Inequality Aversion Parameter Research Articles

Estimating the income-related inequality aversion to energy limiting behavior in the United States

Distributive energy justice is measured by the degree to which, and whether, different members of society have equal share in the benefits and burdens of the energy system. One way to achieve distributional energy justice is to ensure all households, regardless of income, can use as much energy as they need to heat and cool their home to desired temperature. We define a household's cooling balance point (CBP) as the ideal set temperature at which the household desires to keep its living space in summer; the heating balance point (HBP) is defined as the ideal set temperature in winter. To quantify the extent to which balance points were disproportionately concentrated among certain income groups, we used the extended concentration index. This index has an inequality aversion parameter that reflects the value judgment of a society. If this parameter <1, the society is pro-rich; if this parameter >1, as it increases, the society becomes more pro-poor. We estimated the empirical value of the income-related inequality aversion in eight U.S. states and examined several effects of demographic characteristics on inequality aversion.In an online survey, 1066 (from four southern states) and 906 (from four Midwest states) participants made choices between energy policies leading to different distributions of CBP (southern) or HBP (Midwest) across five income groups in a hypothetical society. Participants showed a pro-poor propensity: the median inequality aversions were 1.37, 95% CI of [1.35, 1.39] (CBP) and 1.56, 95% CI of [1.56, 1.60] (HBP). For both CBP and HBP: younger participants were less averse to inequality. For CBP, blacks (vs. whites) and conservatives (vs. centrist) were less averse to inequality; for HBP, Hispanics (vs. whites), low (vs. high) education participants, and those whose homes were well insulated (vs. adequately and vs. poorly insulated) were less averse to inequality. Our findings provide insights into how the broader public values energy justice, which further provides important policymaking implications.

Equitable Care for Severe Hemophilia_A: Distributional Cost-Effectiveness of Prophylactic Weekly Efanesoctocog Alfa Versus Standard-Care Factor VIII in Patients with Severe Hemophilia_A in the United States

Introduction: Prophylactic coagulation factor replacement is crucial to decrease bleeding episodes and improve quality-adjusted life expectancy (QALE) for patients with severe hemophilia A. Even with prophylactic treatment (i.e., at three to four times weekly) patients remain at risk of bleeding events and still develop chronic arthropathy across their lifetimes. The additional economic burden associated with lifelong prophylactic treatment is a major equity concern for patients with hemophilia A and their families. Efanesoctocog alfa is a recently developed extended half-life agent for hemophilia A prophylaxis and management, supporting the possibility of once-weekly prophylaxis. An open-label multicenter study (XTEND-1) showed that once-weekly dosing of efanesoctocog alfa improves the annualized bleeding rate (ABR) by 77% versus prophylaxis with standard-care factor VIII in patients with severe hemophilia A. We sought to evaluate, both for the first time, the conventional and distributional cost-effectiveness of prophylaxis with efanesoctocog alfa versus with standard-care factor VIII for patients with severe hemophilia A in the United States. Methods: For this independent analysis free of industry influence, we built a Markov model to examine the conventional cost-effectiveness of prophylaxis with efanesoctocog alfa versus standard-care factor VIII for patients with severe hemophilia A. Transition probabilities for ABRs and product utilization were informed by phase 3 study data and supplemented with FDA package insert information. Within ABRs, we accounted for treated bleeding severity and bleeding event types, inclusive of hemarthrosis, intracranial hemorrhage, in addition to assuming the prevalence of chronic arthropathy with SHL (i.e., due to silent bleed burden) is eliminated by efanesoctocog alfa. Costs for the base-case were sourced from the Centers for Medicare &amp; Medicaid Services with negotiated (i.e., lower) cost of efanesoctocog alfa supplied from the Veterans Affairs Federal Supply Schedule Service (VA-FSS). Age-, sex- and disease-specific background mortality were employed. Utilities for severe hemophilia A and disutilities for bleed events and hospitalizations were informed by extensive literature specific to severe hemophilia A. The primary outcome was the incremental cost-effectiveness ratio (ICER) in USD/QALY, at a willingness-to-pay threshold of $150,000/quality-adjusted life-year (QALY). The secondary outcome was a threshold analysis for the maximum efanesoctocog alfa price that renders efanesoctocog alfa prophylaxis cost-effective. To account for health inequities in the care of patients with hemophilia A we then conducted a distributional cost-effectiveness analysis (DCEA) to derive an equity weight threshold (i.e., inequality aversion parameter) for the decision of prophylaxis with efanesoctocog alfa versus with standard-care factor VIII. This threshold was then compared to prior estimates for commonly used equity weights in the United States (range 0.5-3.0). Results: In the base-case, prophylaxis with efanesoctocog alfa versus with standard-care factor VIII accrued 19.4 and 15.4 QALYs at mean costs of $17.3 and $9.7 million. The ICER for efanesoctocog alfa was $1,890,000/QALY (95% credible interval 1,190,000-3,330,000). Threshold analysis showed that prophylaxis with efanesoctocog alfa became cost-effective when the price of efanesoctocog alfa decreased by at least 59%. In deterministic sensitivity analysis, the model was most sensitive to the costs of efanesoctocog alfa and factor VIII. In probabilistic sensitivity analysis, standard-care factor VIII was favored over efanesoctocog alfa in 100% of 10,000 Monte Carlo simulations. The equity weight threshold for the treatment decision of prophylaxis with efanesoctocotog alfa versus with standard-care factor VIII was 7.4, higher than commonly used equity weights in the US. This implies a threshold that is higher than what has previously been used in the United States, per DCEA standards. Conclusion: As compared to standard-care factor VIII and at VA-FSS pricing, efanesoctocog alfa prophylaxis is conventionally cost-ineffective for patients with severe hemophilia A. Prophylaxis with efanesoctocog alfa does not meet commonly used distributive equity standards in the United States at this time.

