The Load Model: an alternative to QALY

Background: QALYs are widely used in health economic evaluation, but remain controversial, largely because they do not reflect how many people behave in practice. This paper presents a new conceptual model (Load Model) and illustrates it in comparison with the QALY model.

Methods: Load is the average annual weight attributed to morbidity and mortality over a defined period, using weightings based on preference judgements. Morbidity Load is attributed to states of illness, according to their perceived severity. When people are in full health, Load is zero (no morbidity). Death is treated as an event with negative consequences, incurred in the year following death. Deaths may be weighted equally, with a fixed negative weight such as ?100, or differ according to the context of death. After death, Load is zero. In a worked example, we use the standard gamble method to obtain a weighting for an illness state, for both Load and QALY models. A judge is indifferent between certainty of 1.5 years’ illness followed by death, or a 50/50 chance of 1.5 years’ full health or 1-year illness, each followed by death. The weightings calculated are applied to a hypothetical life, 72 years in full health followed by 3 years with illness then death, using both models. Three other hypothetical outcomes are also compared.

Results: For an example life, the relative size of the morbidity component compared with the mortality component is much higher in the Load model than in the QALY model. When comparing alternative outcomes, there are also substantial differences between the two models.

Conclusions: In the Load model the weight of morbidity, relative to mortality, is very different from that in the QALY model. Given the role of the QALYs in economic evaluation, the implications of an alternative, which generates very different results, warrant further exploration.     

Beyond the Optimistic Curse: A New Multiscenario Approach to Debt Sustainability Assessment

While a careful and accurate debt sustainability assessment (DSA) is crucial for an efficient macroeconomic management, the most widely used framework introduced by the International Monetary Fund (IMF) suffers from several drawbacks that render its results overoptimistic and misleading. In this article, we correct the methodology by demonstrating how policy makers can develop country-specific “intermediate” forecasts of the determinants of debt dynamics, in addition to coherent “optimistic” and “pessimistic” scenarios. Our application to the case of Egypt illustrates that the debt-to-GDP ratio could increase to more than 100 percent by 2015, in contrast with the 61 percent projected by the IMF in 2010.     

On estimating long-run effects in models with lagged dependent variables

A common procedure in economics is to estimate long-run effects from models with lagged dependent variables. For example, macro panel studies frequently are concerned with estimating the long-run impacts of fiscal policy, international aid, or foreign investment.Our analysis points out the hazards of this practice. We use Monte Carlo experiments to demonstrate that estimating long-run impacts from dynamic models produces unreliable results.Biases can be substantial, sample ranges very wide, and hypothesis tests can be rendered useless in realistic data environments. There are three reasons for this poor performance. First, OLS estimates of the coefficient of a lagged dependent variable are downwardly biased in finite samples. Second, small biases in the estimate of the lagged, dependent variable coefficient are magnified in the calculation of long-run effects. And third, and perhaps most importantly, the statistical distribution associated with estimates of the LRP is complicated, heavy-tailed, and difficult to use for hypothesis testing. While many of the underlying problems have been long-known in the literature, the continued widespread use of the associated empirical procedures suggests that researchers are unaware of the extent and severity of the estimation problems. This study aims to illustrate their practical importance for applied research.     

基于Q币的网络虚拟币属性与影响分析

Q币目前并不是货币,但具有一定的货币属性与功能,如有限度的流通性,相对的价值尺度职能,一定程度的支付手段等。就Q币的特征而言,Q币与法定货币之间存在着很大的差异,Q币不能代替人民币的作用。但虚拟币的无限创造能力成为潜在的不稳定因素,中央银行难以有效控制货币供给,可能危及我国的金融安全。我国应严厉打击倒卖Q币的行为,加强对Q币等网络虚拟币的金融监管,建立更安全便捷的支付渠道。     

Regulators’ and stakeholders’ perspectives in a framework for bioenergy development

In this study, ten bioenergy crop rotations (corn, corn-stover, sorghum, soybean, corn-soybean, corn-soybean-canola, corn-stover-soybean, miscanthus, switchgrass, and sorghum-soybean) were selected based on local stakeholder (economically motivated) and regulator (environmentally motivated) preferences. These crops were implemented on diverse landscapes (agricultural, marginal, and agricultural plus marginal lands) one at time for 17 years using a SWAT model of the Saginaw River Watershed in Michigan. The bioenergy crops were evaluated based on 100 percent, 50 percent, and zero percent weight assigned to both stakeholders’ and regulators’ preferences using analytic hierarchy process (AHP), an optimization and decision-making technique that aims to satisfy multiple conflicting objectives. The corn-soybean-canola rotation was selected in all landscapes based on economic benefits (stakeholders’ preferences). Meanwhile, perennial grasses (miscanthus and switchgrass) were selected based on environmental benefits (regulators’ preferences), because they maintain permanent cover, require fewer inputs than traditional row crops, and are less management intensive. When implementing bioenergy crops on marginal lands, pollution generation greatly increased at the field level, indicating that these lands are likely not viable for bioenergy crop production to meet potential future renewable energy demand.     

