A Public-Private Insurance Model for Natural Risk Management: an Application to Seismic and Flood Risks on Residential Buildings in Italy

TL;DR

This paper develops a public-private insurance model for seismic and flood risks in Italy, aiming to enhance social welfare, evaluate risk profiles, and explore diversification benefits, while considering data limitations and risk correlations.

Contribution

It introduces a novel public-private insurance scheme for natural risks that emphasizes social welfare and risk diversification, with detailed risk modeling and analysis of spatial correlation effects.

Findings

Earthquake losses are nearly six times flood losses.

Public funds needed are similar for both perils despite different expected losses.

Risk diversification can reduce government intervention but may increase insurer exposure.

Abstract

This paper proposes a public-private insurance scheme for earthquakes and floods in Italy in which property-owners, the insurer and the government co-operate in risk financing. Our model departs from the existing literature by describing a public-private insurance intended to relieve the financial burden that natural events place on governments, while at the same time assisting individuals and protecting the insurance business. Hence, the business is aiming at maximizing social welfare rather than profits. Given the limited amount of data available on natural risks, expected losses per individual have been estimated through risk-modeling. In order to evaluate the insurer's loss profile, spatial correlation among insured assets has been evaluated by means of the Hoeffding bound for r-dependent random variables. Though earthquakes generate expected losses that are almost six times greater than floods, we found that the amount of public funds needed to manage the two perils is almost the same. We argue that this result is determined by a combination of the risk aversion of individuals and the shape of the loss distribution. Lastly, since earthquakes and floods are uncorrelated, we tested whether jointly managing the two perils can counteract the negative impact of spatial correlation. Some benefit from risk diversification emerged, though the probability of the government having to inject further capital might be considerable. Our findings suggest that, when not supported by the government, private insurance might either financially over-expose the insurer or set premiums so high that individuals would fail to purchase policies.