Valuing insurance against small probability risks: A meta-analysis

Paper: arXiv 2402.16375

Authors: Selim Mankaï, Sébastien Marchand, Ngoc Ha Le

Abstract

The demand for voluntary insurance against low-probability, high-impact risks is lower than expected. To assess the magnitude of the demand, we conduct a meta-analysis of contingent valuation studies using a dataset of experimentally elicited and survey-based estimates. We find that the average stated willingness to pay (WTP) for insurance is 87% of expected losses. We perform a meta-regression analysis to examine the heterogeneity in aggregate WTP across these studies. The meta-regression reveals that information about loss probability and probability levels positively influence relative willingness to pay, whereas respondents’ average income and age have a negative effect. Moreover, we identify cultural sub-factors, such as power distance and uncertainty avoidance, that provided additional explanations for differences in WTP across international samples. Methodological factors related to the sampling and data collection process significantly influence the stated WTP. Our results, robust to model specification and publication bias, are relevant to current debates on stated preferences for low-probability risks management.

Complexity vs Empirical Score

• Math Complexity: 2.5/10
• Empirical Rigor: 7.5/10
• Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper relies on empirical meta-regression analysis rather than complex mathematical modeling to evaluate willingness to pay for insurance. It demonstrates strong statistical rigor through robustness checks for publication bias and model specification across international datasets.

Research Flowchart

  flowchart TD
    A[Research Goal: Assess Demand & WTP for Low-Probability Risk Insurance] --> B[Data Collection: Dataset of Experimental & Survey-Based Contingent Valuation Studies]
    B --> C[Meta-Analysis & Meta-Regression Analysis]
    C --> D[Mean Stated WTP = 87% of Expected Losses]
    C --> E[Key WTP Drivers & Determinants]
    E --> F[Positive Factors: Loss Probability Info, Higher Probability Levels]
    E --> G[Negative Factors: Higher Income, Older Age]
    E --> H[Cultural & Methodological Factors: Power Distance, Uncertainty Avoidance, Sampling Design]