Deep reinforced learning enables solving rich discrete-choice life cycle models to analyze social security reforms. (arXiv:2010.13471v3 [econ.GN] UPDATED)

Discrete-choice life cycle models of labor supply can be used to estimate how
social security reforms influence employment rate. In a life cycle model,
optimal employment choices during the life course of an individual must be
solved. Mostly, life cycle models have been solved with dynamic programming,
which is not feasible when the state space is large, as often is the case in a
realistic life cycle model. Solving a complex life cycle model requires the use
of approximate methods, …

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