Inequality in willingness-to-pay for community-based health insurance

Health Policy. 2005 May;72(2):149-56. doi: 10.1016/j.healthpol.2004.02.014.


The purpose was to provide information for devising community-based health insurance (CBI) policies that reduce inequality in enrolment and further inequality in access to health services. A two-stage cluster sampling was used in the household survey. Inequalities in willingness-to-pay (WTP) for CBI are examined by expenditure quintile using data collected from a household survey. Interviews were conducted with 2414 individuals, 705 of whom were household heads. A bidding game method was used to elicit WTP. Individuals and households were assigned to 6-month expenditure quintiles. We found that mean and median individual WTP for CBI was significantly higher for higher spending quintiles, as was mean and median household WTP. The curves of cumulative percentage of individual and household WTP shifted rightwards for higher quintiles, implying that at any given premium the lower the quintile the lower the uptake of CBI. The Gini coefficient for individual WTP and household WTP was 0.15 and 0.08, respectively, and for individual 6-month expenditure and household 6-month expenditure is 0.68 and 0.63, respectively. The results imply that the premium needs to be adjusted for income; otherwise, a lower proportion of poor people will enrol in CBI and without exemptions or subsidies the poor will have less access to health services than the rich. Thus, exemptions and subsidies for the poor for enrolling in CBI are an important issue for decision-makers with an objective of improving equity of health and helping the poor to break out of the cycle of poverty. Since the distribution of WTP by household is less unequal than the distribution of WTP by individuals, the household might be a better unit of enrolment in terms of equity than the individual.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Data Collection
  • Female
  • Financing, Personal / statistics & numerical data*
  • Humans
  • Insurance, Health / economics*
  • Male
  • Middle Aged
  • Social Class
  • United Kingdom