Kaci Kennedy McDade, G. Kokwaro, K. Munge, O. Ogbuoji
As more countries move from low- to middle-income status, they are perceived as increasingly capable of financing their own health systems. Some donors have begun to transition their support out of such middle-income countries (MICs) to redirect their funds to countries with greater needs. However, this transition may leave a funding gap for MICs that could be difficult to fill when external resources decline. If not carefully managed, such financial shifts could lead to the loss of health gains that occurred while receiving substantial external financial support. Understanding levels of donor dependency (i.e., whether or not a country is likely to have capacity to fill a funding gap caused by donor transition) and donor concentration (i.e., when only a few donors make up the majority of aid) can illuminate areas of potential vulnerability for transition. In this study, we analyzed Kenya’s health system for donor dependency and donor concentration.
{"title":"Development Finance in Transition: Donor Dependency and Concentration in Kenya’s Health Sector","authors":"Kaci Kennedy McDade, G. Kokwaro, K. Munge, O. Ogbuoji","doi":"10.2139/ssrn.3797710","DOIUrl":"https://doi.org/10.2139/ssrn.3797710","url":null,"abstract":"As more countries move from low- to middle-income status, they are perceived as increasingly capable of financing their own health systems. Some donors have begun to transition their support out of such middle-income countries (MICs) to redirect their funds to countries with greater needs. However, this transition may leave a funding gap for MICs that could be difficult to fill when external resources decline. If not carefully managed, such financial shifts could lead to the loss of health gains that occurred while receiving substantial external financial support. Understanding levels of donor dependency (i.e., whether or not a country is likely to have capacity to fill a funding gap caused by donor transition) and donor concentration (i.e., when only a few donors make up the majority of aid) can illuminate areas of potential vulnerability for transition. In this study, we analyzed Kenya’s health system for donor dependency and donor concentration.","PeriodicalId":243720,"journal":{"name":"ERN: Microeconometric Studies of Health Markets (Topic)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126787260","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}
Anastasia Girshina, François Koulischer, Ulf von Lilienfeld-Toal
House prices have increased faster than average income in many countries over the last decade, raising concerns on the affordability of housing. We study the impact of transaction taxes on the real estate market and the effectiveness of tax subsidies to make housing more affordable. We show how the demand and supply elasticities for housing determine the price impact of tax subsidies and the distribution of gains between buyers and sellers. We then use data on all real estate transactions in Luxembourg from 2007 to 2018 to estimate the elasticity of housing supply and demand. For identification, we exploit discontinuities in the transaction tax schedule as well as rules on tax subsidies for new constructions. Our estimates suggest that the elasticity of house prices to transaction taxes is 0.27, so buyers capture a large part of the surplus from the subsidies.
{"title":"Housing Affordability and Transaction Tax Subsidies","authors":"Anastasia Girshina, François Koulischer, Ulf von Lilienfeld-Toal","doi":"10.2139/ssrn.3758466","DOIUrl":"https://doi.org/10.2139/ssrn.3758466","url":null,"abstract":"House prices have increased faster than average income in many countries over the last decade, raising concerns on the affordability of housing. We study the impact of transaction taxes on the real estate market and the effectiveness of tax subsidies to make housing more affordable. We show how the demand and supply elasticities for housing determine the price impact of tax subsidies and the distribution of gains between buyers and sellers. We then use data on all real estate transactions in Luxembourg from 2007 to 2018 to estimate the elasticity of housing supply and demand. For identification, we exploit discontinuities in the transaction tax schedule as well as rules on tax subsidies for new constructions. Our estimates suggest that the elasticity of house prices to transaction taxes is 0.27, so buyers capture a large part of the surplus from the subsidies.","PeriodicalId":243720,"journal":{"name":"ERN: Microeconometric Studies of Health Markets (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128452084","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}
The French market for specialist physician care has a dual legal structure: physicians must exclusively work in sector 1 and charge regulated fees or in sector 2, where they can freely set their fees. Patient out-of-pocket payments in sector 2 are partially covered by private insurance. The primary differentiating factor between both sectors is the number of patients per specialist, which in turn directly affects the overall quality of the service provided. We built an equilibrium model to analyse both specialists decisions about which sector to work in, and patients choice of physician and therefore sector. More specifically, the model allowed us to study the effect of changes in prices and economy-wide patient-to-specialist ratios on profits and patients utility associated with the services provided in each sector.
