David M Dror - Profile on Academia.edu (original) (raw)

Papers by David M Dror

Substitutes to Baseline Surveys

World Scientific series in health investment and financing, Feb 1, 2020

This chapter seeks to propose an efficient alternative to household surveys (HHSs) for obtaining ... more This chapter seeks to propose an efficient alternative to household surveys (HHSs) for obtaining data needed to launch a community-based health insurance scheme. We discuss the three essential pieces of information that are used for the design of the benefits package and its pricing. These are morbidity and utilization patterns, the average cost of care locally, and the distribution of that cost. The methods available to source these data without conducting a full HHS are elaborated.

Baseline Study and Its Purpose

World Scientific series in health investment and financing, Feb 1, 2020

Understanding the local needs of a community lays the foundation for the launch of a microinsuran... more Understanding the local needs of a community lays the foundation for the launch of a microinsurance scheme. The baseline study must precede the operational processes of presenting different options of benefits packages to the community. This chapter discusses the relevance of a baseline study, its objectives, and the stages involved in planning and conducting the study.

The Governance Structure and Training the Key Actors

World Scientific Series in Health Investment and Financing, 2020

The governance structure of community-based health insurance (CBHI) comprises members of the comm... more The governance structure of community-based health insurance (CBHI) comprises members of the community who are also the owners of the scheme. The model is driven by the principle of subsidiarity which posits that every social or economic issue should be dealt with at the most immediate (or lowest) level that can resolve it while respecting camaraderie and human dignity. We learn about the roles and responsibilities of each key actor and their contribution in the various business processes of the scheme.

IntechOpen eBooks, Nov 25, 2023

This chapter offers a detailed analysis of microinsurance (nowadays often called "inclusive insur... more This chapter offers a detailed analysis of microinsurance (nowadays often called "inclusive insurance"), an innovative hybrid model combining grassroots initiatives with top-down approaches to reach populations not covered by government-operated social protection systems. With half of the global population, primarily in low and middle-income countries, lacking social protection, the chapter focuses on the potential of microinsurance to address this pressing issue. The commercial microinsurance attempts, often labeled as "insurance for the poor," have been largely insufficient. An alternative lies in the "Collaborative and Contributive" (C&C) model of microinsurance, which harnesses social forces, typically more compelling than market forces in informal settings, to stimulate demand. The chapter evaluates microinsurance's social and economic impacts, drawing insights from 25 years of progress. It underscores the need for policymakers, international development bankers, and the reinsurance industry to recognize the potential of the C and C model in providing comprehensive insurance to marginalized populations.

Social Science Research Network, Sep 27, 2007

Most industrialized countries have financed health services through health insurance. Two systems... more Most industrialized countries have financed health services through health insurance. Two systems prevail: private, or public (social) health insurance. The theoretical differences between them are reviewed. It is argued that most health systems are, however, hybrids and that health insurance reform in Europe and the United States has accentuated this trend because the principles distinguishing the two systems have often been ignored. This is illustrated through the evolution of voluntary vs. compulsory affiliation, coping with moral hazard, and provider regulation. H ealth insurance has become the foremost form of financing access to curative health services in most countries. Two approaches have been most prevalent: social health insurance (SHI), and private health insurance (PHI). These differ in their basic assumptions: SHI is guided by the notion that health is a basic human right and insurance a tool to advance its implementation. PHI views health as a cluster of risks, insurance of which is a profitable economic activity. Are these two approaches contradictory or complementary? Can they be reconciled into a coherent logic? Have their philosophical and ethical differences been made to accord or, on the contrary, accented, in the process of health insurance reform? Health insurance reforms have emphasized economic issues. Both SHI and PHI have seemingly faced the same problems: rising cost of curative care and rapid development of health technology, linked to the importance of biomedical centres of excellence and increasing health expectations of the public. At the same time, insurers had to deal with financing problems,

