Economic Modelers Research Articles

The PHEM-B toolbox of methods for incorporating the influences on Behaviour into Public Health Economic Models

BackgroundIt is challenging to predict long-term outcomes of interventions without understanding how they work. Health economic models of public health interventions often do not incorporate the many determinants of individual and population behaviours that influence long term effectiveness. The aim of this paper is to draw on psychology, sociology, behavioural economics, complexity science and health economics to: (a) develop a toolbox of methods for incorporating the influences on behaviour into public health economic models (PHEM-B); and (b) set out a research agenda for health economic modellers and behavioural/ social scientists to further advance methods to better inform public health policy decisions.MethodsA core multidisciplinary group developed a preliminary toolbox from a published review of the literature and tested this conceptually using a case study of a diabetes prevention simulation. The core group was augmented by a much wider group that covered a broader range of multidisciplinary expertise. We used a consensus method to gain agreement of the PHEM-B toolbox. This included a one-day workshop and subsequent reviews of the toolbox.ResultsThe PHEM-B toolbox sets out 12 methods which can be used in different combinations to incorporate influences on behaviours into public health economic models: collaborations between modellers and behavioural scientists, literature reviewing, application of the Behaviour Change Intervention Ontology, systems mapping, agent-based modelling, differential equation modelling, social network analysis, geographical information systems, discrete event simulation, theory-informed statistical and econometric analyses, expert elicitation, and qualitative research/process tracing. For each method, we provide a description with key references, an expert consensus on the circumstances when they could be used, and the resources required.ConclusionsThis is the first attempt to rigorously and coherently propose methods to incorporate the influences on behaviour into health economic models of public health interventions. It may not always be feasible or necessary to model the influences on behaviour explicitly, but it is essential to develop an understanding of the key influences. Changing behaviour and maintaining that behaviour change could have different influences; thus, there could be benefits in modelling these separately. Future research is needed to develop, collaboratively with behavioural scientists, a suite of more robust health economic models of health-related behaviours, reported transparently, including coding, which would allow model reuse and adaptation.

Multibenchmark reality checks

Empirical economic modelers often have to choose between two classes of models, with each class containing multiple models. In many cases, this decision is based on the predictive ability of the considered models. This entails that multiple testing and/or p-hacking pose known risks. This study presents a new statistical approach for comparing all model in a single test, serving as a multi-benchmark reality check test. The behavior of the test is studied asymptotically and in small finite samples. We show how the new approach works by analyzing whether one family of linear bivariate models outperforms a univariate family in predicting commodity prices. This paper raises new questions for future research. From an empirical viewpoint, we present several open questions in economic modeling that can be tested with multi-benchmark tests. Meanwhile, from a theoretical viewpoint, further studies can investigate whether a more general method for approximating or simulating the test distribution can be developed.

Simplified Methods for Modelling Dependent Parameters in Health Economic Evaluations: A Tutorial.

In health economic evaluations, model parameters are often dependent on other model parameters. Although methods exist to simulate multivariate normal (MVN) distribution data and estimate transition probabilities in Markov models while considering competing risks, they are technically challenging for health economic modellers to implement. This tutorial introduces easily implementable applications for handling dependent parameters in modelling. Analytical proofs and proposed simplified methods for handling dependent parameters in typical health economic modelling scenarios are provided, and implementation of these methods are illustrated in seven examples along with the SAS and R code. Methods to quantify the covariance and correlation coefficients of correlated variables based on published summary statistics and generation of MVN distribution data are demonstrated using examples of physician visits data and cost component data. The use of univariate normal distribution data instead of MVN distribution data to capture population heterogeneity is illustrated based on the results from multiple regression models with linear predictors, and two examples are provided (linear fixed-effects model and Cox proportional hazards model). A conditional probability method is introduced to handle two or more state transitions in a single Markov model cycle and applied in examples of one- and two-way state transitions. This tutorial proposes an extension of routinely used methods along with several examples. These simplified methods may be easily applied by health economic modellers with varied statistical backgrounds.