Allotransplantation and Gene Therapy Equity for Children with Sickle Cell Disease: Distributional Cost-Effectiveness of Allotransplantation Vs Gene Therapy Vs Standard-of-Care in Pediatric Patients with Sickle Cell Disease in the United States

Introduction: Patients with sickle cell disease (SCD) have reduced quality-adjusted life expectancy due to substantial mortality risks and decreased quality-of-life for every year lived with the disease. Allotransplantation was the first treatment with curative potential, but it carries concomitant risks of transplant-related mortality and graft-versus-host disease (GVHD). Once approved, gene therapy would be the second treatment with the possibility of lifelong cure but unlike allotransplantation, it may do so without the concomitant risks. Prior research has shown that even if gene therapy is conventionally cost-ineffective versus the standard-of-care (SOC), it can be a justifiable treatment option for a historically marginalized patient population in the United States, as demonstrated by equity-weighted cost-effectiveness. For allotransplantation and gene therapy, neither conventional nor distributional (i.e., equity-weighted) cost-effectiveness is known. Accordingly, we conducted the first conventional and distributional cost-effectiveness analyses of allotransplantation therapy for pediatric patients with SCD in the United States. Methods: We built a Markov model of pediatric patients with sickle cell disease to examine the cost-effectiveness of allotransplantation vs gene therapy vs SOC and determine equity weight thresholds. Sex-, age-, and disease-severity-specific annual costs and transition probabilities across disease severities for SOC were informed by 11 years of data from US commercially insured patients with SCD (2007-2017; Optum). Disease severity was defined based on annual number of hospitalizations for vaso-occlusive crises, as defined in clinical trials. SOC included hydroxyurea, opioid therapy, antibiotics, vaccinations, and blood transfusions. Allotransplantation- and GVHD-specific transition probabilities and costs were informed by prior literature and health resource utilization data, originally reported from the Center for International Blood and Marrow Transplant Research and the Pediatric Health Information System. Quality-adjusted life-years (QALYs) were informed by published lifetime simulations of patients living with SCD and matched controls, derived initially from a polynomial fit linking Euroqual-5 Dimensions to the visual analog scale for pain in patients with SCD in several studies. Age-, sex- and disease-specific background mortality probabilities were employed. Conventional cost-effectiveness was quantified using an incremental cost-effectiveness ratio (ICER), at a willingness-to-pay threshold of $100,000/QALY. Given expert clinical experience with optimizing allotransplantation outcomes in SCD, we employed a maximum patient starting age of 12 and assumed that gene therapy cost $2.45 million and was 100% effective. To account for health inequities in SCD, we then conducted a distributional cost-effectiveness analysis (DCEA), which applies an inequality aversion parameter (i.e., how much weight one puts on reducing disparities), to the distribution of outcomes across relevant sub-groups for allotransplantation to be favored over SOC and justify funding per DCEA standards. These were compared to prior estimates for commonly used equity weights in the United States (range 0.5-3.0). Results: In the base-case, allotransplantation, gene therapy, and SOC accrued 22.1, 25.5, 15.7 discounted lifetime QALYs at costs of $1.9, $2.8, $1.0 million, respectively, with all therapies on the cost-effectiveness frontier (Table 1). The ICERs and equity weight thresholds were $138,000/QALY and 0.5, and $253,000/QALY and 4.5, for allotransplantation (vs SOC) and gene therapy (vs allotransplantation), respectively. Conclusion: Similar to findings for gene therapy versus SOC in the first published DCEA in sickle cell disease, allotransplantation also appears to be an equitable therapeutic option for pediatric patients with sickle cell disease, regardless of conventional cost-ineffectiveness and as compared to SOC. The consideration of patient-population-specific equity offers an important opportunity to derive transparent benchmarks for intertwined equity- and value-informed decision making. Quantitative consideration of equity in the context of conventional cost-ineffectiveness can be an important tipping point in justification of funding.