{"title":"A Model for Dual Healthcare Market with Congestion Differentiation","authors":"Damien Besancenot, K. Lamiraud, R. Vranceanu","doi":"10.2139/ssrn.3738625","DOIUrl":"https://doi.org/10.2139/ssrn.3738625","url":null,"abstract":"The French market for specialist physician care has a dual legal structure: physicians must exclusively work in sector 1 and charge regulated fees or in sector 2, where they can freely set their fees. Patient out-of-pocket payments in sector 2 are partially covered by private insurance. The primary differentiating factor between both sectors is the number of patients per specialist, which in turn directly affects the overall quality of the service provided. We built an equilibrium model to analyse both specialists decisions about which sector to work in, and patients choice of physician and therefore sector. More specifically, the model allowed us to study the effect of changes in prices and economy-wide patient-to-specialist ratios on profits and patients utility associated with the services provided in each sector.","PeriodicalId":243720,"journal":{"name":"ERN: Microeconometric Studies of Health Markets (Topic)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122090976","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}
The Patient Protection and Affordable Care Act (ACA) introduced significant changes to the health insurance marketplace in the United States. The act also imposed reporting requirements on insurers. The law has required insurers since 2010 to file yearly the Supplemental Health Care Exhibit (SHCE). The SHCE provides unique information on how health insurers operate. We analyze data in the SCHE to understand how insurers have complied with one of the major new regulations affecting health insurers' operations arising from the ACA—the Medical Loss Ratio (MLR) Provision. This requires that insurers spend a minimum percentage of their premium revenue on medical claims, quality improvement expenses, and deductible fraud and abuse detection and recovery expenses. Our analysis of the 2010–2017 SHCE indicates that insurers' underwriting performance worsened in the early years of the ACA as they worked to increase MLRs to become ACA‐compliant. Analysis of the SHCE further reveals that insurers' profits from managing uninsured plans grew as the profitability of underwriting insured plans decreased. Future research on health insurer operations is warranted. The currently underutilized and data‐rich SHCE provides unique information that makes future research possible.
{"title":"Health Insurers' Operations in the Face of Health Care Reform: An Analysis of the Supplemental Health Care Exhibit","authors":"Yung-Chou Lei, M. Browne","doi":"10.1111/rmir.12154","DOIUrl":"https://doi.org/10.1111/rmir.12154","url":null,"abstract":"The Patient Protection and Affordable Care Act (ACA) introduced significant changes to the health insurance marketplace in the United States. The act also imposed reporting requirements on insurers. The law has required insurers since 2010 to file yearly the Supplemental Health Care Exhibit (SHCE). The SHCE provides unique information on how health insurers operate. We analyze data in the SCHE to understand how insurers have complied with one of the major new regulations affecting health insurers' operations arising from the ACA—the Medical Loss Ratio (MLR) Provision. This requires that insurers spend a minimum percentage of their premium revenue on medical claims, quality improvement expenses, and deductible fraud and abuse detection and recovery expenses. Our analysis of the 2010–2017 SHCE indicates that insurers' underwriting performance worsened in the early years of the ACA as they worked to increase MLRs to become ACA‐compliant. Analysis of the SHCE further reveals that insurers' profits from managing uninsured plans grew as the profitability of underwriting insured plans decreased. Future research on health insurer operations is warranted. The currently underutilized and data‐rich SHCE provides unique information that makes future research possible.","PeriodicalId":243720,"journal":{"name":"ERN: Microeconometric Studies of Health Markets (Topic)","volume":"326 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116108167","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}
Adequate nutrition is generally regarded as a core dimension in any evaluation of well‐being. In the context of India, a country with a high prevalence of poor nutrition, there is a dearth of nutrition studies with adequate coverage and comparability. Using primary data on food consumption from a village in a poorer state of India, we study the consumption of five key nutrients, namely, calories, protein, carbohydrates, calcium and iron. Among the various determinants of nutrition, we find that expenditure has a significant impact on nutrition and the expenditure elasticity of nutrition is comparatively high for all the key nutrients. By correcting for potential endogeneity, we demonstrate a causal link from expenditure and food subsidy provided by the public distribution system to nutritional intake. There is some evidence that household characteristics such as household size and gender of the household head matter for nutrition; however, they are not robust under various specifications.
