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Page 37
Suggested Citation:"Chapter Five - Conclusions ." National Academies of Sciences, Engineering, and Medicine. 2015. Economic and Development Implications of Transportation Disinvestment. Washington, DC: The National Academies Press. doi: 10.17226/22109.
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Page 38
Suggested Citation:"Chapter Five - Conclusions ." National Academies of Sciences, Engineering, and Medicine. 2015. Economic and Development Implications of Transportation Disinvestment. Washington, DC: The National Academies Press. doi: 10.17226/22109.
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Page 38
Page 39
Suggested Citation:"Chapter Five - Conclusions ." National Academies of Sciences, Engineering, and Medicine. 2015. Economic and Development Implications of Transportation Disinvestment. Washington, DC: The National Academies Press. doi: 10.17226/22109.
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Page 39

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37 Adequacy, Applicability, and Understanding of Tools Although a review of available methods, data, and tools finds that economic methods and tools are adequate for understand- ing the specific types of implications needed to understand disinvestment scenarios, most practitioners cite a practical need for more data and better models and information when facing a decision. For example, of the agencies surveyed for this synthesis, 36% find themselves disinvesting because assets deteriorate faster than originally expected and 39% find themselves disinvesting because demand grew faster than expected. Furthermore, more than 54% cited a need for better data and 73% a need for better models to understand the implications for disinvestment. This suggests that while intricate models of asset con- dition, travel demand, economic impact, and societal cost exist, the tools are not currently configured in ways that make it practical to analyze a disinvestment scenario, and agencies have often not found ways to readily apply them. The link- ages between needs models, demand models, cost models, risk models, and economic impact models require a level of tech- nical investment and knowledge of infrastructure that is only present in a limited number of transportation agencies. As a consequence, traditional techniques such as cost–benefit analy- sis, economic impact analysis, risk-based asset management, and travel demand modeling are underutilized when agencies confront a need for developing disinvestment scenarios (as shown by the case examples, literature review, and survey). Applying the available methods and tools for disinvest- ment scenarios requires changing the agency business process (and the understanding of planning) such that at least as much attention is given to a disinvestment scenario as an investment scenario. This raises a paradox for agencies—in that to respon- sibly develop a disinvestment scenario in and of itself requires an investment in the decision itself. It is difficult to raise support (and justify agency resources) for a corridor study, long-range plan, or modeling study with an explicit goal of disinvestment. Such a goal may provide stakeholders with limited incentive to fund or engage in such a study. Furthermore, processes such as the National Environmental Policy Act and the statewide planning and metropolitan planning organization processes do not have explicit planning requirements for disinvestment, but rather they simply allow disinvestment to occur as a result of limited funds, focusing only on the investment and not the disinvestment outcome. OVERALL FINDINGS This synthesis found that states are only beginning to pro- actively consider disinvestment as a meaningful choice in their planning, programming, and systems evaluation, and that economic analysis of such scenario consideration is in its infancy. Although economic methods and tools can lend themselves to a defensible and robust understanding of dis- investment outcomes, practitioners lack the time, resources, or know-how to configure and apply such tools. There is also some question among practitioners as to how reliable such analysis can be given the complexity of factors asso- ciated with disinvestment outcomes, as well as whether or not economic analysis could, or would, alter disinvestment outcomes. To some degree, disinvestment analysis requires adding layers of complexity to familiar planning concepts such as minimum tolerable conditions, investment needs, and travel demand forecasting. However, new concepts such as con- sidering risk and likelihood of future demands, defining “real options” for alternative possible uses of existing assets, and re-thinking the true base case in any economic analysis, must be integrated as well. The case examples show the current state of the practice, but fall considerably short of illustrating the state of the art in terms of how existing methods and tools can be applied to disinvestment scenarios. The current synthesis suggests a need for case examples to illustrate and demonstrate how existing models, methods, and data can be assembled for dif- ferent types of disinvestment scenarios. Furthermore, while the survey and case examples primarily address state transpor- tation agencies, it is important to note that the models and data needed for disinvestment analysis, as well as many aspects of disinvestment decision making, are also relevant at the metro- politan planning organization and regional planning organiza- tion level. STATE OF THE PRACTICE Overall, the findings offered in this synthesis address the current state of the practice; suggest a way forward to a “most effective practice” in disinvestment planning; iden- tify clear gaps in methods, data, and tools; and point to some new approaches and methods appropriate for disinvestment scenarios. chapter five CONCLUSIONS

