Equity Weights Research Articles

Equity weighting increases valuations when using real-world data

Environmental economists have long debated whether and how to appropriately integrate distributional concerns into cost benefit analysis. Recent White House guidance instructs U.S. government analysts to weight different groups’ costs and benefits according to their incomes. Groups with incomes below the median would have weights above one, while groups with incomes above the median would have weights below one. We explore the impact of this method. We find that the average weight is above one in a policy-relevant setting. In this example, weighting increases the magnitude of monetized costs and benefits. The average weight varies with the unit of analysis and the choice of unit of analysis can change the sign of the net benefits.

Socioeconomic distributional impacts of evaluating flood mitigation activities using equity-weighted benefit-cost analysis

As the global impact of climate change intensifies, there is an urgent need for equitable and efficient climate adaptation policies. Traditional approaches for allocating public resources for climate adaptation that are based on economic benefit-cost analysis often overlook the resulting distributional inequalities. In this study, we apply equity weightings to mitigate the distributional inequalities in two key building and household level adaptation strategies under changing coastal flood hazards: property buyouts and building retrofit in New York City (NYC). Under a mid-range emissions scenario, we find that unweighted benefit cost ratios applied to residential buildings are higher for richer and non-disadvantaged census tracts in NYC. The integration of income-based equity weights alters this correlation effect, which has the potential to shift investment in mitigation towards poorer and disadvantaged census tracts. This alteration is sensitive to the value of elasticity of marginal utility, the key parameter used to calculate the equity weight. Higher values of elasticity of marginal utility increase benefits for disadvantaged communities but reduce the overall economic benefits from investments, highlighting the trade-offs in incorporating equity into adaptation planning.

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 & 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.

A Formal Framework For Incorporating Equity Into Health Care Quality Measurement.

Quality measurement is an important tool for incentivizing improvement in the quality of health care. Most quality measurement efforts do not explicitly target health equity. Although some measurement approaches may intend to realign incentives to focus quality improvement efforts on underserved groups, the extent to which they accomplish this goal is understudied. We posit that tying incentives to approaches on the basis of stratification or disparities may have unintended consequences or limited effects. Such approaches might not reduce existing disparities because addressing one aspect of equity may be in competition with addressing others. We propose equity weighting, a new measurement framework to advance equity on multiple fronts that addresses the shortcomings of existing approaches and explicitly calibrates incentives to align with equity goals. We use colorectal cancer screening data derived from 2017 Medicare claims to illustrate how equity weighting fixes unintended consequences in other methods and how it can be adapted to policy goals.

Can Independently Elicited Adult- and Child-Perspective Health-State Utilities Explain Priority Setting?

ObjectivesTime trade-off (TTO) utilities for EQ-5D-Y-3L health states valued by adults taking a child’s perspective are generally higher than their valuations of the same state for themselves. Ceteris paribus, the use of these utilities in economic evaluation implies that children gain less from treatments returning them to full health for a specified amount of time than adults. In this study, we explore if this implication affects individuals’ views of priority-setting choices between treatments for adults and children. MethodsWe elicited TTO utilities for 4 health states in online interviews, in which respondents valued states for a 10-year-old child and another adult their age. Views on priority setting were studied with person trade-off (PTO) tasks involving the same health states. We tested the ability of the subjects’ TTO utilities to predict these societal choices in PTO. ResultsThere are no significant differences between adult and child health state valuations in our study, but we do observe a substantial preference for treating children over adults in the PTO task. ConclusionsOur findings suggest that perspective-dependent health-state utilities only explain a small part of views on priority setting between adults and children. External equity weights might be useful to better explain the higher priority given to children.

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.

The Broader Opportunity Costs in the Broader Cost-Effectiveness Analysis Framework.

The traditional cost-effectiveness analysis framework usually takes a healthcare system perspective, where the aim is to maximise population health from a fixed budget allocated to healthcare. Extensions to this framework have been suggested, including: (i) incorporating impacts that fall outside the healthcare sector; (ii) accounting for outcomes beyond health; and (iii) assessing equity considerations. Several alternatives have been proposed that serve these purposes, for example, the extended "impact inventory", the "beyond-the-QALY" approach and the distributional cost-effectiveness analysis. This paper aims to develop a comprehensive framework that incorporates into the cost-effectiveness analysis framework some of its most advocated extensions and provides a means of arriving at a unidimensional cost-effectiveness analysis result measure. Building on previous work, I proposed a framework that explicitly incorporates the full extent of the opportunity costs that arise when new dimensions and distributional concerns are included in cost-effectiveness analyses. A hypothetical example is provided as a way of illustration. Operationalising the proposed framework requires system-wide representative values and/or robust estimates concerning: (i) selecting dimensions; (ii) measuring opportunity costs associated with each dimension; (iii) quantifying equity weights and percentages of beneficiaries and losers meeting equity considerations; and (iv) attaching monetary values to dimensions measured using a non-monetary metric. Extending the cost-effectiveness analysis framework entails extending the measurement of the opportunity costs of funding decisions. This implies populating an ambitious puzzle that in some cases poses fundamental conceptual and empirical questions. Potential routes of further research that might facilitate such undertaking are proposed.

