U.S. Department of Transportation
Federal Highway Administration
1200 New Jersey Avenue, SE
Washington, DC 20590
Status of the Nation's Highways, Bridges, and Transit:
2002 Conditions and Performance Report
|Chapter 10: Sensitivity Analysis|
Part I: Description of Current System
Part II: Investment Performance Analyses
Part III: Bridges
Part IV: Special Topics
Part V: Supplemental Analyses of System Components
The accuracy of the investment requirements reported in Chapter 7 depends on the validity of the underlying assumptions used to develop the analysis. This section explores the effects that varying several key assumptions in the highway investment requirement analytical process would have on the Cost to Improve Highways and Bridges and the Cost to Maintain Highways and Bridges. While not discussed directly in this chapter, any changes in the projected investment requirements would also affect the gaps identified in Chapter 8 between projected spending and the investment requirement scenarios.
Alternative Travel Growth Assumptions
States provide forecasts of future vehicle miles traveled (VMT) for each individual Highway Performance Monitoring System (HPMS) sample highway section. As indicated in Chapter 7, the Highway Economic Requirements System (HERS) assumes that the forecast for each sample highway segment represents the level of travel that will occur if a constant level of service is maintained on the facility. This implies that VMT will only occur at this level if pavement and capacity improvements made on the segment over the 20-year analysis period are sufficient to maintain highway-user costs at 2000 levels. If HERS predicts that highwayuser costs will deviate from baseline 2000 levels on a given highway segment, the model’s travel demand elasticity features will modify the baseline VMT growth projections from HPMS.
The HERS model utilizes VMT growth projections to predict future conditions and performance of individual highway segments and to calculate future investment requirements. If the HPMS VMT forecasts as modified by the HERS travel demand elasticity features are overstated, the investment requirement projections may be too high. If the travel growth is underestimated, the investment requirement projections may be too low.
The effective VMT growth rates predicted by the HERS model could be off target if either the HPMS forecasts don’t precisely represent the travel that will occur if a constant level of service is maintained, or if the travel demand elasticity procedures in HERS don’t accurately predict the response that highway-users will have to changes in costs. The latter effect is addressed in the next section by varying the values of the elasticity parameters used in the model. This section explores the impacts of the former case by modifying the estimates of future travel found in the HPMS sample data.
As indicated in Chapter 9, the State-supplied VMT growth projections in HPMS for 2000 to 2020 average 2.08 percent per year, well below the 2.99 average annual VMT growth rate observed from 1980 to 2000. The HERS model assumes that the 2.08 percent composite VMT growth projection in HPMS represents the growth that will occur at a constant level of service. If this forecast understates future growth, the investment requirements will be higher than predicted.
Exhibit 9-6 shows the impact of different levels of future investment on the average annual VMT growth rate, if one assumes that the baseline travel growth forecasts in HPMS represent a constant level of service. Exhibit 10-1 shows the impact on investment requirements of assuming that the VMT growth that would occur at a constant level of service is different from what is indicated in the HPMS forecasts. The first line assumes a growth rate of 2.99 percent annually (matching the actual average annual growth rate over the last 20 years), rather than the 2.08 percent rate derived from the HPMS forecasts. This is achieved by factoring up the growth rates entered into the HERS model for each section by 43.8 percent. Modifying the travel growth projections in this fashion would increase the Cost to Maintain Highway and Bridges by 52.5 percent. Increased VMT would increase the rate of pavement deterioration, as well as increase the share of resources that HERS would recommend using for capacity expansion to over 50 percent of total spending. Both of these factors would tend to increase the investment required to maintain user costs at 2000 levels. The Cost to Improve Highways and Bridges would increase by 50.4 percent based on this change in assumptions. The increased travel would increase the number of pavement and capacity projects that HERS would find to be cost-beneficial.
