Use Of Economic Models Research Articles

Agricultural policies and food systems: Priorities for indicator development

AbstractExisting indicators of agricultural protection and support were developed primarily to gauge the market and welfare effects of government policies. They have shed light on a wider range of impacts through their use in economic models and empirical analysis. The rising scale of support to agriculture globally, and continued reliance on market distorting policy instruments, make this work as important as ever. Deeper investments are nonetheless needed to address heightened concerns about the spill‐over impacts of agricultural policies on the performance of food systems, in particular with respect to food security and nutrition, rural livelihoods, resource use and the environment, and global emissions. A first area for development is improved measures of policies to correct agriculture's externalities. A priority here is to develop a carbon tax equivalent of sectoral mitigation efforts. A second area is to provide a clearer delineation of government spending on private versus public goods. This would make a valuable contribution to a ‘repurposing’ agenda that seeks to identify how agricultural budgets can be spent more effectively, as well as the scope for transferring resources to wider social priorities, such as public health and climate action.

Globalization and the Australian Professional Standards for Teachers

Globalization has been perceived as a major source of influence in education in general and the work of teachers in particular (Stier, 2004). This paper sets out to discuss the impacts of globalization on teacher standards and teachers’ practices in the context of Australia by raising two key arguments. First, globalization has led the Australian teacher standards to be developed in a way that emphasizes the need for global competitiveness, and consequently influenced teachers’ work through the use of economic models including accountability and evidence-based practices. Second, globalization has highlighted the importance of digital literacy in teacher standards, and as a result promoted teachers’ real-life practices of digital technologies integration in the classroom. The paper concludes with several implications in terms of research and practice. Keywords: Australian professional standards for teachers , globalization, teacher standards DOI: 10.7176/JEP/13-17-11 Publication date: June 30 th 2022

POSA262 The Use of Akaike Information Criterion and Bayesian Information Criterion Rules of Thumb in Nice Oncology Appraisals: A Targeted Review

NICE Decision Support Unit’s Technical Support Document 14 (2011) recommends using Akaike information criterion (AIC) and Bayesian information criterion (BIC) to assess the statistical fit of parametric survival models to observed data for use in economic models. However, the document includes no clear guidance on interpretation of AIC and BIC values aside from the lowest AIC and BIC being the best statistical fit, despite “rules of thumb” for categorising models according to relative statistic fit versus the distribution with the lowest AIC and BIC being available in the literature.

Payer perceptions on the use of economic models in oncology decision making.

BACKGROUND: To support oncology formulary decisions, especially with accelerated regulatory approvals and niche populations, payers desire data beyond what regulators review. Economic models showing financial impact of treatments may help, but data on payers' use of economic models in oncology are limited. OBJECTIVE: To assess payer perceptions regarding use of economic models in informing oncology formulary decisions. METHODS: A multidisciplinary steering committee involving health economists and payers developed a survey containing singleanswer, multiple-answer, and free-response questions. The pilot survey was tested at a mini-advisory board with 5 US payers and revised based on feedback. In February 2020, the survey was distributed to 221 US payers through the AMCP Market Insights program and 10 additional payer panelists, who were invited to discuss survey results. Results were presented primarily as frequencies of responses and evaluated by plan size, type of health plan, and geography (regional vs national). Differences in categorical data responses were compared using Pearson chi-square or Fisher's exact tests. Two-tailed values were reported and an alpha level of 0.05 or less was used to indicate statistical significance. RESULTS: Overall, 106 of 231 payers completed the survey (45.9%); 45.5% represented small plans (< 1 million lives), and 54.5% represented large plans (≥ 1 million lives). Respondents were largely pharmacists (89.9%), and 55.6% indicated that their job was pharmacy administrator. Payers indicated moderate/most interest in cost-effectiveness models (CEMs; 85.3%) and budget impact models (BIMs; 80.4%). Overall, 51.6% of respondents claimed oncology expertise on their pharmacy and therapeutics committees. Large plans were more likely to have expertise in reviewing oncology economic models than small plans (55.6% vs 31.1%, P = 0.015). The most common reasons for not reviewing economic models included "not available at time of review" (44.1%) and "potential bias" (38.2%). Overall, 43.1% of payers conduct analyses using their own data after reviewing a manufacturer-sponsored economic model. To inform formulary decisions, 62.7% of payers use BIMs and 66.7% use CEMs sometimes, often, or always. When comparing therapies with similar safety/efficacy profiles, 68.6% of payers reported economic models as helpful a moderate amount, a lot, or a great deal. Over one-third of payers (37.3%) were willing to partner with manufacturers on economic models using their plans' data. Payers valued preapproval information, data on total cost of care, and early access to models. Concerns remained regarding model transparency and assumptions. CONCLUSIONS: Most US payers reported interest in using economic models to inform oncology formulary decision making. Opportunities exist to educate payers in assessing economic models, especially among small health plans. Ensuring model availability at launch, transparency in model assumptions, and payer-manufacturer partnership in model development may increase the utility of oncology economic models among US payers. DISCLOSURES: Pfizer provided funding for this research, and Pfizer employees led the development of the survey instrument, were involved in the analysis and interpretation of the data, and contributed to the manuscript as authors. Arondekar and Niyazov are employed by Pfizer. Biskupiak, Oderda, and Brixner are managers of Millcreek Outcomes Group and were paid as consultants on this project. Burgoyne was a consultant for Pfizer on this project.

