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3 juillet 2022
- 2207.01010
Mots-clés
Computer Science - Multiagent Systems Computer Science - Machine Learning Economics - General EconomicsSujets proches
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Menna Hassan et al., « Government Intervention in Catastrophe Insurance Markets: A Reinforcement Learning Approach », arXiv - économie
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Résumé
This paper designs a sequential repeated game of a micro-founded society with three types of agents: individuals, insurers, and a government. Nascent to economics literature, we use Reinforcement Learning (RL), closely related to multi-armed bandit problems, to learn the welfare impact of a set of proposed policy interventions per $1 spent on them. The paper rigorously discusses the desirability of the proposed interventions by comparing them against each other on a case-by-case basis. The paper provides a framework for algorithmic policy evaluation using calibrated theoretical models which can assist in feasibility studies.