Abandon the idea of an “optimal economic path” for climate policy

AbstractMany economic modelers believe that there is an “optimal economic path” for solving the climate problem that exists independent of human choices. This belief rests on the notion that Integrated Assessment Models can determine the path that “maximizes global welfare” and, in turn, this path should drive climate policy. This commentary focuses on an under‐appreciated problem with that belief. We argue that the existence of pervasive increasing returns to scale, network externalities, learning curves, spillovers, and other nonlinear effects puts the idea of a single optimal economic path at odds with our current understanding of the most important forces driving the development of real economic and technological systems. We further argue that this idea is detrimental to rigorous understanding of climate solutions.This article is categorized under: Assessing Impacts of Climate Change > Scenario Development and Application Climate Economics > Economics and Climate Change Climate Economics > Economics of Mitigation

The business accounting matrix: a proposal with an application

National accounting matrices (NAM) perfectly describe the economic structure of a national economy, summarising the whole process of generation of primary income and its distribution among the different institutional sectors of the economy. It is not just a way to represent the main economic statistics of an economy but it also serves as the basis for most macroeconomic modelling efforts. The business accounting matrix (BAM) presents the most relevant information for the firm in a similar way, adapted to the descriptive potential of financial accounting, what we believe can be useful both for economic modellers and for decision makers at the firm level. Our intention is not to convince business administrators to change their accounting paradigm but to help analysts and researchers to obtain a comprehensive description of the activity of a firm aligned to well recognised economic statistical standards.

Development of a conceptual model of childhood asthma to inform asthma prevention policies

BackgroundThere is no definitive cure for asthma, as prevention remains a major goal. Decision analytic models are routinely used to evaluate the value-for-money proposition of interventions. Following best practice standards...

From Spreadsheets to Script: Experiences From Converting a Scottish Cardiovascular Disease Policy Model into R.

Given the advantages in transparency, reproducibility, adaptability and computational efficiency in R, there is a growing interest in converting existing spreadsheet-based models into an R script for model re-use and upskilling training among health economic modellers. The objective of this exercise was to convert the Scottish Cardiovascular Disease (CVD) Policy Model from Excel to R and discuss the lessons learnt throughout this process. The CVD model is a competing risk state transition cohort model. Four health economists, with varied experience of R, attempted to replicate an identical model structure in R based on the model in Excel and reproduce the intermediate and final results. Replications varied in their use of specialist health economics packages in addition to standard data management packages. Two versions of the CVD model were created in R along with a Shiny app. Version 1 was developed without health economics specialist packages and produced identical results to the Excel version. Version 2 used the heemod package and did not achieve the same results, possibly due to the non-standard elements of the model and limited time to adapt the functions. The R model requires less than half the computational time than the Excel model. Conversion of the spreadsheet models to script models is feasible for health economists. A step-by-step guide for the conversion process is provided and modellers' experience is discussed. Coding without specialist packages allows full flexibility, while specialist packages may add convenience if the model structure is suitable. Whichever approach is taken, transparency and replicability remain the key criteria in model programming. Model conversions must maintain standards in these areas regardless of the choice of software.

Disarray at the headquarters: Economists and Central bankers tested by the subprime and the COVID recessions

Abstract The article explores the discussions among economic modelers and central banks research staff and decision makers, namely on the adequacy of unconventional monetary policy and fiscal expansionary measures after the subprime crisis and as the COVID recession is developing. First, the article investigates the arguments, models and policy proposals of several mainstream schools of economics that challenged the traditional Chicagoan orthodoxy based on Milton Friedman’s views, and developed the Lucas Critique, the New Classical synthesis and Real Business Cycle approach that replaced monetarism as the main rivals to old-time Keynesianism. Second, the transformation of Real Business Cycle models into Dynamic Stochastic General Equilibrium (DSGE) models is mapped, as it extended the ideas of the iniquity of government intervention and unified academic and central bank research. Yet, a battery of criticism was levied against the DSGE models and, as the debate emerged over quantitative easing and other tools of unconventional monetary policy, the need for policy pragmatism shattered the previous consensus. The article then proceeds to discuss how the leading mainstream academic economists reacted to changes in central banks‘ practices, noticing a visible dissonance within Chicago-school and DSGE economists, as well as major contortions of central bankers in order to justify their new postures. The article concludes with a call for an extensive menu of fiscal, industrial and innovation policies in order to respond to recessions and structural crises.

Ambivalent economizations: the case of value added modeling in teacher evaluation

Research on economization processes is increasingly taking seriously the social and material processes through which various policy domains are transformed into economic problems and solutions. This article engages “Value Added Modeling” (VAM) in teacher evaluation systems as a case study in economization. VAM is a statistical technology for evaluating the effectiveness of schoolteachers using student test scores, which wrests authority for the determination of quality teaching away from education professionals and toward quantitative economic modelers. Mobilizing field theory, we trace a half century of changing relationships among economists, other academics, and various policy audiences (from media to philanthropists to state and federal government) in struggles to define education policy concerning teacher quality. We show that economization is a set of overlapping, sometimes contradictory processes that can take different forms: in this case, the spread of an “economic style of reasoning” or the establishment of “economic policy devices.” The case of VAM shows stages of economization in which processes first proceeded independently of one another, then interacted in contradictory ways, and finally, mutually reinforced one another. What primarily drove these interactions was the struggle for scientific capital within the economics discipline and the changing place of education policy and VAM within it. Ultimately, VAM’s original role as a policy device for evaluating and selecting individual teachers has foundered even as it has become an important tool for economists to accrue scientific capital and expand their style of reasoning to broader audiences.

