The paper addresses several key issues in the field of game theory, namely: determination of the perfect Bayesian equilibrium for signaling games - the pure strategy case; signaling on the labor force market; application of the signaling game on the labor force market of EU-27. The analysis of the perfect Bayesian equilibrium for signaling games - the pure strategy case has lead to the following conclusion: if the Sender strategy is unifying or separating then the equilibrium will be called unifying or, respectively separating.In the section Signaling on the labor force market, there are issues regarding the complete information case, where we suppose that the worker’s ability is common information for all players, but also issues regarding the incomplete information case. Three types of perfect Bayesian equilibriums may exist in this last model: unifying equilibrium, when both types of workers choose a single type of education; separating equilibrium, when the perfect Bayesian equilibrium is separating by itself, and hybrid equilibrium, if a worker chooses a level of education with certainty, the other one may randomly choose between joining the fist one (by selecting the level of education of the first type) and getting separated from him (by selecting a different level of education).This analysis allows us to draw the following conclusions: in case of signaling games on the labor force market, the pure strategy case, three types of equilibriums are available: unifying, separating and hybrid; as the worker’s ability is private information, this allows a low ability worker to pretend to be a high ability worker; the low ability workers find it more difficult to accumulate additional education requiring higher wages in return; besides the classical separating equilibrium, same as for the unifying equilibrium, there are other separating equilibriums implying a different educational choice by the high ability worker; sometimes the separating equilibrium becomes the limit of the hybrid equilibrium. The application is meant to strengthen, at least partially, given the lack of consistent data, the theoretical results.
