Estimating Willingness-to-Pay for Health Insurance Among Rural Poor in India By Reference to Engel's Law

Abstract

Community-Based Health Insurance (CBHI) (a.k.a. micro health insurance) is a contributory health insurance among rural poor in developing countries. As CBHI schemes typically function with no subsidy income, the schemes’ expenditures cannot exceed their premium income. A good estimate of Willingness-To-Pay (WTP) among the target population affiliating on a voluntary basis is therefore essential for package design. Previous estimates of WTP reported materially and significantly different WTP levels across locations (even within one state), making it necessity to base estimates on household surveys. This is time-consuming and expensive. This study seeks to identify a coherent anchor for local estimation of WTP without having to rely on household surveys in each CBHI implementation. Using data collected in 2008e2010 among rural poor households in six locations in India (total 7874 households), we found that in all locations WTP expressed as percentage of income decreases with household income. This reminds of Engel’s law on food expenditures. We checked several possible anchors: overall income, discretionary income and food expenditures. We compared WTP expressed as percentage of these anchors, by calculating the Coefficient of Variation (for inter-community variation) and Concentration indices (for intra-community variation). The Coefficient of variation was 0.36, 0.43 and 0.50 for WTP as percent of food expenditures, overall income and discretionary income, respectively. In all locations the concentration index for WTP as percentage of food expenditures was the lowest. Thus, food expenditures had the most consistent relationship with WTP within each location and across the six locations. These findings indicate that like food, health insurance is considered a necessity good even by people with very low income and no prior experience with health insurance. We conclude that the level of WTP could be estimated based on each community’s food expenditures, and that this information can be obtained everywhere without having to conduct household surveys.