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risk premiums will occur, while preferred characteristic is hardly supply is sufficient enough. If these characteristics are not enough to supply, only those workers with preferred properties work in risky jobs and no differential risk premium will occur in the market (ibid: 284).

 

Consider the following regression model example:

 

Where is the observed wage, is risk, is the worker's age, and the 's are coefficients in the regression.

 

Age would probably have an impact on the acceptance of wage. Young workers will put the future of consumption in danger with regard to acceptance of higher risk and at the same they have much more to lose than older coworkers. In this case, the supply price of hazardous jobs should fall with age. Moreover, an individual may minimize or maximize his risk aversion over his lifetime, and it leads to changes based on the acceptance of wage function over his lifetime. Therefore, the age systematically related to job risk because of these two reasons mentioned above. Age can affect the market risk premium only as long as it reflects unmeasured characteristic will affect production by differential risk. The risk will have different effects on people and will make some people more efficient and some others less effective. This means that they are unable to complete their work, but will also place additional costs on others. Both effects will reduce the wage rate for these people if they are observed in the dangerous jobs. Therefore wage differentials are being a kind of compensation for costs incurred by hiring such labor (ibid: 285).

 

Thaler and Rosen (1975) uses a data set from 1967 as Survey of Economic Opportunity (SEO). The dataset was created to represent those with the most low-income population in 9488 which contained representatives of U.S. households. The data set was reduced to only male heads of the household. Data Set offers information about personal and industry-based characteristic. It also contained industry of employment and occupation of the individual. Also data describing industrial hazards car published by the Bureau of Labor statistics (BLS) conducted by a year period 1955-1967 (ibid: 286).

 

Thaler and Rosen (1975) his goal was to estimate the equalizing difference function W (). They used four independent variables to control factors when determining salary rate than the job risk. These are the contents of the variable C. The first set controls regional wage differentials. The second set measures the staff characteristic of individuals that include age, education, size of family or marital status, and race. It could have been included age squared and education squared for other nonlinear characteristic. The third set-controlled for other characteristic of the job, including union and dummy variables for manufacturing and service industries (ibid: 289).

 

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