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

Inconsistent Risk Profiles within Pan-European Private Banks: Insufficient Transparency for Retail Investors

The Markets in Financial Instruments Directive (MiFID) must protect retail investors and increase risk transparency. To disclose and mitigate investment risks effectively, banks use standardized risk profiles. Through a scenario-based case study, we demonstrate that based on future risk-adjusted returns and volatility, these risk profiles of pan-European private banks significantly differ. Even though MiFID is not subject to bandwidth restrictions, differences could interfere with risk transparency and lead to significant differences in future risk, return, and managed expectations of clients due to profile overlap. This article uses the risk profiles of twelve pan-European private banks. We found significant non-equality among three rebalancing strategies: buy-and-hold, yearly rebalancing, and bandwidth rebalancing. The impact of broader bandwidths in the rebalancing strategy results in a significantly higher risk and return for investors due to greater flexibility in equity weights. Consequently, this article presents inconsistencies in private banks’ risk profiles. Future regulations should address and reconstitute guidelines to mitigate risk discrepancies. The difference in risk and return within the pan-European private banks creates a lack of transparency and does not contribute to investor protection envisaged by MiFID.

Equity-oriented integrated optimization of train timetable and stop plans for suburban railways system

In the suburban railway system, when oversaturation occurs in the railway line or the train skips the same station continuously, passengers waiting at different stations may receive a varying share of train resources. As a result, some passengers have to endure a very long waiting time, causing issues of inequity. Thus, this paper focuses on improving the system-wide equity performance through integrated optimization of the train timetable and stop plan while ensuring travel efficiency and cost rationality. As a part of the study, a novel equation to estimate equity performance by considering the difference in passenger travel utility is developed. Then, an integrated optimization model combining the train timetable and stop plan is proposed to minimize total travel time, train running time, and equity performance. Unlike other studies in the literature, this paper does not define any initial set of stopping plans, and synchronously optimizes the train timetable and stops the plan. This facilitates obtaining better solutions by expanding the solution space. Furthermore, it overcomes the NP-hardness of the investigated problem by using the adaptive large-scale neighborhood search (ALNS) algorithm to solve the multi-objective mixed-integer linear programming model. Finally, this paper discusses the original and optimized scheduling indicators of a real-world case based on the Shanghai Jinshan railway and performs a sensitivity analysis on equity weights. The results show that the proposed approach can improve the overall benefits of efficiency, cost, and equity by 23%. Specifically, in terms of equity, the passenger travel utility variance was reduced by 42.8%. This analysis provides essential information to railway managers in formulating the train operation plan.

To weigh or not to weigh. Recommendations for communicating aggregated results of buildings LCA

Interpreting contradictory results of multiple midpoint environmental indicators is challenging task. Hence, partial or full aggregation into building single scores has gained ground for the clear message they convey. This paper helps to improve understanding of the possibilities and limitations of such practice. Partial aggregated scores of five buildings were explored, limited to the environmental indicators shared by the methods examined and inventoried for the case studies. In general, the buildings’ single score ranking was maintained regardless of the aggregation approach, but rank reversal is possible if e.g., ecotoxicity impact indicators are considered. Such indicators are directly influenced by the mass of metals used in a building. Furthermore, uncertainties on their results, in LCI data and in impact and damage assessment are high, and experience with them is still limited. No single best aggregation stands out per se. All of them can play their part if officially supported to ensure that coherent weights/factors are built upon solid, up-to-date data and fair intergenerational and income equity valuation procedures. In such cases, LCA practitioners are encouraged to use single scores in addition to environmental profiles or selected indicators. Overall aggregation procedures shall be transparently described, and zero pure time preference rate and equity weighting applied and explicitly declared. Sensitivity/uncertainty analysis shall be performed to assess results robustness, potential ranking reversal risks, and the effect of different discount rates. When partial aggregation is alternatively pursued, it shall be based on endpoint categories.