Captives of Capital? Exploring economic models as recursive and performative agents

The financial sector could play a more significant and transformative role in supporting the energy transition. Portraying techno-economic models, upon which the sector depends for the support of its investment decisions, as performative or self-fulfilling agents which serve only to entrench the hegemony of the present incumbents, undermines the potential for using these approaches to accelerate the energy transition. In this article, we outline the role of capital markets in the energy transition and show how techno-economic modelling has attracted a growing interest from authors within the renewable energy sector. We summarise the concerns of social scientists about economic modelling, neatly captured by its depiction as a calculative agency intent on its self-replication. We argue that there is a need to align the two perspectives, especially as a means of strengthening the support of the financial sector for the energy transition, and suggest several ways in which this alignment could be achieved. Important research questions include further exploration of the recursive and performative relationship between economic models and the economy, the inclusion of externalities in modelling studies, the use of economic models as agents of change rather than recalcitrance, and finally strengthening capital markets in the Global South.

PRO67 The Use of Vignettes to Derive Health Utilities for Spinal Muscular Atrophy Type I (SMA-I)

Spinal muscular atrophy type I (SMA-I) is a rare genetic condition usually diagnosed before 6 months of age. Health utilities are required to evaluate the economic impact of treatments for SMA-I. However, it is impossible for these to be derived directly from affected children. The aim of this study was to derive SMA-I health utilities via vignettes. Participants were presented with 4 vignettes describing SMA-I health states that differed in levels of severity: 1. Permanent Assisted Ventilation (PAV); 2. Non-sitting; 3. Sitting; and 4. Walking. Participants were asked to imagine themselves as parents to a child with SMA. For each vignette participants first determined whether the state was worse than death (WTD) using a visual analogue scale (VAS) (range: -100 to 100). Health state utilities were then captured using time trade-off (TTO) and standard gamble (SG). Task wording was varied depending on whether the state was rated WTD. The study was completed online with a representative sample of the UK adult population. 321 participants completed the study (age: 18-65; 49.7% females). Mean health state utilities for TTO were: -0.0243 [PAV, 95% confidence interval: -0.0914, 0.0428]; -0.0264 [Non-sitting, -0.0966, 0.0438]; 0.0977 [Sitting, 0.0291, 0.1664]; 0.3844 [Walking, 0.3225, 0.4463]. For the SG: 0.0028 [-0.0611, 0.0677], 0.0139 [-0.0505, 0.0783], 0.0946 [0.0302, 0.1591] and 0.3782 [0.3176, 0.4388]. The least severe health state (“Walking”) differed significantly from the other three states (p<0.0001). Mean utilities were not statistically significant for the worst 2 health states. Mean health state utilities differed in line with severity of SMA-I. Although participants were not able to discriminate between the two worst health states, this, and the relatively low spread between mean utilities reflect the severity of SMA. These results contribute to a growing body of utility data for use in economic models of SMA treatments.

