| Summary: | Access to health care is a serious problem in Sierra Leone, more so in rural areas where living standards are low and there is absence of health care facilities. Health insurance, it is argued, will play an important role in giving access to medical care and reducing the high out of pocket (OOP) health expenditure, thus preventing unnecessary deaths and increasing well-being. It is however difficult to know the exact value households place on health and health care as they are not generally exchanged in the market place. For this reason, nonmarket valuation is increasingly becoming an important tool for informing policy makers. The Contingent Valuation and Discrete Choice Experiment (DCE) are the most widely used methods. However, due to its increased popularity, the ability to calculate incremental benefit of each attribute used, and it proving to be more appealing, this work therefore used the DCE method to collect data. This study provides the following: first, a review of the application of DCE to health outcomes including health insurance for the period 1990 – 2013; second it estimates the willingness to pay (WTP) for health insurance; third, it estimates the impact of corruption on participation in health insurance; and finally, it looks at ability to pay (ATP) for health insurance among informal sector workers in Sierra Leone using a DCE method. The four essays/papers (Chapters 2 – 5) represent the main outcomes of this research. Eight informal sector activities were selected namely – petty trading, subsistence farming, commercial bike riding (“okada”), cattle rearing, fishing, tailoring, alluvial mining and quarrying. More precisely, the first empirical paper used a random effect logit model to estimate households’ WTP for health insurance for an improvement in coverage, choice of provider and a reduction in waiting time. The second empirical paper on the impact of corruption introduces two definitions of corruption – perceived and actual (free health care). The study used the mixed logit (MXL) model to estimate the impact of corruption on households’ participation in health insurance. The final empirical paper on the other hand looked at ability to pay for health insurance. This paper is built on the assumption that simply perceiving need for health insurance is insufficient for someone to participate in it. Participation in health insurance is backed by the financial ability of the household to pay for health insurance. This study used two approaches: a univariate probit (naive) model and a recursive bivariate probit method (RBPM). We use data from discrete choice experiment to estimate ability to pay for health insurance. Conditional on a set of covariates, the findings of the thesis suggest the following: first, that households are willing to pay for health insurance for an improvement in coverage, choice of provider (public and non-public) and a reduction in waiting time; second, that corruption generates substantial additional cost to households, hence the higher WTP to participate in schemes with evidence of corruption, more so, actual (free health care) corruption; and finally, that households do not have the financial capacity to pay for health insurance. Our result also shows that households that perceived NEED do not only have the ability to pay for it but are also not likely to participate in the scheme.
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