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Government-Sponsored Health Insurance in India
to commercial facilities such as a bank, immunization rates for diptheria, pertussis, and tetanus (DPT3) as a proxy for primary care, and enrolment by a private insurance company. The latter result is puzzling and could reflect the different incentive environment for government-owned vis-à -vis privately owned commercial insurers. Even though both types of commercial insurers (government-owned or privately owned) are for-profit firms and in principle face the same incentives, does the former’s proximity to government and possible lack of incentives to maximize enrolment result in public insurers’ making less of an effort to enroll beneficiaries? Or is it that the bottom-line impact of earning higher premiums (which are based on enrolment) and ensuring a larger risk pool is more important to privately owned insurers than to their public counterparts? Do internal incentives for field enrolment agents differ among these types of firms? If so, how is this manifested? Further research is needed to understand the incentive environment of public and private insurers. Interestingly, Sun found that about a quarter of the difference between eligible and enrolled populations was related to the reduced number of enrolled family members. More than one third of families with five or more members enrolled fewer than five, which is the RSBY family limit. Enrolment decreased as family size increased. One would expect that large families would enroll the maximum number of five members. Why is this not the case? Three explanations come to mind. First, during the day of enrolment, not all members were present. The second relates to the outdated BPL lists, which may not account for family members no longer living in the household (due to marriage, death and change of residence). Another explanation may involve incentives facing enrolment agencies. Since a flat fee is paid per family irrespective of the number of members enrolled, agencies have little incentive to incur the extra time and cost to enroll the maximum number of family members.
Targeting and Equity Considerations The effectiveness of targeting in the enrolment process depends on the quality of BPL listings. Unfortunately, the BPL scoring and classification system in India is notorious for false positives (leakage) and for false negatives (undercoverage). Jalan and Murgai (2007) compared BPL classification with consumption patterns drawn from the household Consumer Expenditure Schedule of the NSS. They found that BPL scores misclassified 49 percent of the non-poor as poor. The misclassification of non-poor