Distributional Cost-Effectiveness of Equity-Enhancing Gene Therapy in Sickle Cell Disease in the United States.

Gene therapy is a potential cure for sickle cell disease (SCD). Conventional cost-effectiveness analysis (CEA) does not capture the effects of treatments on disparities in SCD, but distributional CEA (DCEA) uses equity weights to incorporate these considerations. To compare gene therapy versus standard of care (SOC) in patients with SCD by using conventional CEA and DCEA. Markov model. Claims data and other published sources. Birth cohort of patients with SCD. Lifetime. U.S. health system. Gene therapy at age 12 years versus SOC. Incremental cost-effectiveness ratio (ICER) (in dollars per quality-adjusted life-years [QALYs] gained) and threshold inequality aversion parameter (equity weight). Gene therapy versus SOC for females yielded 25.5 versus 15.7 (males: 24.4 vs. 15.5) discounted lifetime QALYs at costs of $2.8 million and $1.0 million (males: $2.8 million and $1.2 million), respectively, with an ICER of $176 000 per QALY (full SCD population). The inequality aversion parameter would need to be 0.90 for the full SCD population for gene therapy to be preferred per DCEA standards. SOC was favored in 100.0% (females) and 87.1% (males) of 10 000 probabilistic iterations at a willingness-to-pay threshold of $100 000 per QALY. Gene therapy would need to cost less than $1.79 million to meet conventional CEA standards. Benchmark equity weights (as opposed to SCD-specific weights) were used to interpret DCEA results. Gene therapy is cost-ineffective per conventional CEA standards but can be an equitable therapeutic strategy for persons living with SCD in the United States per DCEA standards. Yale Bernard G. Forget Scholars Program and Bunker Endowment.

Comparing Income Distributions Using Atkinson's Measure of Inequality

AbstractThis article is aimed at undergraduate and graduate economics students, and public sector economists, who are interested in inequality measurement. It examines the use of the Atkinson inequality measure to compare income distributions. A major feature of this measure is that distributional value judgements are made explicit, via the use of a particular form of social welfare function. Emphasis is given to the interpretation of changes in inequality and the role of the relative inequality aversion parameter, which reflects an important feature of those value judgements.