Willingness to Pay for Health Insurance

World Scientific series in health investment and financing, Dec 1, 2018

Following are the consolidated main messages from Chapters 5.1–5.3:Estimating Willingness to Pay ... more Following are the consolidated main messages from Chapters 5.1–5.3:Estimating Willingness to Pay (WTP) for health insurance (HI) coverage is the only way to estimate the expected income of voluntary and contributory HI schemes. This estimate is needed to ensure that the cost of benefits packages remain within available resources, so as to minimize the risk of bankruptcy.Data on WTP are necessary to inform the design of customized HI benefits packages by consumers, notably by groups or communities.One approach to estimate individual WTP is the Revealed Preferences method (RP), introduced first by Samuelson, which involves studying actual purchasing behavior of products which are related to the product we are interested in. The assumption is that revealed preferences can identify the value people place on a product for which purchasing information does not exist.Another approach to estimate WTP is the Stated Preferences method (SP), which involves asking people what they would be willing to pay for insurance coverage that they do not yet have, and that may not be available in the market. SP has been refined into several techniques, and the one used most often to value non-market goods is called Contingent Valuation (CV). It consists of asking respondents the maximum amount they would be willing to pay for an intervention under evaluation (e.g. insurance).Most of the rural population in low-income countries is not familiar with the concept of insurance. Hence, it is challenged to reveal the price they are willing to pay for (insurance coverage) a product they have never before been offered or purchased.Field evidence of experiments with choice of package and price by groups of rural poor people in India points that they tend to converge toward consensus on the components of the benefit package and the price per person per year (PPPY), namely on the generally accepted declared WTP.It must be recognized that the actual level of their WTP could differ from the declared level. A first estimate of the gap between declared and actual WTP in community-based health insurance (CBHI) has been obtained from the evidence that households modulate WTP levels not by negotiating a different price, but by limiting the number of household members enrolled (at the agreed price PPPY) to reduce the total cost per household for HI. Initial evidence suggests that households enrolled only half their members in the first and second year. Longitudinal studies could verify whether the gap between the declared and actual WTP would diminish over time.Dror and Koren (2012) conducted a review of 14 experimental field studies eliciting WTP for health insurance among low-income persons in developing countries. They observed that the large methodological diversity reported in these studies made it impossible to identify a single “gold standard” method to elicit and estimate WTP.However, there was implied consensus that WTP must be explored locally, because there is no single “one-size-fits-all” option to determine the income side of different HMI schemes operating in different settings. Thus, estimates of WTP were based on household surveys. Collecting data with such surveys is both time-consuming and expensive.Several studies explored faster and cheaper methods to estimate WTP than surveys.Binnendijk et al. (2013) examined whether the relation between WTP for HI and income might be similar to Engel’s Law, an observation in economics stating that the proportion of income spent on food decreases as income increases, even if actual expenditure on food rises. These authors used data from six locations in India to check WTP expressed as a percentage of three anchors: overall income, discretionary income, and food expenditures, by calculating the Coefficient of Variation (for inter-community variation) and Concentration indices (for intra-community variation). They found that food expenditures had the most consistent relationship with WTP within each location, and across the six locations. This suggests that, just like food, HI is considered a necessity good even for people with very low income and no prior experience with health insurance. Thus, it is possible to estimate the WTP level based on each community’s food expenditures.On an average, WTP for CBHI was around 4.5% of food expenditures in the studied locations. Food expenditure information can be obtained through cheap and fast research methods, such as focus group discussions with target communities or from data published routinely and in the public domain.Nosratnejad et al. (2016) estimated WTP for HI on the basis of readily available data pertaining to GDP per capita, by using vote counting to identify factors which were consistently correlated with higher WTP for insurance: family size, education level, income, past hospitalization, and perceived poor health status. Their meta-analysis revealed that the WTP for HI among rural households in low and middle-income countries (LMICs) was…

Financing Micro Health Insurance: Theory, Methods and Evidence

Healthcare for all at affordable prices is still a major but universally elusive goal. Everyone s... more Healthcare for all at affordable prices is still a major but universally elusive goal. Everyone spends money on healthcare, and it is the most impoverishing consumption item. Thus, most governments (and the United Nations) promote Universal Health Coverage — each country's unique blend of tools for healthcare financing, including taxes, subsidies and market controls.

Social Science Research Network, 2014

Data in Microinsurance

World Scientific Series in Health Investment and Financing, 2020

This chapter aims to introduce the relevance of data in establishing a microinsurance scheme. The... more This chapter aims to introduce the relevance of data in establishing a microinsurance scheme. The success of a scheme rests in large part on the affordability of the benefits package (premium) and the relevance of the benefits it provides to the members. There are several combinations for such a solution, and identifying them requires using local, context-specific, and reliable data. Here we study the significance of data in microinsurance, the various types of data available, their sources, and methods to present the findings of the data analysis.

Estimating Willingness to Pay

Actual community-based health insurance (CBHI) premium payments often fall short of Willingness-t... more Actual community-based health insurance (CBHI) premium payments often fall short of Willingness-to-Pay (WTP) estimates. This study examines the gap between the estimated premiums and actual payments for CBHI by analyzing data from 3,685 households in rural India. Descriptive statistics are used to analyze the gap between the estimated premium and actual payments. Heckman two-stage sample-selection model is applied to analyze the predictors of actual payment, subject to household enrolment in CBHI. The estimated premiums were 0.50–1.26% of per-capita gross domestic product (PCGDP). The actual payments were ~50% of the estimates. The gap resulted as households enrolled fewer family members than expected. Further analysis indicates that a quadratic function (to estimate expected enrollees from the household) combining with a fixed premium (expressed as a percentage of PCGDP) can better predict actual income. Heckman analysis indicates that focusing on greater awareness and financial li...