Evaluation of a Heart Failure Telemonitoring Program Through a Microsimulation Model: Cost-Utility Analysis.

BackgroundHeart failure (HF) is a major public health issue in Canada that is associated with high prevalence, morbidity, and mortality rates and high financial and social burdens. Telemonitoring (TM) has been shown to improve all-cause mortality and hospitalization rates in patients with HF. The Medly program is a TM intervention integrated as standard of care at a large Canadian academic hospital for ambulatory patients with HF that has been found to improve patient outcomes. However, the cost-effectiveness of the Medly program is yet to be determined.ObjectiveThis study aims to conduct a cost-utility analysis of the Medly program compared with the standard of care for HF in Ontario, Canada, from the perspective of the public health care payer.MethodsUsing a microsimulation model, individual patient data were simulated over a 25-year time horizon to compare the costs and quality-adjusted life years (QALYs) between the Medly program and standard care for patients with HF treated in the ambulatory care setting. Data were sourced from a Medly Program Evaluation study and literature to inform model parameters, such as Medly’s effectiveness in reducing mortality and hospitalizations, health care and intervention costs, and model transition probabilities. Scenario analyses were conducted in relation to HF severity and TM deployment models. One-way deterministic effectiveness analysis and probabilistic sensitivity analysis were performed to explore the impact on the results of uncertainty in model parameters.ResultsThe Medly program was associated with an average total cost of Can $102,508 (US $77,626) per patient and total QALYs of 5.51 per patient compared with the average cost of Can $97,497 (US $73,831) and QALYs of 4.95 per patient in the Standard Care Group. This led to an incremental cost of Can $5011 (US $3794) and incremental QALY of 0.566, resulting in an incremental cost-effectiveness ratio of Can $8850 (US $6701)/QALY. Cost-effectiveness improved in relation to patients with advanced HF and with deployment models in which patients used their own equipment. Baseline and alternative scenarios consistently showed probabilities of cost-effectiveness greater than 85% at a willingness-to-pay threshold of Can $50,000 (US $37,718). Although the results showed some sensitivity to assumptions about effectiveness parameters, the intervention was found to remain cost-effective.ConclusionsThe Medly program for patients with HF is cost-effective compared with standard care using commonly reported willingness-to-pay thresholds. This study provides evidence for decision makers on the use of TM for HF, supports the use of a nurse-led model of TM that embeds clinically validated algorithms, and informs the use of economic modeling for future evaluations of early-stage health informatics technology.

Why we need a European focus on foodborne parasites

Foodborne parasites (FBP) are recognized as being a neglected pathogen group, often associated with marginalized or disadvantaged populations, especially those living in regions where water supply or sanitation are inadequate. Nevertheless, we are also increasingly recognising that FBP are not just restricted to such places, and even those that do have a circumscribed endemic area may also travel further in our globalised world; FBP are relevant everywhere, including Europe.Against this background, COST Action Euro-FBP (FA1408) was established and ran for a period of 4 years, addressing a number of different questions related to FBP, particularly in the European setting. In this special issue (SI), some of the issues and outputs associated with Euro-FBP are considered in greater depth, as an output also of the final Euro-FBP meeting. As well as more general issues regarding, for example, globalization and climate change, use of economic models, and the value of risk-based surveillance that puts the topic in perspective, individual articles are included that address specific parasites. These include protozoan parasites, such as Cryptosporidium, Giardia, and Toxoplasma, as contaminants of water, shellfish, and fresh produce, fishborne parasites such as Anisakid nematodes, and meatborne parasites, such as Trichinella. Some of the works provide specific data on occurrence or outbreaks, whilst others are concerned with techniques. In addition, implementation of some of the educational and collaborative tools that are unique to COST Actions are described. COST Actions are not generally intended to deliver a scientific endpoint, and Euro-FBP does not do so. However, the articles in this SI, along with other articles published elsewhere during and subsequent to the course of the Action, as direct outputs of the Euro-FBP activities, indicate that FBP are indeed a relevant topic for European scientists.

