Demand for healthcare services in Nigeria: a multivariate nested logit model

The object of this paper is to explain the healthcare decision process and the factors that influence medicare demand decisions of Nigerian households during a period of economic depression. It is based on a sample from a small-area analysis focusing on a relatively homogenous group. The objective of the study involved the estimation of the parameters of the demand for healthcare services in order to understand the nature of healthcare choices and the pathways to those choices that Nigerian households make under dire economic circumstances. These demand parameter estimates are considered valuable inputs into healthcare policy. Yet, to date, there is no sufficient information on the vital factors that shape households' utilization of medicare services nor is there sufficient information on the relative importance of healthcare alternatives available to them. This is the knowledge gap that this study hopes to fill. The nested logit model was found to be an appropriate functional form for the analysis

A distributional analysis of out-of-pocket healthcare financing in Nigeria using a new decomposable Gini index

This study applies a new method of decomposing total redistributive effect of taxation proposed by Duclos et al. (2003) to assess the redistributive effects of direct healthcare financing in Nigeria. This new framework makes it possible not only to introduce into the conventional Gini Index estimation framework a flexible ethical measure of aversion to inequality but also a novel concepts of horizontal inequity and re-ranking. The empirical results indicate that when the decision to utilize healthcare is always linked to the decision to pay for healthcare, as is the case in Nigeria, out-of-pocket payment, contrary to existing literature, may indeed be progressive with high levels of horizontal inequity and re-ranking effect. But the progressivity may underlie the lack of ability to pay by poorer households. All the components of the redistributive effect are also likely to vary with the level of the social aversion to inequit

Simple sequential procedure for modeling of item non-response in econometric analysis: Application to CV survey data

Item non-response occurs when respondents fail to provide answers to some or all of the questions posed during survey interviews. The standard procedure is to exclude such responses from the econometric analysis. This may be appropriate if the sample included does not differ significantly from those excluded in the analysis. If this is not the case, the econometric analyst faces a sample selection bias problem. The aim of this paper is to provide further evidence using a simple sequential procedure to deal with the problem when using non-randomly selected samples in social science research. The procedure entails different levels of estimation and diagnostic with the Ordinary Least Squares (OLS), Heckman's 2-step and Full Information Maximum Likelihood (FIML) estimators. In the application context, we found the FIML estimator to be more efficient in dealing with sample selection bias than the Heckman's 2-step approach

Socioeconomic gradients in self-rated health: a developing country case study of Enugu State, Nigeria

Health inequalities, Self-rated health (SRH), Health status index (HSI), Convergence, Concentration index, Extended concentration index, C13, D63, I11,

The Effect of Protest Zeros on Estimates of Willingness to Pay in Healthcare Contingent Valuation Analysis

'Protest zeros' occur when respondents reject some aspect of the contingent valuation (CV) market scenario by reporting a zero value even though they place a positive value on the amenity being valued. This is inevitable even in the best-designed CV study, and, when excluded on an ad hoc basis, may cause a selection bias problem. This could affect the reliability of the willingness to pay (WTP) estimates obtained for preference assessment. Treatment of 'protest zeros' in general, and particularly in the context of developing countries, has been rather unsatisfactory. Most case studies employ the Heckman 2-step approach, which is much less robust to co-linearity problems than the Full Information Maximum Likelihood (FIML) estimator. The main objective of this article is to illustrate a sequential procedure to simultaneously deal with co-linearity and selectivity bias resulting from excluding 'protest zeros' in CV analysis. The sequential procedure involves different levels of estimation and diagnostics with the 2-step and FIML estimators; the duration of the procedure depends on the diagnostic test results at each stage of the estimations. The data used for the analysis were elicited using the conventional dichotomous choice buttressed with an open-ended follow-up question. The survey was designed to elicit households' WTP for a proposed community-based malaria control scheme in rural Cameroon. In the application context, we found that the different levels of estimation and diagnostics resulted in reliable WTP estimates from the FIML approach, which would obviously have been overlooked in the absence of such diagnostics.Contingent-valuation, Malaria, prevention, Willingness-to-pay.