Pricing of Microinsurance or Rate Making

In commercial insurance, it is common practice to charge each individual the premium that reflect... more In commercial insurance, it is common practice to charge each individual the premium that reflects that person’s estimated contribution to the risk pool. However, in microinsurance, community rating is applied, whereby every participant pays the same premium, irrespective of age, gender, health status, or claims history. This methodology is challenging in terms of pricing the package and maintaining an equilibrium between high-risk and low-risk individuals. The reality in microinsurance practice is that the price determines the package, rather than the other way around. This chapter provides a detailed guideline on context-dependent pricing.

Why and how to apply re-assurance to community health schemes in low-income countries?: urquoi et comment appliquer la ré-assurance aux systèmes de santé communautaires dans les pays à faible revenu?

Dans les pays a faible revenu, la plupart des personnes appartenant au secteur informel se trouve... more Dans les pays a faible revenu, la plupart des personnes appartenant au secteur informel se trouvent totalement depourvues de couvertures medicales, en raison du financement insuffisant de services sante. Le role des communautes qui ont institue un partage des risques, decrites comme des groupes de micro-assurances, a ete reconnu, et le nombre de ces initiatives est en croissance. Toutefois, les unites de micro-assurance sont rarement structurees comme une veritable assurance-maladie. Les causes de leur instabilite financiere et les solutions qui s'offrent sont expliquees dans la dissertation, basees sur des donnees factuelles, notamment l'Ouganda et les Philippines, ainsi que des simulations de situations, pour examiner les arguments avances et les solutions proposees. Cette dissertation porte sur l'adaptation de techniques de gestion du risque aux systemes communautaires ; plus particulierement, l'accent est mis sur le transfert de risque de groupe de micro-assurance a des systemes de reassurance. Un modele de reassurance a ete elabore, base sur deux hypotheses : (i) que la reassurance couvre des risques "assurable" au-dela d'un seuil, contre le paiement d'une prime ; (ii) que les unites de micro-assurance soient responsables des paiements des risques jusqu'a ce seuil (plus prime de reassurance). Un algorithme est propose pour distinguer les prestations assurables de ceux qui sont non assurables. Le principal enseignement de cette etude est que, lorsque les resultats financiers des groupes de micro-assurance peuvent etre estimes, ils peuvent faire l'objet de traites de reassurance ce qui permet de les stabiliser des la premiere annee. Le deuxieme enseignement est qu'il faut parfois que le pool de reassurance fonctionne pendant plusieurs annees avant que l'on puisse parvenir a equilibrer les recettes et les couts. Le troisieme enseignement est que la taille de groupe de reassures peut raccourcir cette periode, ainsi que reduire le cout de prime du reassureur.

The Geneva Papers on Risk and Insurance - Issues and Practice, 2021

In considering the focus of the special issues on this theme, the Editor-in-Chief and the Editori... more In considering the focus of the special issues on this theme, the Editor-in-Chief and the Editorial Board allowed the Guest Editor(s) freedom of choice. They gracefully refrained from taking a position on whether microinsurance required a separate theoretical framing or whether it should be analysed using classical models (thus suggesting that this is another type of insurance). It is helpful to recall that the term microinsurance was first used in an article published in 1999 (Dror and Jacquier 1999). It is also useful to remind that most of the printed material (this issue included) offers empirical analysis. We scoped the volume of publications on this topic in Google Scholar since 2000 (see Fig. 1). The first decade saw a tenfold increase in the number of publications per year, from about 100 to close to 1000. After that, we witness a continued but lesser growth (the highest number of microinsurance publications per year, 2300, was recorded in 2014). The ResearchGate weekly reports of browses-downloads-citations also suggest an ever-increasing and widespread use of published material. The Web of Science count of microinsurance publications shows two peaks, in 2016 and 2019. These were the years when this journal published special issues on microinsurance. This suggests how significant the contribution of the special issues was to scientific (peer-reviewed) publications on this topic. The more comprehensive treatises on microinsurance were published as books. Also, we recall region-specific scoping studies that have been the source of statistics on enrollments. Over this time, most authors have moved on from the initial preoccupation with definitions. We have one article summarising the developments in this

World Scientific series in health investment and financing, Dec 1, 2018

The Institute of Social Studies is Europe's longest-established centre of higher education and re... more The Institute of Social Studies is Europe's longest-established centre of higher education and research in development studies. On 1 July 2009, it became a University Institute of the Erasmus University Rotterdam (EUR). Postgraduate teaching programmes range from six-week diploma courses to the PhD programme. Research at ISS is fundamental in the sense of laying a scientific basis for the formulation of appropriate development policies. The academic work of ISS is disseminated in the form of books, journal articles, teaching texts, monographs and working papers. The Working Paper series provides a forum for work in progress which seeks to elicit comments and generate discussion. The series includes academic research by staff, PhD participants and visiting fellows, and award-winning research papers by graduate students.