IDENTIFYING OPTIMAL VACCINATION STRATEGIES VIA ECONOMIC AND EPIDEMIOLOGICAL MODELING

Vaccination is among the most effective means of preventing and controlling infectious disease outbreaks. Mathematical models can be used to identify the optimal allocation of vaccine among various groups when host populations are heterogeneous. Population heterogeneity may affect individual decision-making and government policy. We show that mixing among sub-populations can profoundly influence the optimal vaccination allocation. Centralized and decentralized programs are examined, accounting for individual behavior and economic constraints. We also compare approaches to modeling transitions between epidemiological classes by epidemiological and economic modelers, and identify key differences.

Estimating the cost-effectiveness of salt reformulation and increasing access to leisure centres in England, with PRIMEtime CE model validation using the AdViSHE tool

BackgroundPRIMEtime CE is a multistate life table model that can directly compare the cost effectiveness of public health interventions affecting diet and physical activity levels, helping to inform decisions about how to spend finite resources. This paper estimates the costs and health outcomes in England of two scenarios: reformulating salt and expanding subsidised access to leisure centres. The results are used to help validate PRIMEtime CE, following the steps outlined in the Assessment of the Validation Status of Health-Economic decision models (AdViSHE) tool.MethodsThe PRIMEtime CE model estimates the difference in quality adjusted life years (QALYs) and difference in NHS and social care costs of modelled interventions compared with doing nothing. The salt reformulation scenario models how salt consumption would change if food producers met the 2017 UK Food Standards Agency salt reformulation targets. The leisure centre scenario models change in physical activity levels if the Birmingham Be Active scheme (where swimming pools and gym access is free to residents during defined periods) was rolled out across England.The AdViSHE tool was developed by health economic modellers and divides model validation into five parts: validation of the conceptual model, input data validation, validation of computerised model, operational validation, and other validation techniques. PRIMEtime CE is discussed in relation to each part.ResultsSalt reformulation was dominant compared with doing nothing, and had a 10-year return on investment of £1.44 (£0.50 to £2.94) for every £1 spent. By contrast, over 10 years the Be Active expansion would cost £727,000 (£514,000 to £1,064,000) per QALY.PRIMEtime CE has good face validity of its conceptual model and has robust input data. Cross-validation produces mixed results and shows the impact of model scope, input parameters, and model structure on cost-per-QALY estimates.ConclusionsThis paper illustrates how PRIMEtime CE can be used to compare the cost-effectiveness of two different public health measures affecting diet and physical activity levels. The AdViSHE tool helps to validate PRIMEtime CE, identifies some of the key drivers of model estimates, and highlights the challenges of externally validating public health economic models against independent data.

Health Utility Book (HUB)–Cancer: Protocol for a Systematic Literature Review of Health State Utility Values in Cancer

Background. Treatment options in oncology are rapidly advancing, and public payer systems are increasingly under pressure to adopt new but expensive cancer treatments. Cost-utility analyses (CUAs) are used to estimate the relative costs and effects of competing interventions, where health outcomes are measured using quality-adjusted life years (QALYs). Health state utility values (HSUVs) are used to reflect health-related quality of life or health status in the calculation of QALYs. To support reimbursement agencies in the appraisal of oncology drug submissions, which typically include a CUA component, we have proposed a systematic literature review of published HSUV estimates in the field of oncology. Methods. The following databases will be searched: MEDLINE, EMBASE, EconLit, and CINAHL. A team of reviewers, working independently and in duplicate, will evaluate abstracts and full-text publications for eligibility against broad inclusion criteria. Studies using a direct, indirect, or combination approach to eliciting preferences related to cancer or cancer treatments are eligible. Data extraction will capture details of study methodology, participants, health states, and corresponding HSUVs. We will summarize our findings with descriptive analyses at this stage. A pilot review in thyroid cancer is presented to illustrate the proposed methods. Discussion. This systematic review will generate a comprehensive summary of the oncology HSUV literature. As a component of the Health Utility Book (HUB) project, we anticipate that this work will assist both health economic modelers as well as critical reviewers in the development and appraisal of CUAs in oncology.

