Measuring wage premiums for job risks.

Measuring wage premiums for job risks

During the past 10 years, a large amount of research has been devoted to measuring the wage premiums which workers receive as a result of bearing additional occupational injury and illness risks. Improved estimates of the premiums are of value for policy evaluation because they are used to assess the benefits of proposed occupational safety and health regulations.

The motivation for this research is the idea that, in general, if a worker has a choice between two jobs of different riskiness, he will choose the riskier one only if it pays a sufficiently higher wage. The wage premium for bearing extra risk is known as a compensating wage differential, because the premium is viewed as being paid to compensate for the additional riskiness. A compensating differential should not be confused with workers' compensation benefits. The former is paid as a component of wages, while the latter is an indemnity benefit paid only if a worker is injured. They are related, however, in that both are paid to compensate a worker for the costs he bears in the event of an injury or illness.

Research on measuring compensating differentials endeavors to explain observed variations in wages by means of an equation which relates worker and job characteristics to wage levels. Let W represent the wage level, X represent worker and job characteristics known to affect wages, such as education or experience, and let R represent the riskiness of a job. It is hypothesized that wages are related to X and R through the equation W = a bX

cR where b and c are coefficients which indicate by how much wages change with unit increases in X and R. For example, suppose that R measures the number of injuries and illnesses incurred by 100 workers in 1 year, that W measures weekly wages, and that c has a value of 5. Then the equation indicates that an increase in the riskiness of a job of 1 case per 100 workers per year is associated with an increase in weekly wages of \$5. The object of empirical work on compensating differentials is to obtain better estimates of c from data sets containing information on wages and worker and job characteristics.

In a recent paper, we examine two issues in the measurement of compensating differentials. First, we study to what extent the differentials differ for men and women and for union and nonunion workers. Second, we analyze the impact of including a measure of workers' compensation benefits in the wage equations used to estimate the differentials.

The primary source of the data was a sample of private nonagricultural blue-collar and service workers drawn from the May 1980 Current Population Survey. Separate wage equations were estimated for union men, nonunion men, union women, and nonunion women. Standard education, experience, and demographic characteristics were included as X variables in the wage equations. In addition, two measures of job risk and a measure of workers' compensation benefits were included as variables explaining wage variations. The job risk variables, obtained from the Bureau of Labor Statistics' 1980 Annual Survey of Occupational Injuries and Illnesses, measure the number of lost workday injury and illness cases per 100 full-time workers and the number of lost workdays per lost workday case. These measure the frequency and severity of injury and illness cases by industry, respectively. The workers' compensation variable measures the proportion of weekly wages replaced by total temporary disability benefits. It was imputed from information on the workers' weekly wages and characteristics and the State laws regarding benefit payments.

Three principal conclusions emerge. First, there is strong evidence of compensating wage differentials for both union and nonunion men. Men receive higher pay to work at riskier jobs; for women, however, the evidence is not as conclusive. Only female union members appear to receive higher wages for riskier jobs, and even here the evidence is not as strong as for men. It is conceivable that the lack of evidence for women suggests that they indeed do not receive wage premiums for job risk. It is equally possible, however, that the poor results for women suggest that the industry job risk variables, which are not available by sex, do not adequately represent the job risks faced by female employees of high-risk industries. Women tend to be underrepresented in these industries and, within them, they tend to work in the low-risk occupations.

A second finding of the research is that, everything else being the same, an increase in the proportion of wages replaced by workers' compensation income benefits leads to a drop in the wage level. This result is stronger for women than for men. A final surprising rsult is that the inclusion of the workers' compensation benefit variable in the wage equations has no effect on estimated compensating wage differentials. Also, coefficients on the interaction of workers' compensation benefits with the risk variables are generally statistically insignificant.

The study and its results are described in full in the paper "Workers' Compensation Benefits and Compensating Wage Differentials,' by John W. Ruser, BLS Working Paper No. 153.--John W. Ruser, Office of Research and Evaluation, Bureau of Labor Statistics.
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