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Belief-Based Model of Career Dropout Under Monopsonistic Employment and Noisy Evaluation

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  • Iñaki Aliende

    (Faculty of Economics and Business, Complutense University of Madrid, 28223 Madrid, Spain)

  • Lorenzo Escot

    (Faculty of Applied Statistics, Research Institute for Statistics and Data Science, Complutense University of Madrid, 28040 Madrid, Spain)

  • Julio E. Sandubete

    (Faculty of Law, Business and Government, Universidad Francisco de Vitoria, 28223 Madrid, Spain)

Abstract

This paper develops a belief-based dynamic optimisation framework to explain career continuation decisions in settings characterised by monopsonistic employment and asymmetric performance evaluation. Extending Holmström’s career concerns model, we consider agents who must decide whether to continue or exit their vocation based on subjective beliefs updated from noisy signals. Unlike the original framework, our model assumes a single institutional employer and limited feedback transparency, turning the agent’s decision into an optimal stopping problem governed by evolving belief thresholds. Analytical results demonstrate how greater signal noise, higher effort costs, and more attractive outside options raise the probability of exit. To validate the framework, we confront belief-based dropout decisions using original survey data from over 8000 football referees in Europe, showing that threats, unmet development expectations, and perceived stagnation significantly predict dropout. The results offer practical insights for institutions, such as sports federations, academic bodies, and civil services, on how to improve retention through increased transparency and better support structures. This study contributes to the literature by integrating optimal stopping theory and dynamic labor models in a novel context of constrained career environments.

Suggested Citation

  • Iñaki Aliende & Lorenzo Escot & Julio E. Sandubete, 2025. "Belief-Based Model of Career Dropout Under Monopsonistic Employment and Noisy Evaluation," Mathematics, MDPI, vol. 13(17), pages 1-23, September.
  • Handle: RePEc:gam:jmathe:v:13:y:2025:i:17:p:2879-:d:1743499
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