The second line in Exhibit 10-1 shows what the projected investment requirements would be if the average VMT growth rate at a constant level of service were 1.17 percent rather than 2.08 percent. This value represents the effect of doubling the decline in the average annual VMT growth rate (relative to the historic values) that is implicit in the HPMS forecasts (i.e., the average annual growth rate over 20 years would drop from 1.82 percent (2.99 to 1.17) rather than by 0.91 percent (2.99 to 2.08)). The impact on the Cost to Maintain Highways and Bridges would be a decrease of 30.6 percent, and the impact on the Cost to Improve Highways and Bridges would be a decrease of 29.2 percent.
Alternative Model Parameters
The HERS model uses several key input parameters whose values may be subject to considerable uncertainty or debate. To assess the importance of such uncertainty, the estimates of future investment requirements were recomputed using different values for some of these parameters, including short run and long run elasticity; the value of ordinary travel time; the value of reductions in incident delay; the value of a statistical life; improvement costs; and truck share growth. Exhibit 10-2 shows the impacts of the alternative parameter values on the Cost to Improve Highways and Bridges.
The travel demand elasticity values used in this report were -0.6 for short term elasticity with an additional -0.4 (total -1.0) for the long term share. In the 1999 C&P report, values of -1.0 and -0.6 (total -1.6) were used. The changes in the elasticity procedures are explained in Appendix A.
Under the highway Maximum Economic Investment scenario, highway user costs are projected to decline. At this level of investment, the elasticity procedures in HERS tend to induce travel growth. Therefore, raising the elasticity values back to the levels used in the 1999 C&P report would increase the amount of induced travel and thus increase the investment requirements slightly.
Value of Ordinary Travel Time
The value of time in HERS was developed using a standard methodology adopted by the U. S. Department of Transportation (USDOT). This methodology provides consistency among different analyses performed within the Department. However, there is a great deal of debate about the appropriate way to value time, and no single methodology has been uniformly accepted by the academic community, or within the Federal Government.
Doubling the value of ordinary travel time in HERS would increase the Cost to Improve Highways and Bridges by 11.7 percent. Increasing the value of time causes HERS to consider more widening projects (which reduce travel time costs) to be cost-beneficial. The proportion of capacity projects implemented as a percentage of total investment would increase, to over 49 percent of total improvement costs. Reducing the value of time by 50 percent would have the opposite effect, resulting in an 8.1 percent reduction in the Cost to Improve Highways and Bridges.
Value of Incident Delay Reduction
As noted in Appendix A and elsewhere in this report, the HERS model has recently been modified to calculate the delay associated with traffic incidents (such as crashes), in addition to recurring congestion delay and signal delay. Research has indicated that such unpredictable delay is even more “costly” to highway users (on a per-hour basis) than is the predictable, routine delay typically associated with peak traffic volumes. The HERS model accounts for this by allowing for a user-specified parameter for the “reliability premium” associated with reductions in incident delay, which is expressed as a multiple of the value of ordinary travel time.
The estimates of investment requirements in Chapters 7 and 8 used a baseline value of 2.0 times the value of ordinary travel time for the reliability premium, which was chosen on the basis of available research. Exhibit 10-2 shows the impacts of setting this premium at a) 3.0 times the ordinary travel time value and b) equal to that value.
Changing the reliability premium associated with incident delay reductions has an effect similar to changing the value of ordinary travel time, though smaller in magnitude. Increasing the reliability premium to 3.0 makes incident delay-reducing improvements relatively more valuable, thereby raising investment requirements by 1.7 percent at the Cost to Improve level. Reducing the premium to 1.0 results in a corresponding reduction of 1.4 percent in the investment estimate.
Value of a Statistical Life
HERS uses $3.0 million for the value of a statistical life, which is the USDOT’s standard value for use in benefit-cost analyses. As in the case with the value of time, there is a great deal of debate about the appropriate value, and no single dollar figure has been uniformly accepted by the academic community or within the Federal Government.
Doubling the value would increase the Cost to Improve Highways and Bridges by 0.4 percent. HERS would find a few more projects to implement on the basis of their increased safety benefits if the value of life were increased. Reducing the value of a statistical life by 50 percent would reduce the Cost to Improve Highways and Bridges by 0.2 percent. A few marginal projects that were justified based on potential reductions in crash rates would not be implemented if the value of life used in the analysis were reduced.