Development of a new cost- & time effective methodology to upscale demand for health insurance among the poor in India

Microinsurance: Innovations in Low-Cost Health Insurance

World Scientific series in health investment and financing, Dec 1, 2018

Microinsurance--low-cost health insurance based on a community, cooperative, or mutual and self-h... more Microinsurance--low-cost health insurance based on a community, cooperative, or mutual and self-help arrangements-can provide financial protection for poor households and improve access to health care. However, low benefit caps and a low share of premiums paid as benefits--both designed to keep these arrangements in business--perversely limited these schemes' ability to extend coverage, offer financial protection, and retain members. We studied three schemes in India, two of which are member-operated and one a commercial scheme, using household surveys of insured and uninsured households and interviews with managers. All three enrolled poor households and raised their use of hospital services, as intended. Financial exposure was greatest, and protection was least, in the commercial scheme, which imposed the lowest caps on benefits and where income was the lowest.

Community-Based Health Insurance (CBHI) (a.k.a. micro health insurance) is a contributory health ... more Community-Based Health Insurance (CBHI) (a.k.a. micro health insurance) is a contributory health insurance among rural poor in developing countries. As CBHI schemes typically function with no subsidy income, the schemes' expenditures cannot exceed their premium income. A good estimate of Willingness-To-Pay (WTP) among the target population affiliating on a voluntary basis is therefore essential for package design. Previous estimates of WTP reported materially and significantly different WTP levels across locations (even within one state), making it necessity to base estimates on household surveys. This is time-consuming and expensive. This study seeks to identify a coherent anchor for local estimation of WTP without having to rely on household surveys in each CBHI implementation. Using data collected in 2008e2010 among rural poor households in six locations in India (total 7874 households), we found that in all locations WTP expressed as percentage of income decreases with household income. This reminds of Engel's law on food expenditures. We checked several possible anchors: overall income, discretionary income and food expenditures. We compared WTP expressed as percentage of these anchors, by calculating the Coefficient of Variation (for inter-community variation) and Concentration indices (for intra-community variation). The Coefficient of variation was 0.36, 0.43 and 0.50 for WTP as percent of food expenditures, overall income and discretionary income, respectively. In all locations the concentration index for WTP as percentage of food expenditures was the lowest. Thus, food expenditures had the most consistent relationship with WTP within each location and across the six locations. These findings indicate that like food, health insurance is considered a necessity good even by people with very low income and no prior experience with health insurance. We conclude that the level of WTP could be estimated based on each community's food expenditures, and that this information can be obtained everywhere without having to conduct household surveys.

Incidence of illness among resource-poor households: evidence from five locations in India

PubMed, Aug 1, 2009

Background & objective: This study examines the association between household attributes and perc... more Background & objective: This study examines the association between household attributes and perceived morbidity within resource-poor house holds (HHs) in India at five locations. This presents an innovation compared to most epidemiological studies, which focus on associations between the incidence of an illness and characteristics of the ill person. Methods: Perceived morbidity was represented by a variable called "Incidence of illness in a HH" (IIH) = the number of self reported illness episodes during three months preceding the survey, divided by household size. Variables were analyzed through bivariate correlation and multivariate linear regression. The evidence was based on a HH survey conducted in 2005 in Maharashtra, Bihar, and Tamil Nadu. Data yield reflected responses of 3,531 HHs, representing 17,323 individuals and 4,316 illness episodes. Results: Analysis showed that incidence of illness among women was higher; the under 5 yr olds and elderly (+55) were particularly vulnerable. However, in the multivariate linear regression model, gender ratio within HHs became an insignificant explanatory variable. Age distribution had a small but significant effect. Household size and the level of education in the HH were negatively and significantly associated with IIH. The regression analysis showed that income had a modest positive effect, but improved housing was associated with reduced IIH. Large differences were noted in IIH across locations. Interpretation & conclusion: Our findings showed that attributes of the unit household, including type of house, income, education and size, have significant effects on IIH; variability in IIH cannot solely be explained by age and gender of HH members.

Health policy, Jun 1, 2007

This study, conducted in India in 2005, provides evidence on Willingness to pay (WTP), gathered t... more This study, conducted in India in 2005, provides evidence on Willingness to pay (WTP), gathered through a unidirectional (descending) bidding game among 3024 households (HH) in seven locations where micro health insurance units are in operation. Insured persons reported slightly higher WTP values than uninsured. About two-thirds of the sample agreed to pay at least 1%; about half the sample was willing to pay at least 1.35%; 30% was willing to pay about 2.0% of annual HH income as health insurance premium. Nominal WTP correlates positively with income but relative WTP (expressed as percent of HH income) correlates negatively. The correlation between WTP and education is secondary to that of WTP with HH income. Household composition did not affect WTP. However, HHs that experienced a high-cost health event and male respondents reported slightly higher WTP. The observed nominal levels of WTP are higher than has been estimated hitherto.

