October 2013

Using data from the Census of Fatal Occupational Injuries to estimate the “value of a statistical life”


Fatality rates by industry and occupation

A breakdown of CFOI risk levels that is useful in empirical work is a matrix of the risks by industry and occupation. Industry risk levels are still the primary focus of most analyses because there is less measurement error in workers reporting their industry than their occupation,3 but utilizing risk measures that incorporate some differentiation in risk levels by broad occupational group remains desirable in order to capture occupational variation in riskiness. For the early years of CFOI data, the industry codes were the Standard Industrial Classification (SIC) codes and the occupation codes were the U.S. Census Bureau codes. Beginning in 2003, the CFOI adopted the North American Industrial Classification codes for industries and the Standard Occupational Classification codes for occupations, and some additional changes were made starting in 2011. To avoid the greater measurement error problems associated with individuals’ reported occupations, most industry–occupation breakdowns appearing in the literature have utilized relatively refined groupings of 50–72 industries coupled with higher level groupings of about 10 major occupations.

Table 1 provides summary fatality rate measures by industry and occupation for an illustrative set of 10 nonagricultural industries and 10 occupations. The measures were constructed with the use of CFOI fatality data from 2003 to 2008 in conjunction with hours-weighted employment data based on Current Population Survey (CPS) Merged Outgoing Rotation Groups (MORGs).4 Average hours were calculated by industry, occupation, and year. In 2007, the BLS released both an hours-weighted approach to calculating the fatality rate and the employment-based approach it had been using until then. The BLS moved completely to the hours-based approach in 2008. The estimates in table 1 incorporate the hours-based methodology.5 Only workers in the age range from 16 to 64 years are included. Using multiple years of data reduces the influence of random year-to-year fluctuations in fatalities—fluctuations that may be particularly problematic for small industry–occupation cells. In 10 instances in table 1, the risk level is not reported because values did not meet BLS publication criteria.

Table 1. Fatality rates, by industry and occupation, 2006–2008
TotalConstructionFinance, insurance, and real estateInformationManufacturingMiningPublic administrationRetail tradeServicesTransportation and public utilitiesWholesale trade
Management, business, and financial1.
Professional and related.
Office and administrative support.
Farming, fishing, and forestry8.3(1)(1)(1)6.7(1)10.38.619.415.54.6
Construction and extraction1211.84.8(1)6.634.
Installation, maintenance, and repair6.913.
Transportation and material moving15.821.615.328.27.925.413.95.714.122.411.4
Industry average10.


(1) Data did not meet BLS publication criteria.

Note: Fatal injury data were obtained with restricted access to the Census of Fatal Occupational Injuries research file.

Source: U.S. Bureau of Labor Statistics.

Both the average industry risks and the average occupational risks exhibit substantial variation across the sample. The average fatality rates by industry per 100,000 workers range from 1.0 to 20.7, and the average occupational fatality rates range from 0.5 to 15.8. There is also considerable within-industry variation in risk by occupation. In the case of the construction industry, for example, the fatality rate per 100,000 workers ranges from 0.6 for office and administrative support workers to 21.6 for transportation and material moving occupations.

The manner in which researchers choose to refine the fatality rate measure depends in part on the focus of the research. The fatality rate dimensions that have been considered by different studies in the CFOI literature include industry, occupation, age, race, immigrant status, and type of accident, as well as various interactions among these dimensions. At the extreme, one could analyze risk levels defined on all of the dimensions. However, doing so will create a large set of fatality rate categories, leaving many empty cells, as well as many other cells with low risk levels that are measured imprecisely.


3 Wesley Mellow and Hal Sider, “Accuracy of response in labor market surveys: evidence and implications,” Journal of Labor Economics, October 1983, pp. 331–344.

4 According to the National Bureau of Economic Research, MORGs “are extracts of [CPS] Basic Monthly Data [obtained] during the household’s fourth and eighth month in the survey, when [questions about] usual weekly hours/earnings are asked.” (See “Current Population Survey (CPS) Data at the NBER” (Cambridge, MA: National Bureau of Economic Research, updated daily).)

5 The procedure followed in the hours-based methodology is described in footnote 2 of “Fatal occupational injuries, annual average hours worked, total employment, and rates of fatal occupational injuries by selected worker characteristics, occupations, and industries, 2007” (U.S. Bureau of Labor Statistics, 2007),

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About the Author

W. Kip Viscusi

W. Kip Viscusi is University Distinguished Professor of Law, Economics, and Management, Vanderbilt University, Nashville, TN