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Title: Modeling demand for community-based health insurance : an analytical framework and evidence from India and Nigeria
Author: Velenyi, Edit V.
ISNI:       0000 0004 2716 5710
Awarding Body: University of York
Current Institution: University of York
Date of Award: 2011
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The thesis offers three primary contributions to the evidence base on demand for community-based health insurance (CB HI): (i) a review of the literature; (ii) an extended analytical framework to guide empirical investigations of demand for CBHI; and (iii) applied analyses to test the hypothesis regarding the relevance and fit of the proposed extension, and explore central positive and normative questions related to demand for CBHI by low-income groups in India and Nigeria. Chapter 2 offers an appraisal of the empirical and theoretical literature on demand for CBHI. Consequently, it proposes an extended analytical framework, which includes vectors of covariates at the household, CBHI, community, and state levels. More importantly, it proposes to test the relevance of social capital in models for demand estimation of CBHI. This extension places the central thrust of the thesis at the intersection of insurance theory and development economics. Chapter 3 exploits cross-sectional household data to apply the proposed extended framework to draw inferences on the nature of demand for micro insurance in India. Results from discrete choice and linear models show that the additional vectors have an impact on choice. While our social capital measures are not robust, the model statistics suggest that the community vector plays a role in demand. Chapter 4 explores demand to understand the market potential of a pilot in Lagos. The analysis draws on household and provider data. The results are more robust in terms of the number of significant covariates and their economic effects than those found in India. As a result, there is stronger and more decomposed evidence on the importance of the extended sets of covariates. Heckman, bivariate and multivariate models show significant effects for the CBHI and community vectors that have larger marginal effects than those observed in the household vector. The investigation offers a methodological insight into the double bounded dichotomous choice contingent valuation method. The evidence from these empirical analyses corroborates the relevance of the extended framework. We found that using the individual and household-level vector alone to estimate demand for CBHI is detached from reality and leads to model misspecification. Although the analyses are hampered by data limitations, the economic effects of the additional vectors are substantial. Understanding the role of social capital could improve the impact of community-based interventions. While there is evidence of interest in insurance even among the poor, the economic size of contributions from low-income groups in absolute terms is limited. However, their individual and household efforts are not negligible, as the stated reservation prices constitute a significant share of their household consumption. These facts imply that, while low-income households value insurance and coverage is demanded, their financial constraints may constitute a price barrier if the premiums are not subsidized. The thesis identifies critical gaps for future investigation: (i) combining analytical approaches (ii) improving measurement of factors; (iii) expanding the geographic scope of research on CB HI, especially in countries where community-based resource mobilization is a policy priority, in order to improve the external validity of findings and, consequently the value of information for design and policy making.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available