We estimated both fatal and non-fatal motor vehicle crash injuries by state and industry.
Our state fatality estimation used three data sets: (1) the National Highway Traffic Safety Administration’s (NHTSA) 1994 Fatal Accident Reporting System (FARS), (2) the U.S. Bureau of Labor Statistics’ 1994 Census of Fatal Occupational Injuries (CFOI) (see Jack and Zak, 1995), and (3) the National Institute for Occupational Safety and Health’s 1980-1989 National Traumatic Occupational Fatalities (NTOF) data (see Jenkins et al., 1993).
To estimate occupational fatalities by state, we used the CFOI fatality count. To reduce the effects of random variation with very small sample sizes, if the CFOI state count was less than nine we used the NTOF average of motor vehicle traffic fatalities (1980-1989). This resulted in an estimated 2,026 U.S. on-the-job motor vehicle fatalities. To get off-the-job motor vehicle-related fatalities, we subtracted the state occupational highway fatality estimates from the 1994 FARS state totals (all ages). (We multiplied the off-the-job fatality estimate by the employer cost per off-the-job fatality averaged over all such fatalities, including fatalities of children, unemployed people, and retirees. We assume that all people under age 65 are workers or dependents.)
To calculate the number of non-fatal occupational injuries, we used four different data sources: the 1993 FARS, the 1994 police-reported state non-fatal injury counts (Blincoe, 1996), the 1993 CFOI, and the National Health Interview Survey (NHIS) 1987-1992. (The NHIS is a nationwide sample of civilian households. It includes information on injuries, whether they were on-the-job, and where they occurred.)
The number of injured on-the-job motor vehicle crash survivors by state was computed in four stages. We started from state counts of police-reported crash survivors, adjusted for police under-reporting of injury. The police reports documented an estimated 70% of the total injury victims (Blincoe, 1996). From these injury counts and FARS fatality counts, we computed the number of injured crash survivors per crash fatality by state. That ratio was multi-plied by the CFOI count of occupational motor vehicle fatalities by state. (This calculation assumes that the percentage of crash fatalities on public roads, 81%, matches the NHIS percentage of on-the-job crash survivors who were injured on public roads.) Finally, the resulting estimates were multiplied by the percentage of injured survivors of motor vehicle crashes on public roads who were injured on the job divided by the percentage of motor vehicle crash fatalities on public roads who died on the job. The percentage of survivors, 5.25%, came from the NHIS. The percent-age of deaths, 4.3%, was computed by dividing the CFOI count by the FARS count.
To distribute the injured survivors of on-the-job crashes by industry, we used the SOII distribution of survivors of lost-workday occupational injuries by two-digit Standard Industrial Classification Code. The SOII excludes medically treated survivors without workdays lost, whom the NHIS estimates are 41.5% of the total. It also does not cover all workers. Notably, it excludes government workers and self-employed truck and taxi drivers. (To estimate injury survivors in the government sector, we multiplied the number of survivors per fatality for the service sector by the CFOI fatality count for government employees.) Beyond its under-coverage problem, the SOII appears to under-count motor vehicle crash injuries. It records only 50,336 of the estimated 195,000 injured survivors of on-the-job crashes.
This update relies on CFOI data to calculate on-the-job motor vehicle fatalities. In previous estimates, the CFOI was used in conjunction with the FARS to estimate on-the-job fatalities. The CFOI has increasingly been accepted as a reliable source of fatality counts. Our reliance on the data results in a drop in the estimated number of occupational fatalities (and the associated costs) from prior reports. The drop does not indicate a trend in the number of fatalities.
Incidence of commercial vehicle crashes used to calculate cost per crash is from a previous Miller study (Miller et al., 1991). The number of commercial vehicle crashes was 1,595,000. Twenty percent of these crashes caused injuries.
Commercial vehicle miles traveled were estimated from two sources. Total vehicle miles traveled in 1994 (2,347 billion) is from Traffic Safety Facts, 1994. The percentage of vehicle miles driven by commercial vehicles (15.8%) was calculated from the Nationwide Personal Transportation Survey, 1990. This percentage was multiplied by the 1994 total number of vehicle miles traveled for an estimate of 371 billion commercial vehicle miles traveled in 1994.
Medical, productivity, emergency services, property damage, legal, and non-liability insurance claims processing costs were estimated with SOII occupational injury survivor counts by vehicle type occupied or pedestrian status and costs per crash victim by vehicle type occupied or pedestrian status from Miller et al. (1996). The costs then were distributed into more detailed categories with the distribution in Miller (1992). Other costs per case and costs in Table 4 are from Miller (1992). These costs were inflated to 1995 dollars using inflators (medical spending per capita, employment cost index, and consumer price index — all items) calculated from the 1996 Economic Report of the President. Employer crash costs were adjusted to specific states using ratios of state to national costs. The medical and composite state price adjusters were calculated from the ACCRA Cost of Living Index. The wage adjuster was calculated from estimates of personal income per capita by state in the 1995 Statistical Abstract of the United States. Costs per employee in Table 5 were calculated using the number of employees by state from Table 626 of the 1995 Statistical Abstract of the United States.
Societal crash costs are updated from Blincoe and Faigin (1992) and Miller (1992) using the refinements from Miller (1993). Average growth in GNP was computed from Tables B-23 and B-59 of the 1996 Economic Report of the President.
Total employer health fringe benefit costs (Figure 1) were computed following the methods in Miller (1992). Sources of data were as follows: sick leave, from Table 683, 1995 Statistical Abstract of the United States, and Table B-25, 1996 Economic Report of the President; workers’ compensation, from Table 604, 1995 Statistical Abstract of the United States; disability insurance, from Table 586, 1995 Statistical Abstract of the United States; health insurance, from Table 156, 1995 Statistical Abstract of the United States; life insurance, from Table 845, 1995 Statistical Abstract of the United States, and Table 6 (Methods) in Miller (1992); and Social Security disability insurance, from Table 593, 1995 Statistical Abstract of the United States.
Costs in Table 6 were assigned to non-fatal injuries by vehicle type. These costs were determined in a recent analysis of highway crash costs (Miller et al., 1996). Fatal crash costs were assigned on a per case basis. The number of employees by industry came from Table 668 of the 1995 Statistical Abstract of the United States. The wage-risk premium was calculated as an average per worker across all industries. Wage-risk premiums are implicit costs to employers to compensate workers for increased risk levels. Since the premiums are implicit and not a direct monetary cost, they were separated from the other costs.
This year’s report employs new methods to cost motor vehicle crashes to employers. The methodology was changed to clean up problems in using average costs per injury. Instead, we assigned costs by vehicle type involved in the crash. By adjusting to vehi-cle type, we more accurately estimated the cost of motor vehicle crashes to employers. As a result, increases to health fringe and non-fringe costs will change by different magnitudes. The most noticeable difference from previous estimates is the decrease in the wage-risk premium. This is attributable to a separate estimate of commercial vehicles used on the job. Commercial vehicles have a lower average non-fatal injury severity and cost than non-commercial vehicles. Thus, average costs and total wage-risk premiums are lower than the all-vehicle average used in prior years.