We analyse the effect of natural catastrophes on insurance demand in a developing economy and the role of insurance regulation in this relationship. The analysis is based on a theoretical model and a panel regression using data for Vietnam. What makes Vietnam especially interesting is the fact that it is strongly affected by natural catastrophes and experienced a change in insurance regulation in recent years. The theoretical results indicate that a loss experience likely has a less positive effect on demand in developing economies than in developed economies. A higher insurance penetration and a tighter insurance regulation, however, can make the impact of a loss event more positive. These findings are mirrored by our empirical analysis: overall natural catastrophes decrease insurance demand of affected households in Vietnam. The enhancement of regulation was not only accompanied by increased insurance demand but it also reverses the effect of natural catastrophes on demand.

Insurers draw on sophisticated models for the probability distributions over losses associated with catastrophic events that are required to price insurance policies. But prevailing pricing methods don’t factor in the ambiguity around model-based projections that derive from the relative paucity of data about extreme events. I argue however that most current theories of decision making under ambiguity only partially support a solution to the challenge that insurance decision makers face and propose an alternative approach that allows for decision making that is responsive to both the evidential situation of the insurance decision maker and their attitude to ambiguity.