Gene Therapy Equity in Sickle Cell Disease: Distributional Cost-Effectiveness Analysis (DCEA) of Gene Therapy Vs. Standard-of-Care in Patients with Sickle Cell Disease in the United States

Introduction: Patients with sickle cell disease (SCD) face substantial mortality risks and decreased quality-of-life for every year lived with disease. Once approved in the United States (US), gene therapy treatment for patients with SCD would allow the possibility of lifelong disease remission and, unlike allotransplantation, do so without the concomitant risks of allotransplantation. While gene therapy has previously been projected to be cost-ineffective using traditional cost-effectiveness criteria in the US, this does not include a quantification of the health disparities present in the clinical care of patients with SCD. We sought to address this knowledge gap by conducting the first distributional cost-effectiveness analysis, a method that quantifies the tradeoffs between traditional cost-effectiveness outcomes and health equity, for gene therapy use in SCD. Methods: We built and validated a Markov simulation model of patients with a diagnosis of mild, moderate, or severe SCD to examine the cost-effectiveness of gene therapy versus patients treated with standard-of-care (SOC). Gender-, age-, and disease-severity-specific annual costs and transition probabilities between disease severities were informed by ten years of real-world data from commercially insured patients in the United States with SCD (2007-2017; Optum claims data). Disease severity was defined based on annual number of hospitalizations and SOC was inclusive of hydroxyurea, opioid therapy, antibiotics, vaccinations, blood transfusions, and stem cell transplantation. Quality-adjusted life-years (QALYs) were informed by published lifetime simulation of patients living with SCD and matched controls. These were originally derived from a polynomial fit linking Euroqual-5 Dimensions to the visual analog scale for pain in patients with SCD in several studies. Age-, gender- and disease-specific background mortality probabilities were employed. Traditional cost-effectiveness was quantified using an incremental cost-effectiveness ratio (ICER) and a cost-effectiveness threshold of $100,000/QALY. Base-case gene therapy was assumed to cost $2.1 million based on other recently approved indications, be 100% effective in achieving disease remission, and applied to a minimum eligibility age of 12, as studied in randomized, controlled trials. To account for health inequities in SCD we then conducted a distributional cost-effectiveness analysis (DCEA), which applies an inequality aversion parameter (i.e., equity weight) to the distribution of outcomes across relevant sub-groups. Specifically, we derived the threshold inequality aversion parameters needed for gene therapy to be favored over SOC and justify funding per DCEA standards. These were compared to prior estimates for commonly used equity weights in the US (range 0.5-3.0) and the United Kingdom (UK) (11.0-28.9). Results: Base-case gene therapy versus SOC treatment starting at age 12 yields 25.5 versus 16.0 discounted lifetime QALYs at costs of $2.4 and $1.1 million, respectively. The ICER of $144,000/QALY is not good value for money using traditional cost-effectiveness methods and a cost-effectiveness threshold of $100,000/QALY. When using DCEA that account for health disparities in SCD, the inequality aversion parameter threshold is 1.7. This implies a preference for reducing disparities in SCD care that is in line with prior estimates in the US and well below those of the UK, per DCEA standards to favor gene therapy over SOC. A corresponding price range for gene therapy for SCD across the range of commonly used equity weights in the US is $1.4-$3.0 million (Figure 1). Conclusion: Gene therapy can be an equitable therapeutic strategy for patients with SCD in the United States despite a projected minimum cost of $2.1 million once approved, based on commonly-used equity weight values used in DCEA. Equitable gene therapy use would include expanding eligibility to include patients with mild and moderate disease severity, in addition to those with severe SCD, assuming similar therapeutic efficacy of gene therapy across disease severity. Rather than relying on ranges of commonly-used equity weights, nationally representative surveys should be fielded to empirically deriving an inequality aversion parameter value for addressing this SCD-specific health disparity to further help inform an equitable price benchmark for gene therapy in the US. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Optimal climate policies under fairness preferences