38 For this reason, while the economic tools and techniques are available [and as demonstrated by the ASCE study (ASCE 2011), the Washington State Department of Transportation (DOT) case example (J. Milton and P. Morin, personal com- munication, 2014) and others], and such tools can be arranged to develop and analyze disinvestment cases, the place for such analysis in the planning and policy environment is unclear. In addition to uncertainty regarding where in the policy envi- ronment disinvestment analysis belongs, there is the added challenge of establishing a most effective practice for creat- ing and comparing disinvestment scenarios, and the invest- ment of staff time and budgets into building the capacity for disinvestment. Finally, a major impediment to fully utilizing available techniques for disinvestment planning rests with the dimensions of a disinvestment scenario. Agencies must address uncertainty on multiple dimen- sions in order to apply economic methods to disinvestment scenarios. These include: 1. Consideration of multiple possible demographic and economic futures and demand patterns; 2. Consideration of multiple possible scenarios for how life-cycle costs may change over an investment life; 3. Consideration of multiple sets of “minimum tolerable conditions” or performance standards for assets which might apply in each possible demand scenario; and 4. Consideration of the risk and likelihood associated with these different scenarios coming to fruition. These dimensions require more time, effort, and know-how than the earlier investment or asset management paradigms of the 20th century. Disinvestment analysis requires significant time, attention, and know-how that is not present in most state DOT environments. The complexity of the problem poses a significant challenge to widespread adoption of economic analysis for disinvestment planning in the near term. Key Gaps in Methods, Data, and Tools The largest gaps in methods, data, and tools pertain to the appropriate application and internally consistent use of avail- able methods and tools. Additional research is needed to: • Identify possible sources of error that may arise when the different types of models needed to assess a disinvest- ment outcome are combined. • Develop a widely accepted structure for how the multiple dimensions of disinvestment planning can be reduced to manageable base cases and performance standards that lend themselves to routine analysis in the planning environment. • Identify ways to automate the links between needs (or asset management) models, travel demand models, socioeconomic/land-use forecasting models, cost–benefit analysis models, and economic impact models such that they can be routinely applied to disinvestment sce- narios; and • Assemble meaningful case studies of actual outcomes of transportation disinvestment outcomes in different circumstances. A gap that cannot be covered by additional research, but that should inform how any findings are implemented, is in the financial and staff capacity of agencies to invest in the most state-of-the-art data, models, and information systems. In the same way, the degree to which agencies can establish consis- tency of decision methods for both investment planning and project programming is likely to enhance the degree to which agencies can benefit from assessing disinvestment scenarios. Promising Approaches and Suggested Most Effective Practice Although the current synthesis finds that there is not yet a rec- ommended most effective practice for assessing the economic implications of disinvestment scenarios, there are promising approaches and practical steps that agencies can take to better support considering disinvestment scenarios. Perhaps first and foremost, the current synthesis finds that it is a more effective practice to explicitly consider disinvestment as a pro-active alternative for managing costs than to simply allow it to happen as an accident of limited funding. Figure 8 suggests a way in which existing demand, risk, needs, and economic models may be combined to both pre- vent and anticipate future disinvestment situations in long- range planning. It can be noted that Figure 8 may be a simplification in that another round of risk and probability modeling may be appropriate to assess not only best and worst case scenarios for demand, but also best and worst case scenarios of need within any given estimate of demand (because of differences in mini- mum tolerable conditions or infrastructure deterioration rates). By developing a realistic disinvestment case, associated with a realistic assessment of the likelihood of changing needs, an agency can more effectively avoid unintended consequences of passive disinvestment. Furthermore, in many cases a disin- vestment scenario may represent the “ounce of prevention” that is better than a “pound of cure.” For example, if an agency can identify a need to disinvest in a facility or program to save life- cycle costs in the long term, the agency may be able to make the choice at a time when there is an option for a short-term invest- ment in the re-use of the facility and the preparation of an alter- native facility more appropriate to different future demands. In this way, agencies may use disinvestment planning to reduce both the risk of “sunk costs” in assets that ultimately become unsustainable and opportunity costs of other assets that can- not be afforded by maintaining all assets at original perfor- mance standards. This points to a need for future research regarding how agencies can build the capacity to identify these

39 opportunities, as well as the data and technical needs for agen- cies to consistently identify and address disinvestment. The needed capacity building likely involves not only addressing the gaps enumerated in the previous section, but also clearly demonstrating how methods and data can most effectively be structured in a typical planning or analytical process. Arriving at a paradigm in which states can consistently and reliably include disinvestment as part of their performance- based planning will likely take years of capacity building and further incorporation of basic economic methods and tools, as well as disinvestment concepts into the DOT business pro- cess. Some early steps in this regard include: 1. In performance-based plans, offering at least two dif- ferent performance standards for each facility (such as a high-demand target and a low-demand target), such that different needs estimates may apply. 2. Considering the comparative return on investment for all projects and programs, taking into account both life-cycle costs and user costs under different future demand assumptions. 3. In long-range plans, considering both investment and disinvestment options, or scenarios that sustain differ- ent programs and assets at different levels (that may exceed or be less than historic levels). 4. In travel model development efforts, including at least two different socioeconomic forecasts to allow for two different traffic forecasts. AREAS FOR FUTURE RESEARCH It can be suggested from this synthesis report that a more com- prehensive research effort be undertaken to develop instruc- tive case examples demonstrating: 1. How a typical disinvestment economic analysis can be structured (through a series of case examples) showing how the base case, investment case, and dis- investment case can be defined, and key data elements required. 2. How both the scale and time horizon of the analysis period can significantly affect the results pertaining to both the need for infrastructure and the potential impli- cations of disinvestment. 3. How available needs models, network and demand mod- els, risk models, and impact models can be assembled in practical ways to assess a disinvestment scenario. 4. How an economic analysis of a disinvestment case differs depending on the available data and modeling resources and the scale of the project. 5. Ways in which appropriate analysis of disinvestment scenarios may yield insights regarding opportunities posed by resource constraints. 6. The likely magnitude of economic benefits and impacts that can result from the current practice of “tolerat- ing underinvestment” in contrast to potential results of identifying and planning for disinvestment when needed. FIGURE 8 Role of different model types in disinvestment scenarios.

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TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 480: Economic and Development Implications of Transportation Disinvestment examines methods available to estimate disinvestment effects on transportation system integrity within and across modes in urban areas, regionally, and in non-metro areas, and the use of those methods by transportation agencies. The report focuses on macroeconomic effects, intermodal tradeoffs, and methods for broadly informing disinvestment decision making in an era of constrained resources. The report includes information on economic forecasting and travel demand models, risk or probability models, needs models, and benefit and impact models.

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