Resumen

This paper studies how ambiguity—uncertainty about the true distribution of risks—affects equilibrium outcomes along the insurance chain. I extend a Stackelberg game to analyze the interactions between a reinsurer leader, who is neutral to both risk and ambiguity, and two ambiguity-averse insurers who compete in a linear city model to offer coverage to risk- and ambiguity-averse policyholders. Unlike standard models that focus solely on risk or examine only parts of the insurance chain, this framework captures the full structure and explicitly separates ambiguity and risk preferences. I find that: (a) ambiguity aversion and imperfect competition lead to partial coverage and premiums above actuarially fair levels; (b) when insurers become more sensitive to ambiguity, coverage falls and premiums rise; and (c) when shocks affect only policyholders, insurers offer more coverage and the effect on premiums depends on the degree of their market power. These findings show that ambiguity influences insurance outcomes in ways that risk alone cannot, providing a rationale for observed patterns that standard models fail to explain.