Integrated assessment models are tools largely used to investigate the benefit of reducing polluting emissions and limiting the anthropogenic mean temperature rise. However, they have been often criticized for their underlying assumptions, often leading to low levels of abatement. Countries and regions that are generally the actors in these models are usually depicted as having standard concave utility functions in consumption. This, however, disregards a potentially important aspect of environmental negotiations, namely its distributive implications. The present paper tries to fill this gap assuming that countries/regions have Fehr and Schmidt (The Quarterly Journal of Economics 114(3):817–868, 1999) (F&S) utility functions, specifically tailored for including inequality aversion. By adopting the RICE model, we compare its standard results with the ones obtained introducing F&S utility functions, showing that, under optimal cooperation, the level of temperature rise is lower in the last scenario. In particular, the peak temperature, reached in 2155 under standard assumptions and one or two decades later under F&S preferences with, respectively, heterogeneous and homogeneous F&S inequality aversion parameters (α and β), is of 2.86 ∘C in the former scenario and of 2.65 ∘C and 2.67 ∘C in the latter two. Furthermore, it is shown that potentially stable coalitions are easier to be achieved when F&S preferences are assumed. However, potentially stable coalitions are far from reaching environmental targets close to limiting the mean temperature rise below 2 ∘C despite the adoption of F&S utility functions. The 2 ∘C target is almost achieved in all scenarios when the payoffs in the F&S utility function are given by the per-capita consumption rather than utility of consumption, with F&S preferences and heterogeneous F&S inequality aversion parameters leading to a peak temperature rise of 2.04 ∘C.

Incorporating Concern for Health Equity Into Resource Allocation Decisions: Development of a Tool and Population-Based Valuation for Uganda

ObjectivesHealth economic analyses that simultaneously address the concerns of increasing population health and reducing health inequalities require information on public preferences for using healthcare resources to reduce health inequalities and how this is valued relative to improving total population health. Previous research has quantified this preference in the form of an inequality aversion parameter in a specified social welfare function. This study aimed to elicit general population’s views on health inequality and to estimate an inequality aversion parameter in Uganda. MethodsAdult respondents from the general population were recruited and interviewed using survey adapted from an existing questionnaire, including trade-off questions between 2 hypothetical healthcare programs. Data on participants’ demographic and socioeconomic characteristics and health-related quality of life measured by 5-level version of EQ-5D were collected. ResultsA nationally representative sample of 165 participants were included, with mean age of 37.1 years and mean 5-level version of EQ-5D at 0.836. Most respondents indicated willingness to trade-off some total population health to reduce health inequality. Translating the preferences into an Atkinson inequality aversion parameter (14.70) implies that health gain to the poorest 20% of people should be given approximately 6 times the weight of health gains to the richest 20%. ConclusionsOur study suggests it is feasible to adapt questionnaires of this type for a Ugandan population and this approach could be used to measure public aversion to health inequality in other settings. The elicited inequality aversion parameter can be used to support the assessment of health inequality impact in economic evaluation in Uganda.

Minimizing inequality in the financing of Argentina’s pension system: Modelling three scenarios

AbstractOne mechanism for influencing income redistribution through a pension system is to incorporate non‐contributory financing. Using mathematic modelling tools, this study compares two arrangements for financing Argentina’s pension system that emerged from an optimization exercise. One arrangement permits financing through income tax and the other does not. The former is found to be preferable in terms of equality and proves robust to changes in the investment rate and the inequality aversion parameter. The use of mathematical modelling tools by decision‐makers with access to sufficient high‐quality data would allow for a credible assessment of the extent to which a particular parametric reform might (or might not) contribute to improved income distribution.

Inequality and human development: How inclusive the growth is in Uttar Pradesh?

PurposeThe present research has been conceptualized to make an inter-district analysis in terms of IHDI of Uttar Pradesh. It aims to provide district-wise estimates of HDI and IHDI with the latest available data, which may prove to be a critical policy input to the policy makers that how different districts are performing in terms of education, health and standard of living parameters and help in implementing tailor made policy actions.Design/methodology/approachThe paper utilizes the Census of India data and unit-level data of National Sample Survey (NSS) for constructing HDI and IHDI. The broad framework for computing IHDI in this study is similar to the approach of UNDP's HDR 2010. To adjust the inequality aspect, the Atkinson inequality aversion parameter has been estimated at indicator level on the basis of NSS unit record data.FindingsThe study reveals that inequality discounted income index is on an average 30 percent lower than unadjusted income index. However, quite high variation exists in case of education and health. The difference ranges from 30 percent to 40 percent in the case of education and from 3 to 36 percent in the health dimension. The surprising fact which study finds that health infrastructure and education infrastructure are poorly correlated with their respective outcomes.Research limitations/implicationsThe study offers a policy suggestion that increasing investment on educational and health infrastructure will not have any significant impact on their respective outcomes unless distributional inequalities are reduced. The study also suggests that rising income inequalities are threat to inclusive growth and sustainable development goals agenda. Thus, it recommends policy makers to take pro-active timely policy measures to reduce income inequalities. The educational achievement should be fixed in terms of average years of schooling and expected years of schooling rather than in terms of literacy rate.Originality/valueThe present research is an original work. This is the first study in the case of Uttar Pradesh which attempted to estimate district-wise IHDI following the internationally accepted UNDP (2010) methodology.

