Government interventions in microinsurance: evidence from China

Abstract

The microinsurance market suffers from severe market failures; thus, government interventions are increasingly used to stimulate its functioning. Our article evaluates, from a law and economics perspective, whether these interventions are effective in increasing access to insurance without inducing moral hazard and adverse selection. We then use this framework to evaluate typical types of government interventions in the Chinese microinsurance market (subsidisation, simplification, use of group policy and established distribution channels). Using practical cases, we further identify solutions to remedy the market frictions induced by government interventions. We find that government interventions are only effective under certain conditions: (1) stable and smartly designed subsidies are provided or innovative market practices are subsidised; (2) insurance policies are easy to understand; (3) product distributors are properly trained or licensed; (4) group policies can be renewed.

Microinsurance in Effort To Enhance Indonesia's Economic Resilience

“…This implies that the newly implemented government policies primarily focus on safeguarding financing institutions rather than business actors themselves. The Government interventions are only effective when innovative market practices are designed and insurance policies are easy to understand in this case is microinsurance (Yan & Faure, 2021). We believe that bridging the gap between risk exposure and the sufficiency of these policies requires collaborative efforts between micro finance institutions in the realm of financing and general insurance companies in terms of protection.…”

Innovations in microinsurance research

“…The authors have used a wide range of methodologies: from empirical analysis based on surveys (Akomea-Frimpong et al 2021 ) to aggregated data (Tiemtore 2021 ), panel data based on more extensive empirical or experimental research (Banerjee and Savitha 2021 ), as well as logit (Cai et al 2021 ) or probit regressions (Alhassan and Magazi 2021 ). Also, we included conceptual frameworks (Yan and Faure 2021 ) and an intensity‑based semi‑parametric multivariate recurrent event model (Zhang et al 2021 ). Our thanks go to the authors for that.…”