The Value of Behavioral Economics for EU Judicial Decision-Making

AbstractThis Article analyzes the value of behavioral economics for EU judicial decision-making. The first part introduces the foundations of behavioral economics by focusing on cognitive illusions, prospect theory, and the underlying distinction between different processes of thought. The second part examines the influence of selected biases and heuristics, namely the anchoring effect, availability bias, zero-risk bias, and hindsight bias on diverse legal issues in EU law including, among others, the scope of the fundamental freedoms, the proportionality test as well as the roles of the Advocate General and Reporting Judge. The Article outlines how behavioral economic findings can be taken into account to improve judicial decision-making. Accordingly, the adaptation of judicial training concerning cognitive illusions, the establishment of a de minimis rule regarding the scope of the fundamental freedoms, and the use of economic models when determining the impact of certain measures on fundamental freedoms is suggested. Finally, an “unbiased jury” concentrating exclusively on specific factual issues such as causal connections within the proportionality test is necessary, if the hindsight bias is to be avoided. While it is of great importance to take behavioral economic findings into account, judicial decision-making is unlikely to become flawless based on natural intelligence. Despite bearing fundamental risks, artificial intelligence may provide means to achieve greater fairness, consistency, and legal certainty in the future.

Economic models used in consequential life cycle assessment: a literature review

Abstract The construction sector is a key actor for achieving the sustainable development goals, particularly from an environmental point of view, due to the significant sector's contribution to energy consumption, greenhouse gas and pollutants emissions, waste generation, resources depletion etc. Life Cycle Assessment (LCA) is a multi-criteria tool to assess environmental impacts, preventing the impact transferring from one life cycle stage to another and thus is widely used to support decision-making. Consequential LCA (CLCA) can be particularly relevant for decisions involving non-marginal changes and may have an important role in supporting decision-makers of the construction sector by giving a wider comprehension of the environmental impacts associated with the changes caused by their decisions. Particularly when assessing large-scale consequences, it is recommended to couple an economic model to the CLCA methodology to assess the changes in the background system. Therefore, this research aims at reviewing the CLCA works applied to the construction sector and the use of economic models in CLCA for assessing non-marginal changes. For that, the review is divided in two parts: the first reviews the CLCA works and papers in the construction sector; and the second part reviews CLCA studies that assess non-marginal changes, regardless the activity or sector.

Longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials

BackgroundCost-effectiveness analyses in patients with migraine require estimates of patients’ utility values and how these relate to monthly migraine days (MMDs). This analysis examined four different modelling approaches to assess utility values as a function of MMDs.MethodsDisease-specific patient-reported outcomes from three erenumab clinical studies (two in episodic migraine [NCT02456740 and NCT02483585] and one in chronic migraine [NCT02066415]) were mapped to the 5-dimension EuroQol questionnaire (EQ-5D) as a function of the Migraine-Specific Quality of Life Questionnaire (MSQ) and the Headache Impact Test (HIT-6™) using published algorithms. The mapped utility values were used to estimate generic, preference-based utility values suitable for use in economic models. Four models were assessed to explain utility values as a function of MMDs: a linear mixed effects model with restricted maximum likelihood (REML), a fractional response model with logit link, a fractional response model with probit link and a beta regression model.ResultsAll models tested showed very similar fittings. Root mean squared errors were similar in the four models assessed (0.115, 0.114, 0.114 and 0.114, for the linear mixed effect model with REML, fractional response model with logit link, fractional response model with probit link and beta regression model respectively), when mapped from MSQ. Mean absolute errors for the four models tested were also similar when mapped from MSQ (0.085, 0.086, 0.085 and 0.085) and HIT-6 and (0.087, 0.088, 0.088 and 0.089) for the linear mixed effect model with REML, fractional response model with logit link, fractional response model with probit link and beta regression model, respectively.ConclusionsThis analysis describes the assessment of longitudinal approaches in modelling utility values and the four models proposed fitted the observed data well. Mapped utility values for patients treated with erenumab were generally higher than those for individuals treated with placebo with equivalent number of MMDs. Linking patient utility values to MMDs allows utility estimates for different levels of MMD to be predicted, for use in economic evaluations of preventive therapies.Trial registrationClinicalTrials.gov numbers of the trials used in this study: STRIVE, NCT02456740 (registered May 14, 2015), ARISE, NCT02483585 (registered June 12, 2015) and NCT02066415 (registered Feb 17, 2014).

