Health insurance, endogeneity and financial risk protection: Evidence from India's National Sample Survey

Health-related uncertainties and the risk of impoverishment from medical expenses are intensified without health insurance, especially in developing countries like India. Using data from the 75th round of the National Sample Survey (NSS), this study examines how health insurance mitigates the catastrophic burden of illness (CBI) among hospitalized individuals. An Endogenous Switching Regression (ESR) model estimated through Full Information Maximum Likelihood (FIML) addresses endogeneity and selection bias. Results show that urban, educated, economically better-off, and formally employed individuals are more likely to be insured, while uninsured groups are largely rural, disadvantaged, and less educated, facing a higher CBI. Treatment effect analysis reveals that uninsured individuals would experience a substantial decline in CBI if insured, while insured individuals would face a pronounced financial burden without coverage. The findings underscore the need for policy measures that extend insurance to the uninsured, strengthen the public healthcare system, and ensure equitable financial protection.