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Respiratory syncytial virus (RSV) is the most common cause of pediatric acute lower respiratory tract infection worldwide. Detailed data on the health and economic burden of RSV disease are lacking from tropical settings with year-round RSV transmission. We developed a statistical and economic model to estimate the annual incidence and healthcare cost of medically attended RSV disease among young children in Singapore, using Monte Carlo simulation to account for uncertainty in model parameters. RSV accounted for 708 hospitalizations in children <6 months of age (33.5/1,000 child-years) and 1,096 in children 6-29 months of age (13.2/1,000 child-years). The cost of hospitalization was SGD 5.7 million (US $4.3 million) at 2014 prices; patients bore 60% of the cost. RSV-associated disease burden in tropical settings in Asia is high and comparable to other settings. Further work incorporating efficacy data from ongoing vaccine trials will help to determine the potential cost-effectiveness of different vaccination strategies. [ABSTRACT FROM AUTHOR]

The authors of this article introduce two teaching modules that aim to increase climate literacy and active learning in undergraduate economics courses through the incorporation of real-world data and modeling. These modules are based on the concept of computational guided inquiry (CGI), which combines a guided inquiry approach within a computational framework, such as Excel. In one module, students estimate and graph expected marginal damages due to regional sea level rise for various polar ice melt scenarios. In the second module, students partially replicate a journal article estimating the total economic value of ecosystem services in the Arctic. These modules have been used in urban, environmental, and climate change economics courses, and are ready to be implemented with minimal upfront cost to instructors. [ABSTRACT FROM AUTHOR]

This paper develops a flexible method for estimating the customer cost of a power outage. We add to the current body of literature by outlining a framework which properly accounts for the effects of outage duration. We begin by separating costs into categories depending on whether the cost varies with outage duration and whether the cost is due to perishable inventory. We derive useful functional forms for each cost category and discuss how parameters vary by load type and outage characteristics. We derive outage cost estimates for an unexpected loss of power to both an example manufacturing plant and an example fire station. The framework described in this paper can easily be employed to model outage costs for a wide range of specific operating conditions. [ABSTRACT FROM AUTHOR]

Belying the International Monetary Fund's (IMF's) reputation as a bastion of neo-liberal policy orthodoxy, this article analyses important yet contingent transformations in IMF fiscal policy thinking which constituted a key intervention in international austerity debates. Applying only to advanced economies, and in the specific post-crash conditions, the Fund came to champion fiscal policy as a more potent and effective counter-cyclical tool. Analysis focuses on alterations to modeling assumptions and analytical techniques, beginning before the crash but accelerating after it, which intellectually bolstered this view. It finds the Fund's rediscovery of some older (Keynesian) assumptions was both longer in germination and more enduring than some have recognized. It also charts the reconciliation of this contingent Keynesianism to 'congenital' IMF concerns for fiscal sustainability. It highlights the variety of economic insights, often with vastly differing policy implications, found within the Fund, and indeed within mainstream macroeconomics. It builds on work questioning the stability, consistency, and coherence of economic ideas suggested by the paradigm framework, and identifies limitations of a paradigm lens for understanding incremental IMF ideational change. It contributes to politics of economic ideas scholarship in highlighting the importance of economic method and modeling assumptions as sites of contestation within gradual but meaningful ideational change. [ABSTRACT FROM AUTHOR]

The objective of this paper is to establish conceptual foundations of analyzing the economic dimensions of Brexit. The International Financial-Trade Exchange Leaking Index (TIFTEL-Index) attempts to analyze and compare pre-Brexit versus post-Brexit international trade and international financial transactions between East and Southeast Asia and Europe. TIFTEL-index is based on three main variables, namely (1) international trade exchange marginal rate (∆Τ′), (2) international financial exchange marginal rate (∆σ′), and (3) GDP in real prices growth marginal rate (∆γ). Simulation findings indicate that Brexit will have only a limited negative effect on the world economy. In addition, Brexit will affect East Asia more than Southeast Asia region. [ABSTRACT FROM AUTHOR]