Measuring well-being dispersion on discrete rating scales

Average levels of well-being across countries and time periods have been reported widely over the years as one of the measures that go beyond the Gross Domestic Product. It is relevant for policy makers to also have information on well-being dispersion to identify groups that lag behind with respect to their ability to pursue happiness. In addition, there is an inherent moral appeal to not only maximize wellbeing but also equalize well-being among people. In this paper, we try to answer the following research question: which measure(s) should be used to gain insight into wellbeing dispersion? We review sixteen measures and their properties, study their behavior in over 92 thousand simulated distributions, and apply them to 4 years of the Dutch Social Cohesion and Well-Being Survey, using bootstrapping to quantify their precision. Our inventory shows that when applied to a discrete ordinal rating scale, common measures such as the standard deviation and Gini coefficient do not show any advantage over the less restrictive index of ordinal variation (IOV). Only the generalized entropy and Atkinson index adhere to additional principles, most notably of diminishing transfers, at the expense of full scale invariance. The simulation study illustrates that dispersion measures are positively correlated but do not rank distributions the same. The field study shows that only the Atkinson index with high inequality aversion provides additional insight. We recommend using the index of ordinal variation, supplemented if needed with the Atkinson index using a high value for the inequality aversion parameter.

Combining Microsimulation and Optimization to Identify Optimal Flexible Tax-Transfer Rules

We use a behavioural microsimulation model embedded in a numerical optimization procedure in order to identify optimal (social welfare maximizing) tax-transfer rules. We consider the class of tax-transfer rules consisting of a universal basic income and a tax defined by a 4th degree polynomial. The rule is applied to total taxable household income. A microeconometric model of household, which simulates household labour supply decisions, is embedded into a numerical routine in order to identify – within the class defined above – the tax-transfer rule that maximizes a social welfare function. We present the results for five European countries: France, Italy, Luxembourg, Spain and United Kingdom. For most values of the inequality aversion parameter, the optimized rules provide a higher social welfare than the current rule, with the exception of Luxembourg. In France, Italy and Luxembourg the optimized rules are significantly different from the current ones and are close to a Negative Income Tax or a Universal basic income with a flat tax rate. In Spain and the UK, the optimized rules are instead close to the current rule. With the exception of Spain, the optimal rules are slightly disequalizing and the social welfare gains are due to efficiency gains. Nonetheless, the poverty gap index tends to be lower under the optimized regime.

The Contribution of Increased Equity to the Estimated Social Benefits from a Transfer Program: An Illustration from PROGRESA/Oportunidades

Abstract Most impact evaluations of Conditional Cash Transfers (CCTs) and Unconditional Cash Transfers (UCTs) focus on the returns to increased human capital investments that will be reaped largely or exclusively in the future (e.g., when current children have increased productivities as adults). But the objectives of these programs are not only to increase human capital investments with implications for future levels and distributions of income but also to alleviate current poverty and reduce current inequality. The current distributional gains from such programs depend on the degree of inequality aversion in the social welfare function. Simulations show that, for a range of inequality aversion parameters, the welfare gains from current redistribution for the Mexican PROGRESA CCT program can be as large, or possibly much larger, than the estimated present discounted value of future earnings from human capital investments in lower and upper secondary schooling. These, moreover, are underestimates of the gains from redistribution because, in addition to current gains, such gains will be augmented in the future through the distribution of the returns on the human capital investments induced by cash transfer programs. Therefore, to fully evaluate such programs, it is critical to incorporate the distributional gains, not only the impacts on human capital investments.