{"title":"Nutrient Consumption in India: Evidence from a Village Study","authors":"I. Dutta, S. Kapoor, P. Pattanaik","doi":"10.1111/rode.12679","DOIUrl":"https://doi.org/10.1111/rode.12679","url":null,"abstract":"Adequate nutrition is generally regarded as a core dimension in any evaluation of well‐being. In the context of India, a country with a high prevalence of poor nutrition, there is a dearth of nutrition studies with adequate coverage and comparability. Using primary data on food consumption from a village in a poorer state of India, we study the consumption of five key nutrients, namely, calories, protein, carbohydrates, calcium and iron. Among the various determinants of nutrition, we find that expenditure has a significant impact on nutrition and the expenditure elasticity of nutrition is comparatively high for all the key nutrients. By correcting for potential endogeneity, we demonstrate a causal link from expenditure and food subsidy provided by the public distribution system to nutritional intake. There is some evidence that household characteristics such as household size and gender of the household head matter for nutrition; however, they are not robust under various specifications.","PeriodicalId":243720,"journal":{"name":"ERN: Microeconometric Studies of Health Markets (Topic)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130636382","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}
Access to public healthcare in Nairobi County is unequal among social classes. Lower social classes have worse healthcare than either the upper or the middle classes. These health inequalities are correlated with socio-economic inequalities. The higher socio-economic classes have better access to healthcare than the lower socio-economic classes. Higher incomes, education, employment and wealth result in better health of the households in the County. Unequal access to healthcare contributes to disparities in health status, increases costs for both the insured and the uninsured. Lack of access to healthcare reduces disposable incomes, particularly burdening the lower income households. These households cannot afford the care they need. This has forced them to forego such care altogether. The objectives of the study were three, namely: to evaluate the influence of demographic variables in access to public healthcare, to evaluate the influence of socio-cultural factors in access to public health care, and to evaluate the influence of institutional factors in access to public healthcare. The study used descriptive design, specifically, cross-sectional design for collection, measurements and analysis of data. The study took place in Nairobi County. The target population was households living in Nairobi County, where the sample was drawn from. The sampling techniques included multi-stage random sampling, random sampling, stratifies random sampling, cluster random sampling, convenient sampling and purposive sampling. The sample size was obtained using Chadha’s formula (2006) to arrive at 1066 sample size. Data collection instruments included observations, face-to-face interviews, questionnaires, in-depth interviews and focus group discussions. Qualitative data was analyzed thematically but quantitative data was analyzed using descriptive statistics. Data was analyzed using SPSS version 23. The results show that there were positive correlations between independent and dependent variables. The P-value was statistically significant. The results were not due to random chance and that P-0.01 < 0.05 and this confirms a positive relations ships between the variables. The relationships were mutually inclusive and highly correlated. On that basis, the null hypotheses were rejected and the alternate hypotheses accepted. The results show that demographic (disposing), socio-cultural (need) and institutional (enabling) factors influence access to healthcare. Socio-economic factors should be addressed to benefit all the households. Socio-cultural factors should be distributed fairly among the households. Health systems should be improved and adequately financed to provide the requisite resources to all the households.
