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FHWA Home / Policy & Governmental Affairs / 2006 Conditions and Performance

Conditions and Performance

FHWA - 2006 Conditions and Performance Report: Part II Executive Summary - Investment/Performance Analysis
Status of the Nation's Highways, Bridges, and Transit:
2006 Conditions and Performance

Part II Executive Summary

Investment/Performance Analysis

Chapters 7 through 10 present and analyze estimates of 20-year capital investment scenarios for highways, bridges, and transit. The projections shown in this report reflect complex technical analyses that attempt to predict the impact that capital investment may have on the future conditions and performance of the transportation system. Separate estimates of investments for highways, bridges, and transit are generated independently by separate models and techniques. While the Highway Economic Requirements System (HERS), National Bridge Investment Analysis System (NBIAS), and Transit Economic Requirements Model (TERM) all utilize benefit-cost analysis, their methods for implementing this analysis are very different. Each model relies on separate databases, making use of the specific data available for only one part of the transportation system and addressing issues unique to each mode. These three models have not yet evolved to the point where direct multimodal analysis would be possible.

Chapter 7 presents estimates of future investment for specific scenarios, which are defined differently for each mode. These scenarios are intended to be illustrative only; this report does not endorse any particular level of future highway, bridge, or transit investment. While estimates are made of the cost to maintain future indicators of conditions and performance and current year levels, and the cost to improve performance based on standards unique to each model, these represent only two points on a continuum of alternative investment levels. Chapter 9 analyzes the impacts different levels of future investment might have on various measures of physical condition, operating performance, and system use.

Chapter 8 compares 2004 spending with the average annual investment scenario levels for the 2005–2024 period stated in constant 2004 dollars in Chapter 7 for the benchmark scenarios. The investment scenario estimates reflect the total capital investment required from all sources—Federal, State, local, and private—to achieve certain levels of performance. While the analyses in Chapter 8 identify the magnitude of the differences between current spending and the investment scenarios, they do not directly address which revenue sources might be used to finance additional investment, nor do they suggest how much might be contributed by each level of government. This report makes no recommendations concerning future levels of Federal investment.

As in any modeling process, simplifying assumptions have been made in HERS, NBIAS, and TERM to make analysis practical and to meet the limitations of available data. (See Appendices A, B, and C for more details on the individual models.) The accuracy of the projections of future investment scenarios depends in large part on the underlying assumptions used in the analysis. Chapter 10 explores the impact that varying some of these key assumptions would have on the overall results.

The HERS, NBIAS, and TERM models all have a broader focus than traditional engineering-based models, looking beyond transportation agency costs to consider the benefits that transportation provides to users of the system and some of the impacts that transportation investment has on nonusers. From an economic perspective, the cost of an investment in transportation infrastructure is simply the straightforward capital cost of implementing an improvement project. The benefits of transportation capital investments are generally characterized as the attendant reductions in costs faced by (1) transportation agencies (such as for maintenance), (2) users of the transportation system (such as savings in travel time and vehicle operating costs), and (3) others who are affected by the operation of the transportation system (such as reductions in environmental or other societal costs).

While the economic-based approach would suggest that projects be implemented in order based on their benefit-cost ratios (BCRs) until the funding available under a given scenario is exhausted, in reality other factors influence Federal, State, and local decisionmaking that may result in a different outcome. If some projects with lower BCRs were carried out in favor of projects with higher BCRs, then the actual amount of investment required to achieve any given level of performance would be higher than the amount predicted in this report. Consequently, increasing spending to the level identified as the 'Cost to Maintain" would not guarantee that conditions and performance would actually be maintained. Similarly, while the HERS, NBIAS, and TERM models all screen out potential improvements that are not cost-beneficial, simply increasing spending to the "Cost to Improve" level would not in itself guarantee that these funds would be expended in a cost-beneficial manner. Further, there may also be some projects that, regardless of economic merits, may be infeasible as a practical matter due to factors beyond those considered in the models. As a result, the supply of feasible cost-beneficial projects could be exhausted at a lower level of investment than is indicated by this scenario, and the projected improvements to future conditions and performance under this scenario may not be fully obtainable in practice.

This report has traditionally identified the amount of additional spending above current levels that would be required to achieve certain performance benchmarks, without considering the types of revenues required to support this additional spending. The implicit assumption has been that the financing mechanisms would not have any impact on the investment scenario estimates. In reality, however, increased funding from general revenue sources (such as property taxes, sales taxes, income taxes, etc.) would have different implications than increased funding from user charges (such as fuel taxes, tolls, and fares). For this report, the highway investment modeling procedures have been modified to assume that any increase in highway and bridge investment above 2004 levels would be funded entirely by increases in user charges, and a feedback loop has been added to account for the impact that this increase in the "price" of travel would have on deterring future travel and, by extension, reducing future investment scenario estimates.

While the assumption of increased levies on users via the current tax structure draws revenues, investment, and travel demand together, the inherent economic inefficiencies of the current structure would remain, whereby travel on uncongested facilities is charged at the same rate as those with significant congestion issues. In an ideal (from an economic point of view) world, users of congested facilities would be levied charges precisely corresponding to the economic cost of the delay they impose on one another, thereby reducing peak traffic volumes and increasing net benefits to all users combined.

For this report, the HERS model has been adapted to illustrate the maximum, theoretical impact that efficient pricing could have on the estimates of future highway investment scenarios. This highly stylized analysis, presented in Chapter 10, assumes that congestion pricing would be implemented universally on all congested roads. This analysis demonstrates that congestion pricing has considerable potential for reducing peak period congestion and future investment scenario estimates. However, this analysis should be viewed as an interim product that will be refined in future editions of the C&P report. Importantly, it does not account for the considerable costs that could be associated with implementing and administering such a comprehensive pricing system. The methodology used for this analysis is presented in Appendix A. The "Pricing Effects" section in Part IV provides a further discussion of ongoing research in this area.


Page last modified on November 7, 2014
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