A Community of Practice for Economic Modelling of Climate Change Mitigation in New Zealand

The public and private sectors face important strategic decisions about low-emissions transitional pathways. Such decisions require sound evidence, with input from experts and stakeholders across the board. Models can be used for evidence-based decision-making, but New Zealand has shortcomings in its capacity for climate policy analysis, particularly in comparison with other jurisdictions. These deficiencies pose a serious risk to New Zealand’s future economic development. Climate policy analysis requires assessing a wide range of factors. A multi-model approach supported by multiple providers improves consistency, coordination, and collaboration across members of the modelling community, users of modelling results, and funders of modelling. This document summarises the compelling case for developing a New Zealand ‘Climate Policy Modelling Initiative’ (CPMI). This initiative would coordinate and enhance delivery of modelling across multiple providers. This work is informed by several workshops that brought together economic modellers from a range of organisations. If supported by government leadership and commitment, the CPMI would have a transformational effect on New Zealand’s capacity to plan for a successful low-emissions future.

Estimating comparable English healthcare costs for multiple diseases and unrelated future costs for use in health and public health economic modelling.

ObjectivesHealthcare interventions, and particularly those in public health may affect multiple diseases and significantly prolong life. No consensus currently exists for how to estimate comparable healthcare costs across multiple diseases for use in health and public health cost-effectiveness models. We aim to describe a method for estimating comparable disease specific English healthcare costs as well as future healthcare costs from diseases unrelated to those modelled.MethodsWe use routine national datasets including programme budgeting data and cost curves from NHS England to estimate annual per person costs for diseases included in the PRIMEtime model as well as age and sex specific costs due to unrelated diseases.ResultsThe 2013/14 annual cost to NHS England per prevalent case varied between £3,074 for pancreatic cancer and £314 for liver disease. Costs due to unrelated diseases increase with age except for a secondary peak at 30–34 years for women reflecting maternity resource use.ConclusionsThe methodology described allows health and public health economic modellers to estimate comparable English healthcare costs for multiple diseases. This facilitates the direct comparison of different health and public health interventions enabling better decision making.

Environmental limitation mapping of potential biomass resources across the conterminous United States

AbstractSeveral crops have recently been identified as potential dedicated bioenergy feedstocks for the production of power, fuels, and bioproducts. Despite being identified as early as the 1980s, no systematic work has been undertaken to characterize the spatial distribution of their long‐term production potentials in the United states. Such information is a starting point for planners and economic modelers, and there is a need for this spatial information to be developed in a consistent manner for a variety of crops, so that their production potentials can be intercompared to support crop selection decisions. As part of the Sun Grant Regional Feedstock Partnership (RFP), an approach to mapping these potential biomass resources was developed to take advantage of the informational synergy realized when bringing together coordinated field trials, close interaction with expert agronomists, and spatial modeling into a single, collaborative effort. A modeling and mapping system called PRISM‐ELM was designed to answer a basic question: How do climate and soil characteristics affect the spatial distribution and long‐term production patterns of a given crop? This empirical/mechanistic/biogeographical hybrid model employs a limiting factor approach, where productivity is determined by the most limiting of the factors addressed in submodels that simulate water balance, winter low‐temperature response, summer high‐temperature response, and soil pH, salinity, and drainage. Yield maps are developed through linear regressions relating soil and climate attributes to reported yield data. The model was parameterized and validated using grain yield data for winter wheat and maize, which served as benchmarks for parameterizing the model for upland and lowland switchgrass, CRP grasses, Miscanthus, biomass sorghum, energycane, willow, and poplar. The resulting maps served as potential production inputs to analyses comparing the viability of biomass crops under various economic scenarios. The modeling and parameterization framework can be expanded to include other biomass crops.

Can Economic Model Transparency Improve Provider Interpretation of Cost-effectiveness Analysis? Evaluating Tradeoffs Presented by the Second Panel on Cost-effectiveness in Health and Medicine.

