Pub Date : 2018-12-01DOI: 10.1142/9789813238480_0005
D. Dror
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-si
{"title":"Willingness to Pay for Health Insurance","authors":"D. Dror","doi":"10.1142/9789813238480_0005","DOIUrl":"https://doi.org/10.1142/9789813238480_0005","url":null,"abstract":"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-si","PeriodicalId":421903,"journal":{"name":"World Scientific Series in Health Investment and Financing","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121163814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1142/9789813238480_0016
{"title":"Mobilizing Community-based Health Insurance to Enhance Awareness and Prevention of Airborne, Vectorborne, and Waterborne Diseases in Rural India","authors":"","doi":"10.1142/9789813238480_0016","DOIUrl":"https://doi.org/10.1142/9789813238480_0016","url":null,"abstract":"","PeriodicalId":421903,"journal":{"name":"World Scientific Series in Health Investment and Financing","volume":"34 13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123146816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1142/9789813238480_0007
{"title":"Estimating Willingness-to-Pay for Health Insurance Among Rural Poor in India by Reference to Engel’s Law","authors":"","doi":"10.1142/9789813238480_0007","DOIUrl":"https://doi.org/10.1142/9789813238480_0007","url":null,"abstract":"","PeriodicalId":421903,"journal":{"name":"World Scientific Series in Health Investment and Financing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122196552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-12-01DOI: 10.1142/9789813238480_0023
{"title":"Impact of Community-based Health Insurance in Rural India on Self-Medication and Financial Protection of the Insured","authors":"","doi":"10.1142/9789813238480_0023","DOIUrl":"https://doi.org/10.1142/9789813238480_0023","url":null,"abstract":"","PeriodicalId":421903,"journal":{"name":"World Scientific Series in Health Investment and Financing","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133195928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.1142/9789813278752_0008
E. Keuffel, A. Preker
The following sections are included:IntroductionBackgroundObjectiveCurrent SituationInstitutional (Supply-Side) Funding OptionsNon-institutional (Demand-Side) Funding: Implications for the Private SectorOptions and EvaluationCriteria for Entry (Education Providers)SummaryEndnotesReferences
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