yr. $432,000 per $1 million spent Source: APTA (2014), Economic Impact of Public Transportation Investment: 2014 Update Table 2-4. Summary of cost reduction and spending impacts in the TCRP Project J-11, “Economic Impact Study.”

18 Guidance for Calculating the Return on Investment in Transit State of Good Repair • Wages. A subset of the total economic impact that indicates the value of additional wage dollars generated as a result of an investment. • Job Equivalent. The number of full­time jobs that could be created from available wages, given an average wage rate. • Corresponding Tax Revenue. The tax revenue generated from the expected value of the economic input assuming a specific tax rate. References 1. Cambridge Systematics, Inc., and Economic Development Research Group. “Best Practice Methodology for Calculating Return on Investment for Transportation Programs and Projects.” Contractor’s Report for NCHRP Project 8­36, Task 62. 2008. 2. ECONorthwest, and Parsons Brinckerhoff Quade & Douglas, Inc. TCRP Report 78: Estimating the Benefits and Costs of Public Transit Projects: A Guidebook for Practitioners. TRB, National Research Council, Washington, D.C., 2002. 3. Spy Pond Partners, LLC; HDR, Inc.; and H. Cohen. (2017). NCHRP Research Report 866: Return on Invest- ment in Transportation Asset Management Systems and Practices. Transportation Research Board, Washing­ ton, D.C., 2017. 4. Weisbrod, G., and A. Reno. “Economic Impact of Public Transportation.” Contractor’s Final Report for TCRP Project J­11, Task 7. 2009. 5. APTA. Economic Impact of Public Transportation Investment: 2014 Update. 2014. 6. Spy Pond Partners, LLC; KKO & Associates, LLC; H. Cohen; and J. Barr. TCRP Report 157: State of Good Repair: Prioritizing the Rehabilitation and Replacement of Existing Capital Assets and Evaluating the Implica- tions for Transit. Transportation Research Board of the National Academies, Washington, D.C., 2013. 7. Robert, W., V. Reeder, K. Lawrence, H. Cohen, and K. O’Neil. TCRP Report 172: Guidance for Developing a Transit Asset Management Plan. Transportation Research Board of the National Academies, Washington, D.C., 2014. 8. Robert, W., V. Reeder, K. Lawrence, H. Cohen, and K. O’Neil. “Guidance for Developing the State of Good Repair Prioritization Framework and Tools: Research Report.” Contractor’s Final Report for TCRP Project E­09A. 2014. 9. Spy Pond Partners, LLC; AECOM; McCollom Management Consulting, Inc.; H. Cohen; and S. Silkunas. TCRP Research Report 198: The Relationship Between Transit Asset Condition and Service Quality. Transpor­ tation Research Board, Washington, D.C., 2018. 10. Kittelson & Associates Inc.; Parsons Brinckerhoff; KFH Group, Inc.; Texas A&M Transportation Institute; and ARUP. TCRP Report 165: Transit Capacity and Quality of Service Manual,Third Edition. Transportation Research Board of the National Academies, Washington, D.C., 2013. 11. Pratt, R., and J. Evans. TCRP Report 95: Traveler Response to Transportation System Changes Handbook, Third Edition: Chapter 10: Bus Routing and Coverage. Transportation Research Board of the National Academies, Washington, D.C., 2004. 12. Frank, L., M. Bradley, S. Kavage, J. Chapman, & T. K. Lawton. “Urban Form, Travel Time, and Cost Relation­ ships with Tour Complexity and Mode Choice.” Transportation, 35(1), 2008, pp. 37–54. 13. Litman, T. Understanding Transport Demands and Elasticities: How Prices and Other Factors Affect Travel Behavior. Victoria Transport Policy Institute, 2013. 14. U.S. Department of Transportation. The Value of Travel Time Savings: Departmental Guidance for Economic Evaluations Revisions 2 (2015 Update). Washington, D.C., 2015. 15. Internal Revenue Service. 2016 Standard Mileage Rates for Business, Medical and Moving Announced. IR­2015­137, 2015. 16. New Zealand Transport Authority. Economic Evaluation Manual. NZTA, 2016. 17. Litman, T. Evaluating Public Transit Benefits and Costs: Best Practices Guidebook. Victoria Transport Policy Institute, 2017. 18. Litman, T. Transportation Cost and Benefit Analysis: Techniques, Estimates and Implications [Second Edition]. Victoria Transport Policy Institute, 2016. 19. Federal Highway Administration (FHWA). Economic Analysis Primer. Washington, D.C., 2003.

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Transit state of good repair (SGR) is a critical area within the U.S. transit industry. All transit agencies, large or small, regardless of region of the country or modes operated, face challenges in maintaining their physical assets in good repair, and many are in a situation where the funds available for rehabilitating and replacing existing capital assets are insufficient for achieving SGR.

The TRB Transit Cooperative Research Program's TCRP Research Report 206: Guidance for Calculating the Return on Investment in Transit State of Good Repair addresses transit agency, user, and social costs and benefits of SGR investments. The report presents an analysis methodology that utilizes and builds upon previous research performed through the Transit Cooperative Research Program (TCRP) presented in TCRP Reports 157 and 198. The guidance (presented in Chapter 3) walks through the steps for calculating the ROI for a potential investment or set of investments.

A key product of the research is a spreadsheet tool intended for transit agency use. It is discussed in Chapter 4.

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