Risk-based benefit-cost analysis of ecosystem-based disaster risk reduction with considerations of co-benefits, equity, and sustainability

Ecosystem-based disaster risk reduction (Eco-DRR) measures are gaining attention as creative solutions to reduce community vulnerability against risks while providing multiple co-benefits. We evaluate an Eco-DRR, an afforestation effort, Boca de Sapo (hereafter, BdS), in a marginalized community in peri-urban Lima where we perform household surveys and key informant interviews. To estimate the economic viability, we design a benefit-cost analysis (BCA) and include probabilistically estimated DRR benefits and place-based economic and non-market co-benefits representing stakeholder values. Accounting for income differences, we incorporate equity weights to estimate social welfare benefits. We then evaluate BdS impacts based on BCA results and stakeholder responses along broader sustainability dimensions, and benchmark the project's contribution to urban sustainability using two international frameworks. Household surveys revealed high concern for rockfall risk, and a double-bounded contingent valuation indicated an average household willingness to pay (WTP) of $3.44 ± 0.49/month for BdS maintenance. The equity-weighted risk-based BCA using Monte Carlo simulations indicated BdS was unviable considering DRR benefits with a Benefit-Cost Ratio (BCR) of 0.06 ± 0.08. BCR estimates increased to 1.18 ± 0.42 with incremental integration of tangible property rights co-benefits, and to 1.70 ± 0.59 with addition of WTP representing non-market co-benefits. Our findings demonstrate that inclusion of the multiple Eco-DRR place-based, socio-cultural, and ecological co-benefits with primary DRR benefits is critical as they generate substantial wellbeing impacts for communities. Adapting a sustainability lens revealed holistic Eco-DRR outcomes including access to public green spaces, social inclusion, stronger resource governance, and health and wellbeing benefits, highlighting areas for improvement and pathways for adaptive governance.

Social cost of carbon under a carbon-neutral pathway

Climate change is the challenge of the century, and achieving the goals of the Paris Agreement will require worldwide cooperation and mutual effort. Over 120 countries have made their net-zero commitments, and quantifying the social cost of carbon (SCC), i.e. the climate damage caused by an additional ton of CO2 emissions, under a carbon-neutral pathway would provide a carbon price benchmark for policymakers. Here, we set in detail the emission trajectories of different jurisdictions under a carbon-neutral pathway based on the submitted nationally determined contributions. We then assess global and regional warming, climate change damages, and the SCC with the Policy Analysis of Greenhouse Effect integrated assessment model. We find a peak warming of about 2.1 °C relatives to pre-industrial levels in this century under our carbon-neutral emission pathway. And even if all countries meet their carbon-neutral commitments, this would not be sufficient to limit global warming to 1.5 °C relative to pre-industrial levels. We compare the SCC using fixed discount rates, dynamic discounting, and an equity weighting approach. Notably, the introduction of equity weights would increase the estimated SCC from 79 (11–186) to 291 (83–592) US$ per tCO2. Climate change damages will be borne primarily by warmer and poorer countries, and this profound inequality would likely undermine efforts to eradicate extreme poverty. Statistics on current carbon taxes and carbon trading prices show that they are notably lower than global or even regional SCCs, suggesting that the current system does not adequately reflect the global externalities of CO2 emissions. More studies are needed to assess the equity aspects of climate change impacts, to help refine mechanisms to align domestic interests with global interests, and to facilitate the implementation of national carbon-neutral commitments in place.

Health Impacts of Climate Change as Contained in Economic Models Estimating the Social Cost of Carbon Dioxide.

The health impacts of climate change are substantial and represent a primary motivating factor to mitigate climate change. However, the health impacts in economic models that estimate the social cost of carbon dioxide (SC‐CO2) have generally been made in isolation from health experts and have never been rigorously evaluated. Version 3.10 of the Framework for Uncertainty, Negotiation and Distribution (FUND) model was used to estimate the health‐based portion of current SC‐CO2 estimates across low‐, middle‐, and high‐income regions. In addition to the base model, three additional experiments assessed the sensitivity of these estimates to changes in the socio‐economic assumptions in the model. Economic impacts from adverse health outcomes represent ∼8.7% of current SC‐CO2 estimates. The majority of these health impacts (74%) were attributable to diarrhea mortality (from both low‐ and high‐income regions) followed by diarrhea morbidity (12%) and malaria mortality (11%); no other health impact makes a meaningful contribution to SC‐CO2 estimates in current economic models. The results of the socio‐economic experiments show that the health‐based portion of SC‐CO2 estimates are highly sensitive to assumptions regarding income elasticity of health effects, income growth, and use of equity weights. Improving the health‐based portion of SC‐CO2 estimates could have substantial impacts on magnitude of the SC‐CO2. Incorporating additional health impacts not previously included in estimates of SC‐CO2 will be a critical component of model updates. This effort will be most successful through coordination between economists and health researchers and should focus on updating the form and function of concentration‐response functions.

