eThesis - School of Business electronic theses

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The aim of this study was to confirm the existence of and explore a hypothesized statistical relationship between sickness absence data and disability pensions within a population on an individual level. Using this information a statistical model was built to forecast disability pension risk and to study the distribution of employee health within organizations. The development of this model was motivated by the opportunities it would provide in financial forecasting and employee rehabilitation in Finnish government offices and agencies.

Within the scope of this thesis research on absenteeism and early retirement was reviewed. The reviewed literature covered a variety of geographical areas and incorporated several different approaches to the analysis of phenomena under study. The role of behavioral and psychological factors in these decisions was stressed and this was also the focus of the literature review. The theoretical insights were then used in the explorative analysis of a personal-level data set provided by the Finnish State Treasury and Ministry of Finance. The main model which was developed in this study was a state space model with logistic transfer functions. The specification of the states was performed on a theoretical basis, while the transfer functions were estimated statistically.

The findings of this study can be separated into two areas – academic findings related to sickness absences and the developed model for practical use. The exploratory data analysis has allowed making several important observations concerning sickness absence patterns prior to disability pension events. Two distinct sickness absence patterns were identified. Each of the sickness absence patterns has specific parameters in terms of duration and quantity of sickness absences.

The practical result of the study is the development of the state space model for evaluation of disability pension risk. The model provides reasonable short term forecasting power and allows studying and comparing employee health distributions within and between organizations. In this way the model acts as a powerful financial and managerial tool.