在内罗毕县，不同社会阶层获得公共保健的机会是不平等的。较低的社会阶层比上层或中产阶级拥有更差的医疗保健。这些健康不平等与社会经济不平等有关。较高的社会经济阶层比较低的社会经济阶层有更好的机会获得医疗保健。收入、教育、就业和财富的增加使该县家庭的健康状况得到改善。获得医疗保健的机会不平等造成了健康状况的差异，增加了参保人和未参保人的费用。缺乏获得医疗保健的机会减少了可支配收入，特别是给低收入家庭增加了负担。这些家庭负担不起他们需要的护理。这迫使他们完全放弃了这种照顾。本研究的目标有三个，即:评估人口变量对获得公共医疗服务的影响，评估社会文化因素对获得公共医疗服务的影响，以及评估制度因素对获得公共医疗服务的影响。本研究采用描述性设计，具体地说，采用横断面设计来收集、测量和分析数据。这项研究在内罗毕县进行。目标人群是居住在内罗毕县的家庭，样本是从那里抽取的。抽样技术包括多阶段随机抽样、随机抽样、分层随机抽样、整群随机抽样、方便抽样和目的抽样。样本量采用Chadha公式(2006)得到，样本量为1066。数据收集手段包括观察、面对面访谈、问卷调查、深入访谈和焦点小组讨论。定性资料采用专题分析，定量资料采用描述性统计分析。数据分析采用SPSS version 23。结果表明，自变量与因变量之间存在正相关关系。p值有统计学意义。结果不是由于随机机会和P-0.01 < 0.05，这证实了变量之间的正相关关系。这种关系是相互包容和高度相关的。在此基础上，零假设被拒绝，替代假设被接受。结果表明，人口(处置)、社会文化(需要)和体制(使能)因素影响获得保健的机会。应处理社会经济因素，使所有家庭受益。社会文化因素应在家庭中公平分配。应当改善卫生系统并为其提供充足的资金，以便向所有家庭提供必要的资源。
{"title":"The Influence of Socio-Cultural Factors in Access to Healthcare in Kenya: A Case of Nairobi County, Kenya","authors":"Davies N. Chelogoi, F. Jonyo, H. Amadi","doi":"10.4236/jss.2020.85023","DOIUrl":"https://doi.org/10.4236/jss.2020.85023","url":null,"abstract":"Access to public healthcare in Nairobi County is unequal among social \u0000classes. Lower social classes have worse healthcare than either the upper or \u0000the middle classes. These health inequalities are correlated with \u0000socio-economic inequalities. The higher socio-economic classes have better \u0000access to healthcare than the lower socio-economic classes. Higher incomes, \u0000education, employment and wealth result in better health of the households in \u0000the County. Unequal access to healthcare contributes to disparities in health \u0000status, increases costs for both the insured and the uninsured. Lack of access \u0000to healthcare reduces disposable incomes, particularly burdening the lower \u0000income households. These households cannot afford the care they need. This has \u0000forced them to forego such care altogether. The objectives of the study were \u0000three, namely: to evaluate the influence of demographic variables in access to \u0000public healthcare, to evaluate the influence of socio-cultural factors in \u0000access to public health care, and to evaluate the influence of institutional \u0000factors in access to public healthcare. The study used descriptive design, \u0000specifically, cross-sectional design for collection, measurements and analysis \u0000of data. The study took place in Nairobi County. The target population was \u0000households living in Nairobi County, where the sample was drawn from. The \u0000sampling techniques included multi-stage random sampling, random sampling, \u0000stratifies random sampling, cluster random \u0000sampling, convenient sampling and purposive sampling. The sample size was \u0000obtained using Chadha’s \u0000formula (2006) to arrive at 1066 sample size. \u0000Data collection instruments included observations, face-to-face interviews, \u0000questionnaires, in-depth interviews and focus group discussions. Qualitative \u0000data was analyzed thematically but quantitative data was analyzed using \u0000descriptive statistics. Data was analyzed using SPSS version 23. The results \u0000show that there were positive correlations between independent and dependent \u0000variables. The P-value was statistically \u0000significant. The results were not due to random chance and that P-0.01 < 0.05 and this confirms a \u0000positive relations ships between the variables. The relationships were mutually \u0000inclusive and highly correlated. On that basis, the null hypotheses were \u0000rejected and the alternate hypotheses accepted. The results show that \u0000demographic (disposing), socio-cultural (need) and institutional (enabling) \u0000factors influence access to healthcare. Socio-economic factors should be \u0000addressed to benefit all the households. Socio-cultural factors should be \u0000distributed fairly among the households. Health systems should be improved and \u0000adequately financed to provide the requisite resources to all the households.","PeriodicalId":243720,"journal":{"name":"ERN: Microeconometric Studies of Health Markets (Topic)","volume":"520 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116310738","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}
Anecdotal reports and small-scale studies suggest that elections are stressful, and might lead to a deterioration in voters’ mental well-being. Nonetheless, researchers have yet to establish whether elections actually make people sick, and if so, why. By applying a regression discontinuity design to administrative health care claims from Taiwan, we determine that elections increased health care use and expense only during legally specified campaign periods by as much as 19%. Overall, the treatment cost of illness caused by elections exceeded publicly reported levels of campaign expenditure, and accounted for 2% of total national health care costs during the campaign period.
