Semi- Markov processes in labor market theory: The case of Switzerland

Narela Spaseski


The mathematical base of stochastic labor markets is the theory of Markov processes, and the uncertainty is its indivisible part. In this paper, Markov processes are used to calculate the equilibrium position, the time needed to reach it, natural rate of unemployment, transition probabilities and first passage time. While the theories of uncertainty give explanation why workers transit, identify the market anomalies and best fitted Markov model. The findings showed that the semi-Markov labor model better fits Switzerland data. Furthermore, the time needed to reach the equilibrium position is 4.6 years and the right number of employed workers, unemployed and inactive workers maintain the highest rate of uncertainty reduction is 67.16 %, 1.31 % and 31.54 % respectively, where 1.31% is the natural rate of unemployment. What is also important to point out is that the percent of employed workers in Switzerland is expected to decrease from 79.4% to 67.16%, while the percent of inactive workers is projected to increase significantly, from 15.9%to 31.54%. Workers who are expected to transit to an Inactive state in the future and stay there for a longer time are the older works (above 45 years). In other words, the Switzerland labor market is directed toward its “bad” equilibrium. In the end, the demographic structure is considered as one of the main factors for sustainable growth. Therefore, the government is suggested to control the population growth and put into practice new-innovative youth policies,becausethe traditional pro-family policies implemented to encourage bigger families has failed to increase the fertility rates to expected levels.


Semi-Markov processes, uncertainty reduction theory, Switzerland labor market, transient analysis

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Copyright (c) 2018 Narela Spaseski

ISSN 2233 -1859

Digital Object Identifier DOI: 10.21533/scjournal

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This work is licensed under a Creative Commons Attribution 4.0 International License