Micro health insurance is an important channel for financing health expenditure for low-income people, yet the supply of such programmes lags behind demand because many of them become unsustainable. Using individual-level dynamic data from a micro health insurance programme in Pakistan, this study tests for the existence of information asymmetry (adverse selection and moral hazard) using a series of non-parametric tests so that insurers and policymakers can better understand the underlying reasons that lead to dynamic claim patterns before taking appropriate actions to improve the sustainability of these programmes. The study’s contribution lies in constructing an appropriate method and novel test statistics to detect information asymmetry using dynamic claim data in a multivariate recurrent event model framework. The results show that adverse selection exists widely for a variety of disease types and that moral hazard is only significant for chronic diseases. Furthermore, pregnancy-related claims demonstrate an increasing trend of adverse selection that needs to be addressed with priority. The analysis provides insight into the sustainable provision of micro health insurance to low-income people in developing regions.

小额医疗保险是为低收入人群筹集医疗支出的重要渠道，但由于许多计划变得不可持续，此类计划的供应落后于需求。本研究使用来自巴基斯坦的微健康保险计划的个人水平动态数据，使用一系列非参数测试来测试信息不对称（逆向选择和道德风险）的存在，以便保险公司和政策制定者可以更好地理解其根本原因。在采取适当行动改善这些计划的可持续性之前，会导致动态的索赔模式。该研究的贡献在于构建了一种合适的方法和新颖的测试统计数据，以在多变量复发事件模型框架中使用动态声明数据来检测信息不对称性。结果表明，逆向选择广泛存在于多种疾病类型中，道德风险仅对慢性疾病具有重要意义。此外，与怀孕有关的主张显示出逆向选择的趋势在增加，需要优先解决。该分析提供了对向发展中地区的低收入人群可持续提供小额医疗保险的见解。