Estimating individual occupational risk using registration data

Abstract

In this paper the occupational risk of individual employed workers is assessed using merged registration data. The analysis features a negative binomial count data regression model for statistical inference. In the model the hazard rate is determined by variables characterizing the personal background and working conditions, such as age, sex, tenure, contract type, working hours and sector. The estimation results can be used to assess individual occupational risk and identify high-risk groups and branches of industry. The main contribution of the paper to the literature is the fact that calculations include the entire population at risk and are based solely on registration data on individuals, jobs, firms and accident casualties.