Reply to “Research incentives and research output”: a caution on quantity incentives and the use of economic models for higher education policy

Using an economic model of academic behaviour, Jorgensenn and Hanssen (Higher Education, 76, 1029–1049, 2018) find that a research incentive based on pages of output would not compromise research quality. Given that quantity is more easily observable, they suggest that such an incentive may have merit as an actual policy. This finding of the economic modelling exercise is shown to rest on an inadequate representation of the policy problem: once the policymaker’s resource trade-off is accounted for, the result fails to hold. A number of other findings and assumptions are critically examined, along with the problematic conflation of findings and assumptions. These concerns raise the broader matter of the merit of using formal economic models to inform higher education policy. A number of reasons are provided to substantiate the view that such models are likely to be inappropriate for this purpose and any policy proposals derived in this fashion ought to be treated with considerable caution.

The ‘curse of dimensionality’ resolved: The effects of climate change and trade barriers in large dimensional modelling

Solving large scale optimisation problems over space and time quickly generates a computational impasse, termed the ‘curse of dimensionality’. This severely limits the practical use of economic models, especially for determining the effects of climate change and protectionist trade policies. In this paper, we employ an innovative approach to solving (otherwise unsolvable) large scale systems through the use of parallel processing methods and a proper ordering of variables and equations in a ‘Nested Doubly Bordered Block Diagonal’ form. We illustrate how the approach can be used to solve an intertemporal CGE model with more than 500 million equations. Using existing damage functions, the framework allows us to determine the impact of climate change on long-run economic growth for 112 countries as a result of the effect of sea-level rise on land endowments, variation in crop yields and productivity and shifts in the demand for energy and transportation. We also compare our solution to more common (and smaller dimensional) recursive methods, in terms of both the economic effects of climate change and potential increases in trade barriers, showing the power and efficiency of our computational approach and parallel processing routine.

The Application of the Global Economic Crisis Smash Effect Simulator (GECSE-Simulator): China, ASEAN, Japan, and EU

This paper proposes the uses of the global economic crisis smash effect simulator as a theoretical framework to evaluate the final effects of any global financial crisis on the world economy. We present different scenarios and results according to different levels of devastation that the global financial crisis can generate on the world economy. It is based on the evaluation of unemployment and worldwide poverty dissemination. The global economic crisis smash effect simulator requires the use of economic modeling in real time and multi-dimensional economic modeling to visualize different scenarios and evaluate the final impact of any global financial crisis.

Health State Utilities Associated with Attributes of Weekly Injection Devices and Subdermal Implant for Treatment of Type 2 Diabetes