Substitutes to Baseline Surveys

World Scientific series in health investment and financing, Feb 1, 2020

This chapter seeks to propose an efficient alternative to household surveys (HHSs) for obtaining ... more This chapter seeks to propose an efficient alternative to household surveys (HHSs) for obtaining data needed to launch a community-based health insurance scheme. We discuss the three essential pieces of information that are used for the design of the benefits package and its pricing. These are morbidity and utilization patterns, the average cost of care locally, and the distribution of that cost. The methods available to source these data without conducting a full HHS are elaborated.

Baseline Study and Its Purpose

World Scientific series in health investment and financing, Feb 1, 2020

Understanding the local needs of a community lays the foundation for the launch of a microinsuran... more Understanding the local needs of a community lays the foundation for the launch of a microinsurance scheme. The baseline study must precede the operational processes of presenting different options of benefits packages to the community. This chapter discusses the relevance of a baseline study, its objectives, and the stages involved in planning and conducting the study.

The Governance Structure and Training the Key Actors

World Scientific Series in Health Investment and Financing, 2020

The governance structure of community-based health insurance (CBHI) comprises members of the comm... more The governance structure of community-based health insurance (CBHI) comprises members of the community who are also the owners of the scheme. The model is driven by the principle of subsidiarity which posits that every social or economic issue should be dealt with at the most immediate (or lowest) level that can resolve it while respecting camaraderie and human dignity. We learn about the roles and responsibilities of each key actor and their contribution in the various business processes of the scheme.

IntechOpen eBooks, Nov 25, 2023

This chapter offers a detailed analysis of microinsurance (nowadays often called "inclusive insur... more This chapter offers a detailed analysis of microinsurance (nowadays often called "inclusive insurance"), an innovative hybrid model combining grassroots initiatives with top-down approaches to reach populations not covered by government-operated social protection systems. With half of the global population, primarily in low and middle-income countries, lacking social protection, the chapter focuses on the potential of microinsurance to address this pressing issue. The commercial microinsurance attempts, often labeled as "insurance for the poor," have been largely insufficient. An alternative lies in the "Collaborative and Contributive" (C&C) model of microinsurance, which harnesses social forces, typically more compelling than market forces in informal settings, to stimulate demand. The chapter evaluates microinsurance's social and economic impacts, drawing insights from 25 years of progress. It underscores the need for policymakers, international development bankers, and the reinsurance industry to recognize the potential of the C and C model in providing comprehensive insurance to marginalized populations.

Social Science Research Network, Sep 27, 2007

Most industrialized countries have financed health services through health insurance. Two systems... more Most industrialized countries have financed health services through health insurance. Two systems prevail: private, or public (social) health insurance. The theoretical differences between them are reviewed. It is argued that most health systems are, however, hybrids and that health insurance reform in Europe and the United States has accentuated this trend because the principles distinguishing the two systems have often been ignored. This is illustrated through the evolution of voluntary vs. compulsory affiliation, coping with moral hazard, and provider regulation. H ealth insurance has become the foremost form of financing access to curative health services in most countries. Two approaches have been most prevalent: social health insurance (SHI), and private health insurance (PHI). These differ in their basic assumptions: SHI is guided by the notion that health is a basic human right and insurance a tool to advance its implementation. PHI views health as a cluster of risks, insurance of which is a profitable economic activity. Are these two approaches contradictory or complementary? Can they be reconciled into a coherent logic? Have their philosophical and ethical differences been made to accord or, on the contrary, accented, in the process of health insurance reform? Health insurance reforms have emphasized economic issues. Both SHI and PHI have seemingly faced the same problems: rising cost of curative care and rapid development of health technology, linked to the importance of biomedical centres of excellence and increasing health expectations of the public. At the same time, insurers had to deal with financing problems,