Simple Sequential Procedure for Modeling of Item Non-Response in Econometric Analysis: Application to CV Survey Data

Item non-response occurs when respondents fail to provide answers to some or all of the questions posed during survey interviews. The standard procedure is to exclude such responses from the econometric analysis. This may be appropriate if the sample included does not differ significantly from those excluded in the analysis. If this is not the case, the econometric analyst faces a sample selection bias problem. The aim of this paper is to provide further evidence using a simple sequential procedure to deal with the problem when using non-randomly selected samples in social science research. The procedure entails different levels of estimation and diagnostic with the Ordinary Least Squares (OLS), Heckman’s 2-step and Full Information Maximum Likelihood (FIML) estimators. In the application context, we found the FIML estimator to be more efficient in dealing with sample selection bias than the Heckman’s 2-step approach

Paying for community-based health insurance schemes in rural Nigeria: the use of in-king payments

Financing healthcare for the poor is one major challenge facing the world’s poorest populations in developing countries. While over 90% of the global burden of disease is borne by over 80%, only about 11% of global health spending is on the poor. Community-based health insurance schemes (CBHIS) have emerged in Africa for mobilizing community resources. They can also be a stepping stone to a more formal and potentially universal coverage. In parts of Africa where such schemes exist, they have not effectively covered the target population. Nigeria has a few such schemes. This paper uses the contingent valuation to examine the possibility of adopting CBHIS using in-kind payments in rural Nigeria. The study finds that gender, household size, health status, the quality of health care centers, confidence in the proposed scheme, distance to the nearest health care center and income are major determinants of households’ willingness to pay (WTP) for the scheme.Soins de santé de financement pour les pauvres est un défi majeur auquel sont confrontées populations les plus pauvres de la planète dans les pays en développement. Alors que plus de 90% de la charge mondiale de morbidité est supportée par plus de 80%, seulement environ 11% des dépenses de santé mondiale est sur les pauvres. Communauté des régimes d’assurance santé (CBHIS) ont émergé en Afrique pour mobiliser les ressources communautaires. Ils peuvent aussi être un tremplin vers une couverture plus formelle et potentiellement universelle. Dans certaines régions d’Afrique où de tels régimes existent, ils n’ont pas effectivement couvert la population cible. Le Nigeria a quelques programmes tels. Ce document utilise l’évaluation contingente d’examiner la possibilité d’adopter CBHIS utilisant des paiements en nature dans les régions rurales du Nigeria. L’étude constate que le sexe, la taille du ménage, l’état de santé, la qualité des centres de soins de santé, la confiance dans le système proposé, la distance du centre de soins de santé le plus proche et le revenu sont des déterminants majeurs de la volonté des ménages à payer (CAP) pour le régime

Using a Contingent Valuation Approach for Improved Solid Waste Management Facility: Evidence from Enugu State, Nigeria

For most public projects, especially environmental projects that are partly funded by multilateral donor agencies, cost--benefit analysis has become a routine procedure for the approval of project funds. These agencies are very keen to know whether the target community or country possesses the aggregate willingness to pay for the project. The two most commonly applied techniques for such analysis are stated preference and behavioural techniques. In this study, we employ the contingent valuation method (CVM), the most widely applicable of the stated preference methods, to establish empirical grounds for pricing the services of a new solid waste management (SWM) improvement facility in Enugu State, Nigeria, initiated by the UK Department for International Development, the State's Environmental Protection Agency, and State and Local Government Programme. We find that CVM can be fruitfully used to support the design and implementation of new SWM facilities and that analysis of the valuation function can give qualitative information that is difficult to identify using baseline surveys or most conventional economic valuation techniques. Copyright 2008 The author 2007. Published by Oxford University Press on behalf of the Centre for the Study of African Economies. All rights reserved. For permissions, please email: [email protected], Oxford University Press.