In this paper, we address the identification and estimation of insurance models where insurees have private information about their risk and risk aversion. The model includes random damages and allows for several claims, while insurees choose from a finite number of coverages. We show that the...

When formal insurance is unavailable, mutual insurance among households can serve as an alternative. This paper analyzes a game between economic agents facing uncertainty and maximizing discounted utility without enforceable contracts or access to capital markets. While autarky is always a...

The objective of this paper is to pursue an intuitive idea: for a consumer who represents an "unfavorable" health risk but an "excellent risk" as a driver, a multi-peril policy could be associated with a reduced selection effort on the part of the insurer. If this intuition should be confirmed,...

Peer-to-peer insurance models combine insurer's underwriting with peers' risk sharing. This paper presents a mathematical formulation of two emerging peer-to-peer insurance models: the individual-covered model and the group-covered model, and establishes their equivalence for a homogeneous...

This study investigates the risk allocation problem of distributed insurance based on blockchain technology in the presence of costs. Blockchain technology changes traditional insurance companies, who no longer bear the risks of policyholders. Instead, they build platforms to connect...

Purpose The authors consider the mutual benefits of the ceding company and reinsurance company in the design of reinsurance contracts. Two objective functions to maximize social expected utilities are established, which are to maximize the sum of the expected utilities of both the ceding company...

The objective of this paper is to pursue an intuitive idea: For a consumer who is an unfavorable health risk but a “better risk” regarding a second peril, would a multi-peril policy not be associated with a reduced selection effort on the part of the insurer? If this intuition should be...

This paper investigates Pareto optimal (PO, for short) insurance contracts in a behavioral finance framework, in which the insured evaluates contracts by the rank-dependent utility (RDU) theory and the insurer uses the expected value premium principle. The incentive compatibility constraint is...

Most of the previous research in the asymmetric information problem treats adverse selection and moral hazard separately, though they may coexist and interact with each other. We build a principal-agent model to examine optimal contracts in a competitive insurance market facing adverse selection...

We study a generalization of the classical monopoly insurance problem under adverse selection (see Stiglitz [1977]) where we allow for a random distribution of losses, possibly correlated with the agent’s risk parameter that is private information. Our model explains patterns of observed...

This article studies insurance demand in a two-period framework in which an individual faces risks in both current and future periods. Models for insurance with and without the presence of endogenous saving are both discussed. In contrast to what most literature suggests, when decisions on...

Part 1 History - Developments in risk and insurance economics: The past 50 years -- Part 2 Climate risk protection - Fifty years of US natural disaster insurance policy -- Climate risk and insurance -- Household financial resilience after severe climate events: The role of insurance -- Insuring...

Low demand for crop insurance, even when subsidized at highly favorable rates, remains a challenge for policymakers in developing countries attempting to create insurance-based farm safety nets. Evidence from a series of surveys and experiments with 477 vegetable farmers in China reveals several...

Purpose: Operational risks appear as the main threats of the modern world. Mistakes made by employees, an imperfect information systems or changes in the law can cause losses that businesses today are not even able to estimate. Therefore, in the face of widespread the asymmetry of information,...

Bundled insurance contracts, providing protection based on several loss coverages, are attractive because they allow insurers to focus on the needs of the policyholder. A common contract feature is a deductible set so that the insurance pays the excess over the deductible of the sum of losses...

The optimal amount of property/land title insurance coverage under both the Torrens and Recording systems remains controversial and this article introduces decision models and shows that the optimal title insurance evolves as market and property-specific conditions change. The models can also be...

A smart mutual peer-to-peer insurance contract is a financial innovation that combines blockchain technology and a mutual insurance contract. This paper constructs a three-stage game theory model of the mutual insurance platform. The role of blockchain technology in solving the claim fraud...

All insurance products are bundles. For example, medical insurance bundles oncology and cardiology insurance. What determines which risks are insured together, and is this welfare enhancing? Theoretically, I introduce selection- costs correlated with willingness-to-pay- into a model of bundling...

In theory, guaranteed renewable (GR) insurance contracts can efficiently insure against reclassification risk without causing adverse selection on pre-existing conditions. In practice, however, adverse selection can still arise on other dimensions. In 2020, in response to protests demanding...

The purpose of this paper is an analysis of the presence of self-selection mechanisms on the market that could bring the market closer to the separating equilibrium state, in line with the Rothschild-Stiglitz equilibrium model and its subsequent modifications. An example is the Polish market of...

Why are insurance markets for new or nonstationary risks often tiny, even when those risks are massive? To answer this question, I develop a general formalism (“CUE”) for dynamic non-Bayesian learning and decisionmaking where decisionmakers penalize model uncertainty. First, I show that data...