Cost-utility analyses include health utilities to compare medical treatments. Health utilities, ranging from 0 to 1, represent the strength of a patient’s preference for a drug profile or health-related outcome. Recently glucagon-like peptide-1 (GLP-1) receptor agonists have been used for management of glycemic control in type 2 diabetes (T2DM). Many GLP-1 drugs have similar modes of administration. In contrast, ITCA 650 is an investigational product which is an implantable device that, following subdermal placement, provides continuous delivery of exenatide for 3 or 6 months. The study’s purpose was to estimate health utilities associated with treatment processes of GLP-1s for use in economic models. During a UK-based pilot study, 19 general population (general population) participants completed time trade-off (TTO) interviews to value health states (often called vignettes or scenarios) which were based on literature review, instructions for use, and clinician interviews. A follow-up pilot study was conducted in both general population and T2DM participants to value modified health states. Participants were recruited to ensure equal distribution across gender and education levels. A total of 20 general population and 18 T2DM patients completed face-to-face interviews (general population mean age= 50.7; T2DM mean age = 56.2). Mean utilities (SD) for ITCA-650 were 0.93 (0.06) for T2DM patients and 0.91 (0.11) for the general population. Mean utility scores for injection health states ranged from 0.83-0.92 for T2DM and 0.82-0.91 for general population. Results are higher than others found in the literature for diabetes treatment processes (range: 0.85 to 0.88). A main study with 200 participants will be conducted in early 2018. Results may be useful in cost-utility models comparing the value of treatment processes for patients with T2DM. Findings suggest the TTO method may be used to quantify preferences among different treatment processes. Disclosure A.M. Rentz: Other Relationship; Self; Intarcia Therapeutics, Inc., Servier. K. Cutts: None. K. Washington: None. M. Beillat: None. K. Yu-Isenberg: Employee; Self; Intarcia Therapeutics, Inc..

Can land value uplift deliver affordable housing? Experiences from England

Purpose The theoretical case for land value capture is well-known, but the effectiveness of affordable housing delivery as a capture mechanism is not so well-documented. Building on the earlier theoretical and empirical work of Whitehead (1991, 2007) and Crook and Whitehead (2002), the purpose of this paper is to consider the provision of affordable housing from a land value capture viewpoint, focusing on the process by which the amount of affordable housing is determined between landowners/developers on the one hand and local planning authorities on the other. Design/methodology/approach The paper adopts a mixed-mode approach for the data collection. Two surveys of local planning authorities were undertaken, together with a series of case study interviews. Findings The paper evaluates whether land value capture has been an effective mechanism for delivering affordable housing by focusing on three principal areas: first, the political agenda in relation to land value capture and the supply of affordable housing; second, the nature and motivation of the stakeholders involved in affordable housing decision-making; and third, the use of economic models as decision tools for determining the amount and type of affordable housing are negotiated. Originality/value The research provides some insight into the effectiveness of local authority affordable housing targets as a means of capturing the uplift in land value that results from the grant of planning permission.

PRM88 - Estimating Patient Utility in Migraine: Longitudinal Analysis of Erenumab Clinical Trial Data

Migraine is a debilitating disease with substantial impact on patients’ health-related quality of life (HRQoL). Cost-utility analysis of migraine preventives requires the estimation of patient utility values and how these relate to monthly migraine days (MMD). The objective of this analysis is to model utility values in a longitudinal framework, allowing more accurate estimates of expected utility values. Data from two pivotal erenumab studies in episodic migraine (EM; NCT02456740) and chronic migraine (CM; NCT02066415) were pooled to analyze HRQoL outcomes. Migraine Specific Questionnaire (MSQ) version 2.1 and Headache Impact Test (HIT-6) condition-specific instruments were mapped to the EQ-5D using published mapping algorithms (Gillard et al. 2012) to generate generic, preference-based utility estimates, suitable for use in economic models. Longitudinal non-linear beta regressions were fitted between mapped EQ-5D utility values, MMD and treatment group (erenumab 140mg and placebo), adjusting for age, sex, race and baseline MMD in the various time periods considered. Expected utility values by MMD were calculated using the Delta method. Multilevel linear models and fractional response models with probit and logit links were also assessed. The analysis sample included data from 1,113 patients; 83.7% females with a mean age of 41.6 years. The longitudinal beta regression models closely approximated the observed utility values. Patients with 14 MMD were predicted to have MSQ mapped mean utility values of 0.608 (95% CI: 0.595–0.621) for patients treated with erenumab 140mg and 0.590 (0.577–0.602) for patients receiving placebo. The respective predicted HIT-6 mapped mean utility values were 0.698 (0.654–0.741) and 0.659 (0.629–0.689). Mapped utility values for erenumab patients were consistently higher than placebo patients with the same number of MMD. Linking patient QoL to MMD allows utility estimates for different levels of MMD to be predicted, for use in economic evaluations of preventive therapies.