• A new clearing model is presented for joint energy-reserve power exchanges. • The submission of combined energy-reserve orders is allowed and encouraged. • The new algorithm can handle non-convex European order types and market coupling. • The new model is formulated as a single convex Mixed Integer Quadratic Program. • A case study is presented to test and evaluate the performance of the new model. In order to enhance the liquidity and stability of ancillary service markets in Europe and to motivate the participation of renewable energy resources, the incorporation of control reserve procurement into day-ahead power exchanges (PXs) is proposed. The design of the corresponding clearing algorithm is presented in detail. The model allows the submission of combined energy-reserve orders and guarantees that opportunity costs of power producers are taken into account. It can also handle non-convex offers (e.g. block bids) and market coupling that are essential components of European PX designs. The formulated optimization problem can be classified as a convex Mixed Integer Quadratic Program; consequently, its solution can be found using readily available generic solvers. A numerical simulation is executed for the purpose of demonstration and also to make a comparison between joint and separated allocation of energy and reserves. The simple initial analysis suggests that the proposed integration approach is beneficial. [ABSTRACT FROM AUTHOR]

To account for endogeneity effects in, e.g., energy demand, modern bottom-up energy system models are often linked to a top-down model describing the macroeconomic system. Solving such linked models involves iteratively passing solutions from one model to the other and vice versa until convergence is reached, which can be computationally demanding. This paper proposes a coordination algorithm that speeds up convergence for the linkage of the two models in case the bottom-up model is a linear program and the top-down model is a mixed-complementarity problem. The coordination algorithm uses duality theory to select optimal bases from previous iterations to predict the solution of the bottom-up model. If the predicted solution is correct, which is shown to be equivalent to the predicted solution vector being non-negative, the bottom-up problem need not be solved in that iteration, resulting in a time gain. Numerical experiments on an energy system design problem illustrate that our coordination algorithm correctly predicts the bottom-up solution in most iterations, resulting in a significant reduction in overall computation time. • A new algorithm speeds up linked top-down (TD) and bottom-up (BU) model convergence. • Optimal bases from prior iterations are used to predict the BU model solution. • Numerical tests reveal 76% average reduction in computation time. • The algorithm outperforms warm start methods by a significant margin. • Promising for large-scale TD-BU models currently deemed computationally challenging. [ABSTRACT FROM AUTHOR]

Background: In response to COVID-19, the UK National Health Service (NHS) extended influenza vaccination in 50- to 64-year-olds from at-risk only to all in this age group for the 2020/21 season. The objective of this research is to determine the cost-effectiveness of continuing to vaccinate all with a quadrivalent cell-based vaccine (QIVc) compared to returning to an at-risk only policy after the pandemic resolves. Methods: A dynamic transmission model, calibrated to match infection data from the UK, was used to estimate the clinical and economic impact of vaccination across 10 influenza seasons. The base case effectiveness of QIVc was 63.9% and the list price was GBP 9.94. Results: Vaccinating 50% of all 50- to 64-year-olds with QIVc reduced the average annual number of clinical infections (−682,000), hospitalizations (−5800) and deaths (−740) in the UK. The base case incremental cost per quality-adjusted life-year gained (ICER) of all compared to at-risk only was GBP6000 (NHS perspective). When the cost of lost productivity was considered, vaccinating all 50- to 64-year-olds with QIVc became cost-saving. Conclusion: Vaccinating all 50- to 64-year-olds with QIVc is likely to be cost-effective. The NHS should consider continuing this policy in future seasons.

The borrowers’ solvency has been deteriorated due to external and unpredictable economic shocks in Ukraine. A negative financial result of Ukrainian banking sector was formed due to a substantial increase in the amount of deductions to reserves on possible losses from active operations. About 40% of the losses were formed by banks, which are categorized as insolvent.In this paper, the models to calculate integral indexes of the banking system have been built. Some new intervals (limits) for the degree of influence of the assess components of integral indexes for banking are verified and calculated.

Several studies have analyzed the social, economic, and environmental impacts of deforestation in the context of developing countries. However, no study, to the best of our knowledge, has focused directly on the role of expanding demand for agricultural commodities on deforestation in the context of developed countries, in general, and the United States, in particular. We used an integrative approach to understand linkages between deforestation and agricultural expansion in SE Georgia where about 15,000 hectares of evergreen forestlands and grasslands have been converted to blueberries between 2010 and 2017. We first developed economic models to understand any differences in profitability between a hectare of pine plantation and blueberry orchard. The economic analysis shows that the annualized net present value of blueberry production is higher by $3848.0/ha than loblolly pine in the region. We developed a site suitability model using geospatial tools for blueberry production in SE Georgia as well and found that about 85% of the available land is suitable for blueberry production in SE Georgia. We also found that about 80% of existing pine forestlands overlap with the land that is suitable for blueberry production. Our results indicate that a further rise in the demand for blueberries could increase deforestation in SE Georgia. We suggest an integrated approach based on innovative economic policies for reducing deforestation in SE Georgia. • The returns from blueberry production are higher than common yellow pine species. • The investment in blueberry is riskier than yellow pines. • >85% of the available land is suitable for blueberry production in SE Georgia. • >80% of the existing pine forestlands overlap with land that is suitable for blueberry production. • Innovative policy designs are needed for reducing deforestation in the region. [ABSTRACT FROM AUTHOR]

