Unemployment Policy Model via Multistage Stochastic Programming

In this paper, there is proposed a model of unemployment policy for institution that has to reduce unemployment's costs, but it cannot change the governmental policy. This institution has also to pay every month for subsidized workplaces otherwise it has to compensate the worker for releasing her/him. The model uses a "socially critical" rate of unemployment, the rate which should be reduced at all costs. This problem can be seen as the problem of multistage stochastic programming because the compensation of the worker can be cheaper than paying the subsidy every month. The model is demonstrated on the Most region (the Czech region facing the worst unemployment situation), and the four-stage model is solved using scenario-based method in the GAMS language on NEOS system.