Willingness to Pay for Health-Related Quality of Life Gains in Relation to Disease Severity and the Age of Patients

ObjectivesDecision-making frameworks that draw on economic evaluations increasingly use equity weights to facilitate a more equitable and fair allocation of healthcare resources. These weights can be attached to health gains or reflected in the monetary threshold against which the incremental cost-effectiveness ratios of (new) health technologies are evaluated. Currently applied weights are based on different definitions of disease severity and do not account for age-related preferences in society. However, age has been shown to be an important equity-relevant characteristic. This study examines the willingness to pay (WTP) for health-related quality of life (QOL) gains in relation to the disease severity and age of patients, and the outcome of the disease. MethodsWe obtained WTP estimates by applying contingent-valuation tasks in a representative sample of the public in The Netherlands (n = 2023). We applied random-effects generalized least squares regression models to estimate the effect of patients’ disease severity and age, size of QOL gains, disease outcome (full recovery/death 1 year after falling ill), and respondent characteristics on the WTP. ResultsRespondents’ WTP was higher for more severely ill and younger patients and for larger-sized QOL gains, but lower for patients who died. However, the relations were nonlinear and context dependent. Respondents with a lower age, who were male, had a higher household income, and a higher QOL stated a higher WTP for QOL gains. ConclusionsOur results suggest that—if the aim is to align resource-allocation decisions in healthcare with societal preferences—currently applied equity weights do not suffice.

Modifying NICE's Approach to Equity Weighting.

The UK's National Institute for Health and Care Excellence (NICE) recently launched a consultation on the methods it uses to evaluate new health technologies, and has highlighted the issue of how 'modifiers', including equity weights, should be incorporated into its processes. The practice of applying equity weights to specific population subgroups, as a means for increasing the effective cost-effectiveness threshold for some new health technologies, is well established in health technology assessment. It is also the subject of extensive discussion in the academic literature. In this paper, we demonstrate that NICE's current approach to equity weighting has the effect of reducing both population health and equity-weighted population health, a fundamental problem that appears to place NICE in contravention of its principles and obligations. We consider two potential methods for modifying NICE's current approach to address this problem. We also consider the merits of NICE abandoning its current approach to equity weighting and adopting a standard 'net benefit' approach in its place. We find that adopting a standard 'net benefit' approach is the most desirable option, as it provides for the most transparency while avoiding specific issues that arise when attempting to modify NICE's current approach. Regardless of the approach NICE uses for equity weighting, we find that protecting the health of National Health Service patients requires that some new technologies be evaluated using an effective cost-effectiveness threshold lower than the 'supply-side' cost-effectiveness threshold. This poses a particular challenge for NICE, given its obligations under the 2019 'Voluntary Scheme' between the UK pharmaceutical industry, the National Health Service, and the UK Government. We conclude by making some recommendations as to how NICE can move forward with the use of 'modifiers' in its decision making.

Rationing, racism and justice: advancing the debate around ‘colourblind’ COVID-19 ventilator allocation

Withholding or withdrawing life-saving ventilators can become necessary when resources are insufficient. In the USA, such rationing has unique social justice dimensions. Structural elements of dominant allocation frameworks simultaneously advantage...

Risk Aversion, Inequality and Economic Evaluation of Flood Damages: A Case Study in Ecuador

While floods and other natural disasters affect hundreds of millions of people globally every year, a shared methodological approach on which to ground impact valuations is still missing. Standard Cost-Benefit Analyses typically evaluate damages by summing individuals’ monetary equivalents, without taking into account income distribution and risk aversion. We propose an empirical application of alternative valuation approaches developed in recent literature, including equity weights and risk premium multipliers, to a case study in Ecuador. The results show that accounting for inequality may substantially alter the conclusions of a standard vulnerability approach, with important consequences for policy choices pertaining damage compensation and prioritization of intervention areas.

Effects of Asset Allocation on Financial Performance of Unit Trust Schemes in Kenya

Abstract Unit Trust Schemes provide diversification, liquidity, professional management among other benefits. In order to diversify the funds raised from various unit holders, fund managers adopt a criterion with which funds are allocated optimally. A descriptive research design was adopted, and the study period was 5-years. The ratio of the composition of different asset classes to the fund value was used as the independent variables. Fund age was used as the control variable. Sharpe ratio was used to measure investment returns and that represented the dependent variable of the study. Data was collected from secondary sources and a multiple linear regression model was adopted to assess the association of the variables. Collected data showed normality traits, positive autocorrelation when measured using Pearson correlation coefficients. The data also showed mixed results for multicollinearity tests. The weight of money market instruments, corporate bonds, treasury bonds and equity significantly affected performance of Unit Trust Scheme funds. They all had probability values in the interval of 0 and 0.05. Therefore, the study concluded that asset allocation significantly affects how a fund will perform. Other factors such as timing, manager experience and prevailing economic conditions have to be considered when evaluating performance of a fund. Keywords: Asset allocation, Financial performance, Unit trust schemes, Kenya.