Willingness to Pay for Health Insurance

World Scientific series in health investment and financing, Dec 1, 2018

Following are the consolidated main messages from Chapters 5.1–5.3:Estimating Willingness to Pay ... more Following are the consolidated main messages from Chapters 5.1–5.3:Estimating Willingness to Pay (WTP) for health insurance (HI) coverage is the only way to estimate the expected income of voluntary and contributory HI schemes. This estimate is needed to ensure that the cost of benefits packages remain within available resources, so as to minimize the risk of bankruptcy.Data on WTP are necessary to inform the design of customized HI benefits packages by consumers, notably by groups or communities.One approach to estimate individual WTP is the Revealed Preferences method (RP), introduced first by Samuelson, which involves studying actual purchasing behavior of products which are related to the product we are interested in. The assumption is that revealed preferences can identify the value people place on a product for which purchasing information does not exist.Another approach to estimate WTP is the Stated Preferences method (SP), which involves asking people what they would be willing to pay for insurance coverage that they do not yet have, and that may not be available in the market. SP has been refined into several techniques, and the one used most often to value non-market goods is called Contingent Valuation (CV). It consists of asking respondents the maximum amount they would be willing to pay for an intervention under evaluation (e.g. insurance).Most of the rural population in low-income countries is not familiar with the concept of insurance. Hence, it is challenged to reveal the price they are willing to pay for (insurance coverage) a product they have never before been offered or purchased.Field evidence of experiments with choice of package and price by groups of rural poor people in India points that they tend to converge toward consensus on the components of the benefit package and the price per person per year (PPPY), namely on the generally accepted declared WTP.It must be recognized that the actual level of their WTP could differ from the declared level. A first estimate of the gap between declared and actual WTP in community-based health insurance (CBHI) has been obtained from the evidence that households modulate WTP levels not by negotiating a different price, but by limiting the number of household members enrolled (at the agreed price PPPY) to reduce the total cost per household for HI. Initial evidence suggests that households enrolled only half their members in the first and second year. Longitudinal studies could verify whether the gap between the declared and actual WTP would diminish over time.Dror and Koren (2012) conducted a review of 14 experimental field studies eliciting WTP for health insurance among low-income persons in developing countries. They observed that the large methodological diversity reported in these studies made it impossible to identify a single “gold standard” method to elicit and estimate WTP.However, there was implied consensus that WTP must be explored locally, because there is no single “one-size-fits-all” option to determine the income side of different HMI schemes operating in different settings. Thus, estimates of WTP were based on household surveys. Collecting data with such surveys is both time-consuming and expensive.Several studies explored faster and cheaper methods to estimate WTP than surveys.Binnendijk et al. (2013) examined whether the relation between WTP for HI and income might be similar to Engel’s Law, an observation in economics stating that the proportion of income spent on food decreases as income increases, even if actual expenditure on food rises. These authors used data from six locations in India to check WTP expressed as a percentage of three anchors: overall income, discretionary income, and food expenditures, by calculating the Coefficient of Variation (for inter-community variation) and Concentration indices (for intra-community variation). They found that food expenditures had the most consistent relationship with WTP within each location, and across the six locations. This suggests that, just like food, HI is considered a necessity good even for people with very low income and no prior experience with health insurance. Thus, it is possible to estimate the WTP level based on each community’s food expenditures.On an average, WTP for CBHI was around 4.5% of food expenditures in the studied locations. Food expenditure information can be obtained through cheap and fast research methods, such as focus group discussions with target communities or from data published routinely and in the public domain.Nosratnejad et al. (2016) estimated WTP for HI on the basis of readily available data pertaining to GDP per capita, by using vote counting to identify factors which were consistently correlated with higher WTP for insurance: family size, education level, income, past hospitalization, and perceived poor health status. Their meta-analysis revealed that the WTP for HI among rural households in low and middle-income countries (LMICs) was…

Financing Micro Health Insurance: Theory, Methods and Evidence

Healthcare for all at affordable prices is still a major but universally elusive goal. Everyone s... more Healthcare for all at affordable prices is still a major but universally elusive goal. Everyone spends money on healthcare, and it is the most impoverishing consumption item. Thus, most governments (and the United Nations) promote Universal Health Coverage — each country's unique blend of tools for healthcare financing, including taxes, subsidies and market controls.

Social Science Research Network, 2014

Data in Microinsurance

World Scientific Series in Health Investment and Financing, 2020

This chapter aims to introduce the relevance of data in establishing a microinsurance scheme. The... more This chapter aims to introduce the relevance of data in establishing a microinsurance scheme. The success of a scheme rests in large part on the affordability of the benefits package (premium) and the relevance of the benefits it provides to the members. There are several combinations for such a solution, and identifying them requires using local, context-specific, and reliable data. Here we study the significance of data in microinsurance, the various types of data available, their sources, and methods to present the findings of the data analysis.

Estimating Willingness to Pay

Actual community-based health insurance (CBHI) premium payments often fall short of Willingness-t... more Actual community-based health insurance (CBHI) premium payments often fall short of Willingness-to-Pay (WTP) estimates. This study examines the gap between the estimated premiums and actual payments for CBHI by analyzing data from 3,685 households in rural India. Descriptive statistics are used to analyze the gap between the estimated premium and actual payments. Heckman two-stage sample-selection model is applied to analyze the predictors of actual payment, subject to household enrolment in CBHI. The estimated premiums were 0.50–1.26% of per-capita gross domestic product (PCGDP). The actual payments were ~50% of the estimates. The gap resulted as households enrolled fewer family members than expected. Further analysis indicates that a quadratic function (to estimate expected enrollees from the household) combining with a fixed premium (expressed as a percentage of PCGDP) can better predict actual income. Heckman analysis indicates that focusing on greater awareness and financial li...