Sustainability and the financial system Review of literature 2015

AbstractMuch actuarial work is underpinned by the use of economic models derived from mainstream academic theories of finance and economics which treat money as being a neutral medium of exchange. The sustainability of a financial system whose understanding is based on a limited view of the role of money has increasingly been subject to criticism. In order to identify needed research programmes to address such criticisms and improve these disciplines, we sought to understand the current state of knowledge in economics and finance concerning the link between monetary and financial factors and sustainability. We have approached this through a search for relevant literature published in the highest-rated academic journals in economics, finance and the social sciences for titles and abstracts containing both references to the financial system on the one hand, and sustainability and environmental factors on the other. The systematic search of a universe of 125 journals and 355,000 articles yielded the finding that surprisingly few research papers jointly address these concepts. Nevertheless, we find that current research shares a broad consensus that the implications of the growth-oriented economic model results in an increasingly interconnected and fragile financial system whose participants are not incentivised to fully recognise the natural environment and resource constraints. We further observe that the prescriptions offered are relatively limited and small-scale in their outlook and that there is a vital need for further research, particularly for actuaries who are required to take a longer-term outlook. The Resource and Environment Board has supported this work with two key objectives: first, to identify research that may have direct application to actuarial work and, second, to identify gaps in academic research that would help drive the Institute and Faculty of Actuaries’ own research agenda. With this in mind there are three further areas of potential actuarial research. These are the policy aim of pursuing growth without limit within a finite ecosystem; discount factors as the primary means of capital allocation and investment decisions; and the use of gross domestic product as the key metric of economic activity and success. We also conclude that further academic research is urgently needed to understand the sustainability of the banking and monetary system.

The Role of Condition-Specific Preference-Based Measures in Health Technology Assessment.

A condition-specific preference-based measure (CSPBM) is a measure of health-related quality of life (HRQOL) that is specific to a certain condition or disease and that can be used to obtain the quality adjustment weight of the quality-adjusted life-year (QALY) for use in economic models. This article provides an overview of the role and the development of CSPBMs, and presents a description of existing CSPBMs in the literature. The article also provides an overview of the psychometric properties of CSPBMs in comparison with generic preference-based measures (generic PBMs), and considers the advantages and disadvantages of CSPBMs in comparison with generic PBMs. CSPBMs typically include dimensions that are important for that condition but may not be important across all patient groups. There are a large number of CSPBMs across a wide range of conditions, and these vary from covering a wide range of dimensions to more symptomatic or uni-dimensional measures. Psychometric evidence is limited but suggests that CSPBMs offer an advantage in more accurate measurement of milder health states. The mean change and standard deviation can differ for CSPBMs and generic PBMs, and this may impact on incremental cost-effectiveness ratios. CSPBMs have a useful role in HTA where a generic PBM is not appropriate, sensitive or responsive. However, due to issues of comparability across different patient groups and interventions, their usage in health technology assessment is often limited to conditions where it is inappropriate to use a generic PBM or sensitivity analyses.

The ‘Curse of Dimensionality’ Resolved: The Effects of Climate Change and Trade Barriers in Large Dimensional Modelling

Solving large scale optimisation problems over space and time quickly generates a computational impasse, termed the ‘curse of dimensionality’. This severely limits the practical use of economic models, especially for determining the effects of climate change and protectionist trade policies. In this paper, we employ an innovative approach to solving (otherwise unsolvable) large scale systems through the use of parallel processing methods and a proper ordering of variables and equations in a ‘Nested Doubly Bordered Block Diagonal’ form. We illustrate how the approach can be used to solve an intertemporal CGE model with more than 500 million equations. Using existing damage functions, the framework allows us to determine the impact of climate change on long-run economic growth for 112 countries as a result of the effect of sea-level rise on land endowments, variation in crop yields and productivity and shifts in the demand for energy and transportation. We also compare our solution to more common (and smaller dimensional) recursive methods, in terms of both the economic effects of climate change and potential increases in trade barriers, showing the power and efficiency of our computational approach and parallel processing routine.