The Second Panel on Cost-Effectiveness in Health and Medicine convened on December 7, 2016 at the National Academy of Medicine to disseminate their recommendations for conduct, methodological practices, and reporting of cost-effectiveness analyses (CEAs). Following its summary, panel proceedings included lengthy discussions including the field's struggle to disseminate findings efficiently through peer-reviewed literature to target audiences. With editors of several medical and outcomes research journals in attendance, there was consensus that findings of cost-effectiveness analyses do not effectively reach other researchers or health care providers. The audience members suggested several solutions including providing additional training to clinicians in cost-effectiveness research and requiring that cost-effectiveness models are made publicly available. However, there remains the questions of whether making economic modelers' work open-access through journals is fair under the defense that these models remain one's own intellectual property, or whether journals can properly manage the peer-review process specifically for cost-effectiveness analyses. In this article, we elaborate on these issues and provide some suggested solutions that may increase the dissemination and application of cost-effectiveness literature to reach its intended audiences and ultimately benefit the patient. Ultimately, it is our combined view as economic modelers and clinicians that cost-effectiveness results need to reach the clinician to improve the efficiency of medical practice, but that open-access models do not improve clinician access or interpretation of the economics of medicine.

Leveraging Electronic Health Records to Meet The Real World Evidence Needs of Hta: A Uk Perspective

The inclusion of real world evidence in HTA submissions has become increasingly desirable. In the UK, databases containing data collected in primary care represent a ready source of real world data however they continue to be underutilised in this field. We sought to review the use of such databases in NICE technology assessments (TAs) and provide recommendations regarding their use in future submissions. The NICE website was searched for keywords relating to the main primary care databases in the UK. All NICE TAs identified through this search were screened and information on the data source and the way the data was used in the submission were extracted. Comments on the data by the evidence review group (ERG) and committee were also extracted and reviewed. A total of 13 NICE TAs were identified. Between 2007 and 2010, data from primary care databases were used in 3 NICE TAs to support arguments regarding the prevalence of asthma and prescribing patterns in asthma and fracture prevention. The ERG/committee did not comment on this data. Between 2011 and 2016, data from primary care databases were used in 10 NICE TAs, with 3 in 2015 and 3 in 2016. In each of these cases the data were used to inform a small number of parameters in an economic model. The data were generally well received by the ERGs/committees. Criticisms of the data typically occurred where the results had been repurposed from a published study. The use of data from UK primary care databases in NICE submissions is increasing. The planning of database studies to support market access should begin early in the drug development process and, through collaboration between the trial team, economic modellers and database experts, can be used to inform a multitude of parameters in the economic model.

Visual Economic Modelling System (VEMS) for Computable General Equilibrium Models

By using a graphical user interface of the software tool Visual Economic Modelling System (VEMS) a modeller can set up a computable general equilibrium model by specifying the various stocks and the flows between them. VEMS generates the corresponding social accounting matrix, the equations of the model, the equations for carrying out the calibration and is capable of performing simulations. The tool is build using Microsoft Visual Basic with an object oriented approach. GAMS is the tool in the background for solving each of the models. GAMS is also used for (partly) calibrating the model and a Prolog program can also be used for the calibration. Static and dynamic (backward and forward-looking) models can be generated. The models are written using the GAMS syntax. There are NLP, MCP, MCP$$^{+}$$+ and MPSGE versions of the model. VEMS is a prototype and needs further development. One obvious application of it would be as an educational tool for economic modellers.

Introducing Irrigation Water into GTAP Data Base Version 9

Water is an essential input in the production processes of all goods and services. However, most economic models ignore water as an essential factor of production. In contrast with other inputs, economic data do not reflect the role of water in the production processes of goods and services and its final value in the demand side. This makes it difficult to incorporate water in economic models, properly examine its role in economic activities, and study its interaction with other inputs in the production processes. Introducing water into an economy-wide database such as Global Trade Analysis Project (GTAP) Data Base which has been widely used by many economic modelers across the world could help them to extend their research agendas on the role and importance of water in economic activities. As the first step towards this direction we divided the crop sectors of the GTAP-Power Data Base (which extends the GTAP Data Base Version 9 by disaggregating the electricity sector) into irrigated and rainfed categories and explicitly included water for irrigation into the cost structure of irrigated crops by river basin at the Agro Ecological Zone (AEZ) level.

Five theses on neuroeconomics

Over the last decade, neuroeconomic research has attracted increasing attention by economic modellers and methodologists. In this paper, I examine five issues about neuroeconomic modelling and methodology that have recently been subject to considerable controversy. For each issue, I explicate and appraise prominent neuroeconomists' findings, focusing on those that are claimed to directly inform economic theorizing. Moreover, I assess often-made assertions concerning how neuroeconomic research putatively advances the economic modelling of choice. In doing so, I combine review and critical arguments to provide a methodological evaluation of neuroeconomists' contributions.