{"title":"Do Elections Make You Sick?","authors":"Hung‐Hao Chang, C. Meyerhoefer","doi":"10.3386/w26697","DOIUrl":"https://doi.org/10.3386/w26697","url":null,"abstract":"Anecdotal reports and small-scale studies suggest that elections are stressful, and might lead to a deterioration in voters’ mental well-being. Nonetheless, researchers have yet to establish whether elections actually make people sick, and if so, why. By applying a regression discontinuity design to administrative health care claims from Taiwan, we determine that elections increased health care use and expense only during legally specified campaign periods by as much as 19%. Overall, the treatment cost of illness caused by elections exceeded publicly reported levels of campaign expenditure, and accounted for 2% of total national health care costs during the campaign period.","PeriodicalId":243720,"journal":{"name":"ERN: Microeconometric Studies of Health Markets (Topic)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116205036","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}
This paper establishes asymptotic properties for spiked empirical eigenvalues of sample covariance matrices for high-dimensional data with both cross-sectional dependence and a dependent sample structure. A new finding from the established theoretical results is that spiked empirical eigenvalues will reflect the dependent sample structure instead of the cross-sectional structure under some scenarios, which indicates that principal component analysis (PCA) may provide inaccurate inference for cross-sectional structures. An illustrated example is provided to show that some commonly used statistics based on spiked empirical eigenvalues misestimate the true number of common factors. As an application of high-dimensional time series, we propose a test statistic to distinguish the unit root from the factor structure and demonstrate its effective finite sample performance on simulated data. Our results are then applied to analyze OECD healthcare expenditure data and U.S. mortality data, both of which possess cross-sectional dependence as well as non-stationary temporal dependence. It is worth mentioning that we contribute to statistical justification for the benchmark paper by Lee and Carter [25] in mortality forecasting.
{"title":"Spiked Eigenvalues of High-Dimensional Separable Sample Covariance Matrices","authors":"Bo Zhang, Jiti Gao, G. Pan, Yanrong Yang","doi":"10.2139/ssrn.3496388","DOIUrl":"https://doi.org/10.2139/ssrn.3496388","url":null,"abstract":"This paper establishes asymptotic properties for spiked empirical eigenvalues of sample covariance matrices for high-dimensional data with both cross-sectional dependence and a dependent sample structure. A new finding from the established theoretical results is that spiked empirical eigenvalues will reflect the dependent sample structure instead of the cross-sectional structure under some scenarios, which indicates that principal component analysis (PCA) may provide inaccurate inference for cross-sectional structures. An illustrated example is provided to show that some commonly used statistics based on spiked empirical eigenvalues misestimate the true number of common factors. As an application of high-dimensional time series, we propose a test statistic to distinguish the unit root from the factor structure and demonstrate its effective finite sample performance on simulated data. Our results are then applied to analyze OECD healthcare expenditure data and U.S. mortality data, both of which possess cross-sectional dependence as well as non-stationary temporal dependence. It is worth mentioning that we contribute to statistical justification for the benchmark paper by Lee and Carter [25] in mortality forecasting.","PeriodicalId":243720,"journal":{"name":"ERN: Microeconometric Studies of Health Markets (Topic)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134377087","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}
In this paper we examine whether the Solow growth model is consistent with across-countries variations in standard of living once investments in education and health are explicitly and simultaneously taken into account. Using a sample of low- and middle-income economies, we provide evidence that per capita GDP is positively affected by population's health, here proxied by the life expectancy at birth. Public expenditure on health affects indirectly the level of per capita income through its positive effectect on life expectancy. Using a Finite Mixture approach, we also show that richer economies are those where the impact of unobserved factors on the level of per capita income is stronger.
