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Estimating Willingness to Pay

Actual community-based health insurance (CBHI) premium payments often fall short of Willingness-to-Pay (WTP) estimates. This study examines the gap between the estimated premiums and actual payments for CBHI by analyzing data from 3,685 households in rural India. Descriptive statistics are used to analyze the gap between the estimated premium and actual payments. Heckman two-stage sample-selection model is applied to analyze the predictors of actual payment, subject to household enrolment in CBHI. The estimated premiums were 0.50–1.26% of per-capita gross domestic product (PCGDP). The actual payments were ~50% of the estimates. The gap resulted as households enrolled fewer family members than expected. Further analysis indicates that a quadratic function (to estimate expected enrollees from the household) combining with a fixed premium (expressed as a percentage of PCGDP) can better predict actual income. Heckman analysis indicates that focusing on greater awareness and financial literacy can lead to an increase in actual payments.