Novel Approaches to Value Assessment Within the Cost-Effectiveness Framework

Novel Approaches to Value Assessment Within the Cost-Effectiveness Framework

Analysis Equity in Financing of Household's Health in Iran ( by Concentration and Extended Concentration Index)

Health status of societies is among the basic indices of economic and social development and hence, investment in this section directly impacts on social welfare and economic growth. Low quality of health care and inequality in health care expenditure contributions can lead to different forms of social and economic consequences. This is the main concern of the public policy makers, in particular those who are engaged with health care services. Hence, monitoring households' health expenditures, which can reflect socio-economic inequality, can provide valuable information for the health policy makers.The concentration index and the extended concentration index introduced by Wgstaff (2002) is used to estimate inequality in health expenditures of urban households. Also, the household’s expenditures in Iran are disaggregated into expenditure quintiles through selected years from 1989 (i.e. beginning of the development programs in Iran after the revolution) till 2014. To this end, Iran’s annual household’s survey data produced by Iran statistic center is used. The concentration index has upward trend in 1989 to 2005, and after that it has fluctuating trend. Fifth quintile has the highest income inequality and the most inequality in health expenditures, because there are some households with high health expenditures in this group; while they are not rich in fact. The extended concentration index has been light fluctuation in the selected years. Increasing the extended concentration index represents the increasing inequalities in health expenditures, so increase in this indicator is a sign of the worsening health situation in the country. Despite of the improvements in some key health indices such as the rate of maternal mortality, the under five years mortality, life expectancy of women and men, the findings of this study shows that the households' expenditure inequality increases in favor of the higher income groups, and on the other, the public policy in health has not been effective as expected. Moreover, the results of the study indicates that higher degree of inequality aversion parameter, the lower disparity between the average households' health expenditures and its average at the "perfect equality". This result shows that the capability of the individuals, and particularly the lower income groups, has been weakened.

Aggregate Distributional Cost-Effectiveness Analysis of Health Technologies

BackgroundHealth inequalities can be partially addressed through the range of treatments funded by health systems. Nevertheless, although health technology assessment agencies assess the overall balance of health benefits and costs, no quantitative assessment of health inequality impact is consistently undertaken. ObjectivesTo assess the inequality impact of technologies recommended under the NICE single technology appraisal process from 2012 to 2014 using an aggregate distributional cost-effectiveness framework. MethodsData on health benefits, costs, and patient populations were extracted from the NICE website. Benefits for each technology were distributed to social groups using the observed socioeconomic distribution of hospital utilization for the targeted disease. Inequality measures and estimates of cost-effectiveness were compared using the health inequality impact plane and combined using social welfare indices. ResultsTwenty-seven interventions were evaluated. Fourteen interventions were estimated to increase population health and reduce health inequality, 8 to reduce population health and increase health inequality, and 5 to increase health and increase health inequality. Among the latter 5, social welfare analysis, using inequality aversion parameters reflecting high concern for inequality, indicated that the health gain outweighs the negative health inequality impact. ConclusionsThe methods proposed offer a way of estimating the health inequality impacts of new health technologies. The methods do not allow for differences in technology-specific utilization and health benefits, but require less resources and data than conducting full distributional cost-effectiveness analysis. They can provide useful quantitative information to help policy makers consider how far new technologies are likely to reduce or increase health inequalities.

E-learning and health inequality aversion: A questionnaire experiment.

In principle, questionnaire data on public views about hypothetical trade‐offs between improving total health and reducing health inequality can provide useful normative health inequality aversion parameter benchmarks for policymakers faced with real trade‐offs of this kind. However, trade‐off questions can be hard to understand, and one standard type of question finds that a high proportion of respondents—sometimes a majority—appear to give exclusive priority to reducing health inequality. We developed and tested two e‐learning interventions designed to help respondents understand this question more completely. The interventions were a video animation, exposing respondents to rival points of view, and a spreadsheet‐based questionnaire that provided feedback on implied trade‐offs. We found large effects of both interventions in reducing the proportion of respondents giving exclusive priority to reducing health inequality, though the median responses still implied a high degree of health inequality aversion and—unlike the video—the spreadsheet‐based intervention introduced a substantial new minority of non‐egalitarian responses. E‐learning may introduce as well as avoid biases but merits further research and may be useful in other questionnaire studies involving trade‐offs between conflicting values.