{"title":"Health and Development","authors":"A. Bucci, L. Carbonari, M. Ranalli, G. Trovato","doi":"10.2139/ssrn.3460577","DOIUrl":"https://doi.org/10.2139/ssrn.3460577","url":null,"abstract":"In this paper we examine whether the Solow growth model is consistent with across-countries variations in standard of living once investments in education and health are explicitly and simultaneously taken into account. Using a sample of low- and middle-income economies, we provide evidence that per capita GDP is positively affected by population's health, here proxied by the life expectancy at birth. Public expenditure on health affects indirectly the level of per capita income through its positive effectect on life expectancy. Using a Finite Mixture approach, we also show that richer economies are those where the impact of unobserved factors on the level of per capita income is stronger.","PeriodicalId":243720,"journal":{"name":"ERN: Microeconometric Studies of Health Markets (Topic)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132047356","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}
This teaching case has the intention to guide through the conduction of a meaningful Data Envelopment Analysis (DEA) in the healthcare sector. A data sample on German hospitals is provided and used throughout different tasks. Apart from the implementation of the DEA model itself, the study also covers areas of pre- and post-processing. As a result, the user of the case study is confronted with common pitfalls and learns to work with procedures, which have emerged as gold standards. The participant is encouraged to use methods for the detection of outliers and for the treatment of missing values to cover common issues in this field. The comparison of different DEA models enhances the understanding of the mechanics of DEA, especially the relevance of slacks for the analysis. In including quality data into the study, another essential feature for hospital analyses is addressed.
With the Helmsman DEA, an interesting, however, rather unfamiliar procedure is presented to achieve a meaningful inclusion of the quality data into the analysis. Using bootstrapping as a subsequent method completes the study. Finally, a recommendation for the grading of the tasks is given. The results and the source code to all implementations are provided.
{"title":"Using Data Envelopment to Estimate Hospital Efficiencies – A Teaching Case","authors":"Sebastian Kohl","doi":"10.2139/ssrn.3495578","DOIUrl":"https://doi.org/10.2139/ssrn.3495578","url":null,"abstract":"This teaching case has the intention to guide through the conduction of a meaningful Data Envelopment Analysis (DEA) in the healthcare sector. A data sample on German hospitals is provided and used throughout different tasks. Apart from the implementation of the DEA model itself, the study also covers areas of pre- and post-processing. As a result, the user of the case study is confronted with common pitfalls and learns to work with procedures, which have emerged as gold standards. The participant is encouraged to use methods for the detection of outliers and for the treatment of missing values to cover common issues in this field. The comparison of different DEA models enhances the understanding of the mechanics of DEA, especially the relevance of slacks for the analysis. In including quality data into the study, another essential feature for hospital analyses is addressed.<br><br>With the Helmsman DEA, an interesting, however, rather unfamiliar procedure is presented to achieve a meaningful inclusion of the quality data into the analysis. Using bootstrapping as a subsequent method completes the study. Finally, a recommendation for the grading of the tasks is given. The results and the source code to all implementations are provided.","PeriodicalId":243720,"journal":{"name":"ERN: Microeconometric Studies of Health Markets (Topic)","volume":"29 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132275560","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}
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