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6 expenditures and includes external or social costs. The most knowledge with respect to state HCASs in several states. recent Oregon HCAS presented two examples to illustrate This was discovered when on several occasions the respon- the difference between cost- and expenditure-based ap- dent mistakenly indicated that no study had been done when proaches. When considering studded tire damage, the costs the research team was aware of a previous study conducted far exceed the expenditures, as evidenced by the extensive in the respondent's state. The research team was able to as- presence of rutted roads in that state. To the extent that road sist the respondent in correcting the survey in some instances expenditures fall short of what is required to fix the problem, whereas in others, the research team was aware of but did not the full costs are not allocated to the highway users. Also, possess the study in question. Thus, the responses summa- Oregon has embarked on a major bridge rehabilitation pro- rized in Appendix B may in some cases not capture the full gram with related expenditures having a significant effect on extent of the state HCAS experience owing to the absence of the results of the HCAS. The expenditures associated with institutional knowledge. this major restoration effort will bear little resemblance to the costs imposed on the system during the period when the Table 1 identifies each state that has performed an HCAS reconstruction is occurring. Thus, nearly all HCASs do not (column 1) and the years in which the studies were com- allocate full costs; rather, they allocate responsibility for the pleted (column 2). The column 3 results demonstrate that the expenditures tied to the highway program. Incremental and Federal Methods have historically been the principal methods used to conduct state HCASs. Each of States have also considered applying the benefits-based these methods is commonly referred to under the umbrella of approach. In this approach, the benefits tied to the use of the cost-occasioned approach. The cost-occasioned approach roadway systems would be measured and allocated to high- determines cost responsibility based on the costs occasioned way users. This method results in an extension of HCASs to by various highway-user classes. This approach attempts to non-users. Extending the study to non-users is theoretically allocate cost responsibility based on the costs imposed by valid to the extent that non-users, or society, benefit directly each class of highway users rather than simply allocating the from the roadway network; however, this approach is com- costs based on relative use. plicated because the great bulk of non-user benefits are actually second- or third-round benefits passed on through The percent of heavy-truck cost responsibility is pre- benefits to highway users. It is very difficult to distinguish sented in column 4. The historic results of state HCASs have such pass-through non-user benefits from other non-user varied widely with heavy-truck responsibility, from a low of benefits. Basing the HCAS on benefits received would en- 18.9% in the 1987 California HCAS to a high of 64.5% in the hance efficiency, as those who benefit from the road system 1979 Florida HCAS. The heavy-truck share varies widely would be required to pay in proportion to the benefits re- based primarily on the scope and type of expenditures in- ceived. This approach, however, has not been used at the cluded, but is also influenced by the proportion and type of state level for a number of reasons. First, the benefits cannot heavy-truck traffic, the definition of the heavy-truck class be measured directly. Second, the data required to under- [generally classified as vehicles weighing in excess of some stand the full benefits of the system and allocate those costs weight threshold between 10,000-lb and 26,000-lb GVW between competing interests would be much larger than (gross vehicle weight)], the methods used in the study, and the current HCAS data requirements. Third, benefits accrue to types of expenditures examined. The majority of the state individuals as both a user and a non-user of a system. Further, HCASs conducted to date have allocated between 30% and some benefits are already allocated in the marketplace. For 50% of the costs to the heavy-truck class. example, the benefits tied to the transport of goods by heavy trucks are recovered through shipping costs, which are paid The fifth column in Table 1 identifies the key allocators by the ultimate consumers of products. Thus, it would be dif- used in the state HCASs conducted to date. The allocator, or ficult to accurately capture the full range of benefits that need measure used to allocate costs to highway-user classes, is to be considered in the benefits-based approach. generally tied to either travel (e.g., VMT), the space vehicles take up on roads [e.g., passenger car equivalents (PCEs)], ve- STATE HIGHWAY COST ALLOCATION STUDIES hicle loads (e.g., ESALs), or a combination of these measures (e.g., ESAL-miles, ton-miles, axle-miles, and PCE-VMT). Table 1 presents the results and basic methods used in 85 state HCASs performed in the United States. Much of the data pre- Historically, state HCASs have focused on expenditures sented in the table were obtained from the 2005 Oregon High- from state revenue systems and state tax systems; however, way Cost Allocation Study conducted by ECONorthwest once the Interstate network was complete and federal and (2005). The data were updated based on the knowledge of the state funds became more interchangeable, recent studies research team and survey responses. Based on these sources, have in most cases examined at least state and federal funds the research team found 85 HCASs performed in 30 states. (Virginia and Wisconsin), whereas others have examined Undoubtedly, there are a small number of HCASs that have federal, state, and local funds in combination and in some not been captured in Table 1. Indeed, the survey process cases separately as well (Arizona, California, Idaho, Indiana, demonstrated that there exists a general lack of institutional Nevada, and Oregon).