Changing the value of a statistical life in HERS does not have a significant impact on the estimates of annual investment requirements. The model is not currently equipped to consider all the safety benefits of highway improvements or safety-oriented projects. Improving the HERS model’s capabilities in this area will be the target of future research.
The unit improvement costs used in HERS to calculate total investment costs may themselves be subject to uncertainty. For example, currently unforeseen circumstances may cause highway construction costs to increase faster than the general rate of inflation in the future. It is therefore prudent to consider the impact of higher-than-expected capital improvement costs, in order to ensure that non-cost-beneficial projects are not mistakenly included in the investment requirements estimated by HERS.
Exhibit 10-2 shows the impact of inflating all the improvement costs used by HERS by 25 percent on the Cost to Improve Highways and Bridges. The increase in investment requirements due to higher unit values for the improvement costs is partially offset by the elimination of some projects that would no longer be considered cost-beneficial by HERS. The net result is an increase of 16.1 percent in the estimated investment requirements.
Truck VMT Shares
The HPMS sample data used in HERS include values for the percentage of single-unit and combination trucks in the current vehicle mix on each segment. Forecasts of future traffic, however, are not broken down by vehicle class, meaning that the data effectively assume no changes in truck shares. Many national forecasts of future VMT, however, indicate that truck travel is expected to grow faster than passenger auto travel.
The HERS model includes a parameter for adjusting the truck share on each functional class over time according to an exogenously specified value, thus allowing the model to simulate changes in the vehicle mix over the 20-year forecast period. The factor used to generate the changes in HERS was drawn from a recent projection of future VMT for different vehicle classes made for FHWA (referenced in Chapter 9). The data in that study suggest that the average VMT share of trucks is expected to increase from 7.7 percent in 2000 to 9.2 percent in 2020. Exhibit 10-2 indicates that accounting for such a change within the HERS estimation procedures would increase the Cost to Improve Highways by 0.4 percent. HERS finds a small number of additional projects to be cost beneficial when the larger truck shares are accounted for.
Impacts of Alternative Parameters on the Cost to Maintain Highways and Bridges
The impacts of alternative model parameters and procedures on the estimated investment requirements are more ambiguous for the Cost to Maintain Highways and Bridges (see Exhibit 10-3) than for the Cost to Improve results reported above. This is due to the way in which the Cost to Maintain Highways and Bridges is defined in this report. (See Chapter 7.) The HERS-modeled portion of this cost was based on the Maintain User Cost scenario, in which investment is sufficient to allow average highway user costs for 2020 as calculated by HERS to match the initial levels in 2000. The initial calculation of user costs, however, is directly affected by many of the parameters shown in the exhibit, including the values of time, incident delay, statistical life, and truck shares. As a result, the average user cost that is maintained will be different for alternative values of these parameters, so the reader should exercise caution in interpreting Exhibit 10-3. The impacts of alternative values on the Cost to Improve, however, are based on implementing all cost-beneficial projects and are thus not subject to this same caveat.
In the case of the ordinary travel time, reliability premium, and value of statistical life parameters, increasing the value of these parameters also increases the initial calculated value of user costs. Maintaining this higher level in the future may thus artificially require a smaller amount of future capital investment, due solely to the change in the baseline values. The effect is to lower the estimated Cost to Maintain when these parameters are increased, while the opposite is true for reduced values of the same parameters.
Increasing the share of trucks over time has the opposite effect on the Maintain User Costs scenario in HERS. Since trucks have higher travel time and vehicle operating costs than do passenger vehicles, an increasing truck share will cause average user costs to rise as well. More investment is then required to maintain user costs at the initial level. For the elasticity parameters, a larger value will cause more travel to be suppressed in the future, thereby reducing investment requirements.
Increasing the unit improvement costs in HERS by 25 percent causes a slightly less-than-proportional increase in the estimated Cost to Maintain Highways and Bridges. The reason for this is that the Cost to Maintain includes bridge preservation investments modeled in the National Bridge Investment Analysis System (NBIAS), which are not affected by changes in the HERS parameters.