Inference Procedures to Quantify the Efficiency-Equality Trade-Off in Health from Stated Preferences: A Case Study in Portugal.

This article develops two inference procedures to calculate the inequality aversion and alpha parameters of a health-related social welfare function with constant elasticity (CES-HRSWF) using stated preferences. Based on the relative concept of inequality, a range of values were proposed for the trade-offs between improving total population health and reducing health inequalities. A self-administered questionnaire was used to collect data from a sample of 422 college students in Portugal. Respondents faced three hypothetical allocation scenarios where they needed to decide between two health programmes that assign different health gains to two anonymous sub-groups of the population and to two sub-groups identified by socioeconomic class. Combinations of the median response to these three questions were used to estimate the parameters of the CES-HRSWF. Findings suggest that the quantification of the efficiency-equality trade-off is not independent of the inference procedure used. Plausible values for the inequality aversion and for the alpha parameters were obtained ranging from 2.24 to 4.85 and from 0.5 to 0.58, respectively. Respondents revealed some aversion to health inequality. However, the extent of this aversion seems to be sensitive to (1) the identification of the groups by occupation status, (2) the size of the health gain, and (3) the inference procedure used.

Income inequality measurement: a fresh look at two old issues

The literature on income inequality measurement is split into (1) the ethical approach, from which the Atkinson–Kolm–Sen and Kolm–Pollak classes of indices are derived, and (2) the axiomatic approach, which mainly leads to the generalised entropies. This paper shows how to rationalise, under utilitarianism, the generalised entropies as ethical indices. In this framework a generalised entropy index is consistent with the principle of transfers if and only if the underlying utility function is increasing. This unconventional interpretation explains the strange behaviour of the generalised entropies for some values of the inequality aversion parameter, as identified by Shorrocks (Econometrica 48:613–625, 1980). In that case, the underlying utility function is convex. Then, it provides a solution to escape the so-called Hansson–Sen paradox (Hansson in Foundational problems in the special sciences. Reidel Publishing Company, Dordrecht, 1977; Sen in Personal income distribution. North-Holland, Amsterdam, pp 81–94, 1978) that affects the standard ethical indices and which corresponds to a counterintuitive increase in inequality as a result of a concave transformation of the utility function. A normalised version of the generalised entropies behaves appropriately after such a transformation.

Distributional cost-effectiveness analysis in low- and middle-income countries: illustrative example of rotavirus vaccination in Ethiopia.

Reducing health inequality is a major policy concern for low- and middle-income countries (LMICs) on the path to universal health coverage. However, health inequality impacts are rarely quantified in cost-effectiveness analyses of health programmes. Distributional cost-effectiveness analysis (DCEA) is a method developed to analyse the expected social distributions of costs and health benefits, and the potential trade-offs that may exist between maximising total health and reducing health inequality. This is the first paper to show how DCEA can be applied in LMICs. Using the introduction of rotavirus vaccination in Ethiopia as an illustrative example, we analyse a hypothetical re-designed vaccination programme, which invests additional resources into vaccine delivery in rural areas, and compare this with the standard programme currently implemented in Ethiopia. We show that the re-designed programme has an incremental cost-effectiveness ratio of US$69 per health-adjusted life year (HALY) compared with the standard programme. This is potentially cost-ineffective when compared with current estimates of health opportunity cost in Ethiopia. However, rural populations are typically less wealthy than urban populations and experience poorer lifetime health. Prioritising such populations can thus be seen as being equitable. We analyse the trade-off between cost-effectiveness and equity using the Atkinson inequality aversion parameter, ε, representing the decision maker's strength of concern for reducing health inequality. We find that the more equitable programme would be considered worthwhile by a decision maker whose inequality concern is greater than ε = 5.66, which at current levels of health inequality in Ethiopia implies that health gains are weighted at least 3.86 times more highly in the poorest compared with the richest wealth quintile group. We explore the sensitivity of this conclusion to a range of assumptions and cost-per-HALY threshold values, to illustrate how DCEA can inform the thinking of decision makers and stakeholders about health equity trade-offs.