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TABLE 1 STATE HIGHWAY COST ALLOCATION STUDY METHODS AND RESULTS % Heavy Vehicle Cost State HCAS Years Completed Method Key Allocators Types of Revenues Examined Responsibility 1993, 1999, 2000, VMT, Axle-Load, Arizona Federal 31.4% (1999) State, Federal, and Local Funds Combined 2001, 2002, 2005 Gross Weight Arkansas 1978 Incremental/Cost Function State, Federal, and Local Funds Analyzed California 1987, 1997 Federal and Incremental 18.9% ESAL-Miles Separately VMT, Truck-VMT, ESALs, Colorado 1981, 1988 Federal 37% Ton-Miles VMT, PCE-Miles, ESALs, Delaware 1992, 1993 Federal and Incremental 20.33% State and Federal Funds Combined Only Axle-Miles, Registrations VMT, ESALs, Axle-Miles, Florida 1979 Incremental 64.5% State and Federal Registrations Georgia 1979, 1982 Incremental 51.2% (1979) VMT, GVW, ESALs, AMT State and Federal Idaho 1987, 1994, 2002 Prospective Cost-Occasioned 37.29% VMT State, Federal, and Local Funds Combined 1984, 1988, 1989, Incremental/ Indiana 53.2% ESAL State, Federal, and Local 2000 Consumption ESAL, Ton-Miles, AMT, Iowa 1983, 1984 Federal 48.94% PCE, VMT Number of Vehicles, VMT, Kansas 1978, 1985 Hybrid 41.85% AMT, Ton-Miles, PCE-VMT, State Funds ESAL-Miles 1992, 1994, 1996, VMT, ESAL-VMT, Kentucky Federal 54.92% State and Federal Funds Combined 1998, 2000 PCE-VMT, Axle-Miles VMT, ESALs, PCE, Delphi, 1956, 1961, 1982, Maine Hybrid/Expenditure Allocation 35.6% TMT, Standard Vehicle State and Federal funds 1989 Equivalent Maryland 1989 State and Local Funds Minnesota 1990 Federal and Incremental 19.2% VMT, Truck-VMT (Continued on next page)

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TABLE 1 (continued) % Heavy Vehicle Cost State HCAS Years Completed Method Key Allocators Types of Revenues Examined Responsibility Mississippi 1980 Incremental 36% VMT, Truck-VMT Vehicle Size, Vehicle Weight, Missouri 1984, 1987, 1990 Federal VMT Montana 1992, 1999 Federal 33% VMT, ESAL-MT, AMT 1984, 1985, 1988, 1990, ESALs, VMT, Axle-Miles, State, Federal, and Local Separately and Nevada Modified Incremental 39.3% 1992, 1994, 1999 Ton-Miles Combined New Mexico 1972 PCE, ESALs, VMT, North Carolina 1983 Federal State and Federal Funds Weight Axle-Miles Ohio 1982 Federal/Incremental VMT 1937, 1947, 1963, 1974, Cost-Occasioned with Congested PCE, VMT, State, Federal, and Local Combined for Cost 1980, 1984, 1986, 1990, Oregon NAPCOM for Pavement Costs 34.1% Uphill PCE, Truck-VMT, Allocation Purposes but State Only for 1992, 1994, 1999, 2001, (Since 1999) Basic Vehicle VMT Revenue Attribution Purposes 2003, 2005, 2007 Pennsylvania 1989, 1990 Federal/Cost-Occasioned Texas 1984, 1985, 1994, 2002 Vermont 1990, 1993, 2006 Federal 25.7% VMT, ADT, ESAL State and Federal Funds Virginia 1991, 1992 Federal 21.7% ESALs, VMT, ADT State and Federal Funds Combined Washington 1977 Incremental Wisconsin 1982, 1992 Federal (1982) 31.7% ESAL, VMT, PCE, Ton-Miles State and Federal Funds Combined VMT, Vehicle Size, Wyoming 1981, 1999 FHWA State HCAS Model 55.8% Horsepower, Weight Adapted from ECONorthwest et al. (2005).