Pricing of Microinsurance or Rate Making

In commercial insurance, it is common practice to charge each individual the premium that reflect... more In commercial insurance, it is common practice to charge each individual the premium that reflects that person’s estimated contribution to the risk pool. However, in microinsurance, community rating is applied, whereby every participant pays the same premium, irrespective of age, gender, health status, or claims history. This methodology is challenging in terms of pricing the package and maintaining an equilibrium between high-risk and low-risk individuals. The reality in microinsurance practice is that the price determines the package, rather than the other way around. This chapter provides a detailed guideline on context-dependent pricing.

Why and how to apply re-assurance to community health schemes in low-income countries?: urquoi et comment appliquer la ré-assurance aux systèmes de santé communautaires dans les pays à faible revenu?

Dans les pays a faible revenu, la plupart des personnes appartenant au secteur informel se trouve... more Dans les pays a faible revenu, la plupart des personnes appartenant au secteur informel se trouvent totalement depourvues de couvertures medicales, en raison du financement insuffisant de services sante. Le role des communautes qui ont institue un partage des risques, decrites comme des groupes de micro-assurances, a ete reconnu, et le nombre de ces initiatives est en croissance. Toutefois, les unites de micro-assurance sont rarement structurees comme une veritable assurance-maladie. Les causes de leur instabilite financiere et les solutions qui s'offrent sont expliquees dans la dissertation, basees sur des donnees factuelles, notamment l'Ouganda et les Philippines, ainsi que des simulations de situations, pour examiner les arguments avances et les solutions proposees. Cette dissertation porte sur l'adaptation de techniques de gestion du risque aux systemes communautaires ; plus particulierement, l'accent est mis sur le transfert de risque de groupe de micro-assurance a des systemes de reassurance. Un modele de reassurance a ete elabore, base sur deux hypotheses : (i) que la reassurance couvre des risques "assurable" au-dela d'un seuil, contre le paiement d'une prime ; (ii) que les unites de micro-assurance soient responsables des paiements des risques jusqu'a ce seuil (plus prime de reassurance). Un algorithme est propose pour distinguer les prestations assurables de ceux qui sont non assurables. Le principal enseignement de cette etude est que, lorsque les resultats financiers des groupes de micro-assurance peuvent etre estimes, ils peuvent faire l'objet de traites de reassurance ce qui permet de les stabiliser des la premiere annee. Le deuxieme enseignement est qu'il faut parfois que le pool de reassurance fonctionne pendant plusieurs annees avant que l'on puisse parvenir a equilibrer les recettes et les couts. Le troisieme enseignement est que la taille de groupe de reassures peut raccourcir cette periode, ainsi que reduire le cout de prime du reassureur.

The Geneva Papers on Risk and Insurance - Issues and Practice, 2021

In considering the focus of the special issues on this theme, the Editor-in-Chief and the Editori... more In considering the focus of the special issues on this theme, the Editor-in-Chief and the Editorial Board allowed the Guest Editor(s) freedom of choice. They gracefully refrained from taking a position on whether microinsurance required a separate theoretical framing or whether it should be analysed using classical models (thus suggesting that this is another type of insurance). It is helpful to recall that the term microinsurance was first used in an article published in 1999 (Dror and Jacquier 1999). It is also useful to remind that most of the printed material (this issue included) offers empirical analysis. We scoped the volume of publications on this topic in Google Scholar since 2000 (see Fig. 1). The first decade saw a tenfold increase in the number of publications per year, from about 100 to close to 1000. After that, we witness a continued but lesser growth (the highest number of microinsurance publications per year, 2300, was recorded in 2014). The ResearchGate weekly reports of browses-downloads-citations also suggest an ever-increasing and widespread use of published material. The Web of Science count of microinsurance publications shows two peaks, in 2016 and 2019. These were the years when this journal published special issues on microinsurance. This suggests how significant the contribution of the special issues was to scientific (peer-reviewed) publications on this topic. The more comprehensive treatises on microinsurance were published as books. Also, we recall region-specific scoping studies that have been the source of statistics on enrollments. Over this time, most authors have moved on from the initial preoccupation with definitions. We have one article summarising the developments in this

World Scientific series in health investment and financing, Dec 1, 2018

The Institute of Social Studies is Europe's longest-established centre of higher education and re... more The Institute of Social Studies is Europe's longest-established centre of higher education and research in development studies. On 1 July 2009, it became a University Institute of the Erasmus University Rotterdam (EUR). Postgraduate teaching programmes range from six-week diploma courses to the PhD programme. Research at ISS is fundamental in the sense of laying a scientific basis for the formulation of appropriate development policies. The academic work of ISS is disseminated in the form of books, journal articles, teaching texts, monographs and working papers. The Working Paper series provides a forum for work in progress which seeks to elicit comments and generate discussion. The series includes academic research by staff, PhD participants and visiting fellows, and award-winning research papers by graduate students.