Progress in indicators to assess agricultural landscape valuation: how and what is measured at different levels of governance

Landscape is defined by the European Landscape Convention as “an area perceived by people, whose character is the result of the action and interaction of natural and/or human factors”. Many efforts have been devoted in addressing the core concepts on which this definition roots: perception and interaction of men and nature, but when coming to large (continental) scale assessments, the latter prevail on the former.This paper aims at presenting a framework for a measurable landscape awareness indicator as a key link to the public demand for a specific type of landscape: the agricultural landscape. This is a necessary effort to complement more physically based assessments, which include as well the impact of human activities on landscapes.The analysis is carried out at different levels of governance: EU and regional, using an example from the Alentejo region in Portugal and EU wide databases, and addresses conceptual and practical questions: what type of societal landscape awareness can be monitored and by whom (e.g., individuals, specific social groups, society as a whole); what are the landscape dimensions that should be assessed; what are the limitations imposed by data-related constraints. By applying the methodology to build composite indicators to map landscape societal awareness, the paper shows the regional and local meaning of indicator approaches developed at European level, presents developments for downscaling to regional level, while introducing the social component to support sound policy development for European rural landscapes.     

基于结构方程模型的集聚农户共生认知及影响因素分析:以重庆市为例

研究目的:探讨对集聚农户共生、集聚区土地利用率提高的影响因素,为提升农户共生的认知水平、优化农户共生关系及促进资源的节约集约利用提供有效路径及理论指导。研究方法:参与式农户调查,结构方程模型。研究结果:(1)户主自身特征、农户家庭特征、集聚共生效益特征及外部环境与政策特征这4类外源潜变量对农户共生认知产生重要影响且影响程度大小不同,其中,集聚共生效益特征的影响最为显著,外部环境与政策特征、户主自身特征和农户家庭特征的影响依次减弱;(2)是否为干部、对原集聚模式的满意度、是否促进农户生产生活条件和政府对集聚区的补贴力度分别对这4类外源潜变量具有较好的解释能力。研究结论:显化农户共生效益、增强"精英"农户及村干部的正向引导、提升农户成员受教育水平、培养农户"共生共荣"理念等是深化农户共生关系,促进和谐乡村人居环境建设的重要路径。     

国际碳基金经营风险管理的经验与启示

当前，国际碳基金运营体系日趋成熟。本文总结了国际碳基金在治理运营模式、风险评价、风险控制与项目退出四个方面的运营经验；并结合实际，提出了中国进一步发展碳基金的建议。     

Are EU trade preferences really effective? An impact evaluation assessment of the Southern Mediterranean Countries’ case

This work assesses the causal impact of the EU trade preferences granted to the Southern Mediterranean Countries (SMCs) in agriculture and fishery products over the period 2004–2014. It overcomes some of the weaknesses of previous assessments and presents several methodological improvements. Firstly, it relies on a continuous treatment – i.e. preferential margins – to capture the ‘average treatment effect’ of trade preferences, rather than on a binary treatment based on dummy variables. Secondly, it uses highly disaggregated data at sectoral level in order to evaluate properly the preferential treatment. Thirdly, it applies a non-parametric matching technique for continuous treatment – specifically, a generalized propensity score matching. The results show, on the one hand, that the impact of the EU preferences is positive and significant on SMCs trade and is better evaluated using impact evaluation techniques. On the other hand, they demonstrate that the relationship between preferences and trade flows is asymmetric and warn against the risk of providing too much of a good thing. These results raise important issues for policy-making. First, they demonstrate that raising the level of preferences is not the solution to foster the SMCs trade towards EU. Second, that the policy-makers should put more emphasis on complementary factors other than trade barriers.     

Multi-scale integrated analysis of rural Laos: Studying metabolic patterns of land uses across different levels and scales

This paper presents an application of the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach to the analysis of rural land uses. Using secondary data on farming systems in Laos, we illustrate how the concept of metabolic pattern can be used to establish links between the various indicators of performance of rural systems. To this purpose, we characterize the socioeconomic activities in rural Laos by a series of quantitative indicators defined across: (i) different hierarchical levels of organization described at different scales (i.e. households, rural villages, administrative regions and the whole country) and (ii) different dimensions of analysis, including economic, agronomic, social, biophysical, and ecological analysis. The MuSIASEM approach simultaneously employs two non-equivalent criteria for quantification. The observed rural system is described in terms of an integrated set of flow elements (money, food, energy, water, fertilizer and other materials), which are mapped against two distinct fund elements: (i) a multi-level matrix of human activity (flows being expressed in terms of intensity per hour) and (ii) a multi-level matrix of land uses (flows being expressed as density per hectare). Our case study shows that in this way it is possible to move across different hierarchical levels, scales and dimensions, to arrive at an integrated representation of the metabolic pattern of farming systems.