Development of a new cost- & time effective methodology to upscale demand for health insurance among the poor in India

Microinsurance: Innovations in Low-Cost Health Insurance

World Scientific series in health investment and financing, Dec 1, 2018

Microinsurance--low-cost health insurance based on a community, cooperative, or mutual and self-h... more Microinsurance--low-cost health insurance based on a community, cooperative, or mutual and self-help arrangements-can provide financial protection for poor households and improve access to health care. However, low benefit caps and a low share of premiums paid as benefits--both designed to keep these arrangements in business--perversely limited these schemes' ability to extend coverage, offer financial protection, and retain members. We studied three schemes in India, two of which are member-operated and one a commercial scheme, using household surveys of insured and uninsured households and interviews with managers. All three enrolled poor households and raised their use of hospital services, as intended. Financial exposure was greatest, and protection was least, in the commercial scheme, which imposed the lowest caps on benefits and where income was the lowest.

Community-Based Health Insurance (CBHI) (a.k.a. micro health insurance) is a contributory health ... more Community-Based Health Insurance (CBHI) (a.k.a. micro health insurance) is a contributory health insurance among rural poor in developing countries. As CBHI schemes typically function with no subsidy income, the schemes' expenditures cannot exceed their premium income. A good estimate of Willingness-To-Pay (WTP) among the target population affiliating on a voluntary basis is therefore essential for package design. Previous estimates of WTP reported materially and significantly different WTP levels across locations (even within one state), making it necessity to base estimates on household surveys. This is time-consuming and expensive. This study seeks to identify a coherent anchor for local estimation of WTP without having to rely on household surveys in each CBHI implementation. Using data collected in 2008e2010 among rural poor households in six locations in India (total 7874 households), we found that in all locations WTP expressed as percentage of income decreases with household income. This reminds of Engel's law on food expenditures. We checked several possible anchors: overall income, discretionary income and food expenditures. We compared WTP expressed as percentage of these anchors, by calculating the Coefficient of Variation (for inter-community variation) and Concentration indices (for intra-community variation). The Coefficient of variation was 0.36, 0.43 and 0.50 for WTP as percent of food expenditures, overall income and discretionary income, respectively. In all locations the concentration index for WTP as percentage of food expenditures was the lowest. Thus, food expenditures had the most consistent relationship with WTP within each location and across the six locations. These findings indicate that like food, health insurance is considered a necessity good even by people with very low income and no prior experience with health insurance. We conclude that the level of WTP could be estimated based on each community's food expenditures, and that this information can be obtained everywhere without having to conduct household surveys.

Incidence of illness among resource-poor households: evidence from five locations in India

PubMed, Aug 1, 2009

Background & objective: This study examines the association between household attributes and perc... more Background & objective: This study examines the association between household attributes and perceived morbidity within resource-poor house holds (HHs) in India at five locations. This presents an innovation compared to most epidemiological studies, which focus on associations between the incidence of an illness and characteristics of the ill person. Methods: Perceived morbidity was represented by a variable called "Incidence of illness in a HH" (IIH) = the number of self reported illness episodes during three months preceding the survey, divided by household size. Variables were analyzed through bivariate correlation and multivariate linear regression. The evidence was based on a HH survey conducted in 2005 in Maharashtra, Bihar, and Tamil Nadu. Data yield reflected responses of 3,531 HHs, representing 17,323 individuals and 4,316 illness episodes. Results: Analysis showed that incidence of illness among women was higher; the under 5 yr olds and elderly (+55) were particularly vulnerable. However, in the multivariate linear regression model, gender ratio within HHs became an insignificant explanatory variable. Age distribution had a small but significant effect. Household size and the level of education in the HH were negatively and significantly associated with IIH. The regression analysis showed that income had a modest positive effect, but improved housing was associated with reduced IIH. Large differences were noted in IIH across locations. Interpretation & conclusion: Our findings showed that attributes of the unit household, including type of house, income, education and size, have significant effects on IIH; variability in IIH cannot solely be explained by age and gender of HH members.

Health policy, Jun 1, 2007

This study, conducted in India in 2005, provides evidence on Willingness to pay (WTP), gathered t... more This study, conducted in India in 2005, provides evidence on Willingness to pay (WTP), gathered through a unidirectional (descending) bidding game among 3024 households (HH) in seven locations where micro health insurance units are in operation. Insured persons reported slightly higher WTP values than uninsured. About two-thirds of the sample agreed to pay at least 1%; about half the sample was willing to pay at least 1.35%; 30% was willing to pay about 2.0% of annual HH income as health insurance premium. Nominal WTP correlates positively with income but relative WTP (expressed as percent of HH income) correlates negatively. The correlation between WTP and education is secondary to that of WTP with HH income. Household composition did not affect WTP. However, HHs that experienced a high-cost health event and male respondents reported slightly higher WTP. The observed nominal levels of WTP are higher than has been estimated hitherto.