Background: The 'German Consortium for Hereditary Breast and Ovarian Cancer' (GC-HBOC) offers women with a family history of breast and ovarian cancer genetic counseling. The aim of this modeling study was to evaluate the cost-effectiveness of genetic testing for BRCA 1/2 in women with a high familial risk followed by different preventive interventions (intensified surveillance, risk-reducing bilateral mastectomy, risk-reducing bilateral salpingo-oophorectomy, or both mastectomy and salpingo-oophorectomy) compared to no genetic test.Methods: A Markov model with a lifelong time horizon was developed for a cohort of 35-year-old women with a BRCA 1/2 mutation probability of ≥ 10%. The perspective of the German statutory health insurance (SHI) was adopted. The model included the health states 'well' (women with increased risk), 'breast cancer without metastases', 'breast cancer with metastases', 'ovarian cancer', 'death', and two post (non-metastatic) breast or ovarian cancer states. Outcomes were costs, quality of life years gained (QALYs) and life years gained (LYG). Important data used for the model were obtained from 4380 women enrolled in the GC-HBOC.Results: Compared with the no test strategy, genetic testing with subsequent surgical and non-surgical treatment options provided to women with deleterious BRCA 1 or 2 mutations resulted in additional costs of €7256 and additional QALYs of 0,43 (incremental cost-effectiveness ratio of €17,027 per QALY; cost per LYG: €22,318). The results were robust in deterministic and probabilistic sensitivity analyses.Conclusion: The provision of genetic testing to high-risk women with a BRCA1 and two mutation probability of ≥ 10% based on the individual family cancer history appears to be a cost-effective option for the SHI. [ABSTRACT FROM AUTHOR]

We present a new model on the impact of terrorism on the Deglobalization process. The channels are faster poverty expansion, largest flows of refugees, expansion of trade protectionism, and last but not least, the dramatic expansion of economic desgrowth. This new model is entitled "The Deglobalization Global Evaluation Model (DGE-Model)". The objective of the DGE-Model is to offer policy-makers and researchers a new analytical tool to study the impact of terrorism on the Deglobalization process of Muslim countries. The applicability of the DGE-Model is not limited to a specific group of Muslim countries or regions, nor is it constrained by the development stage. In short, the DGE-Model is a simple, flexible and versatile tool to study the link between terrorism and Deglobalization. Finally, we apply the DGE-Model to three Muslim countries, namely Syria, Iraq, and Afghanistan. Our sample period is 1999–2018, a period which witnessed acceleration of Deglobalization and expansion of terrorism in those three countries. [ABSTRACT FROM AUTHOR]

Highlights • A model for general complex orders on the all-European power exchange is proposed. • The clearing can handle ramping and income conditions simultaneously. • The formulation has the same theoretical complexity as operating clearing models. • The integrated solution approach facilitates market analysis and later development. Abstract The adequate modeling of power generation is one of the most challenging issues in the field of electricity markets. Practical market clearing requires simple and transparent formulations but some of the financial and technical conditions of power plants are inherently complicated. In Europe, this predicament is usually handled by introducing special order types on day-ahead power exchanges. This approach often leads to algorithmic complications for power exchanges because new order types usually imply specific constraints some of which can affect the behavior of their overall mathematical model. The officially proposed clearing algorithm of the all-European exchange (namely, EUPHEMIA) is supposed to handle so-called complex orders for suppliers. These are composed of a set of traditional hourly step bids with linking conditions i.e. the Minimum Income Condition, the Load Gradient Condition and the auxiliary Scheduled Stop Condition. A new formulation is proposed for the case when all three conditions are attached to the complex order. A single convex Mixed Integer Problem is solved for market clearing which is conceptually similar to the models already widely used in Europe. Numerical case studies are discussed along with practical viability. [ABSTRACT FROM AUTHOR]

Poor mental health has profound economic consequences. Given the burden of poor mental health, the economic case for preventing mental illness and promoting better mental health may be very strong, but too often prevention attracts little attention and few resources. This article describes the potential role that can be played by economic evidence alongside experimental trials and observational studies, or through modeling, to substantiate the need for increased investment in prevention. It illustrates areas of action across the life course where there is already a good economic case. It also suggests some further areas of substantive public health concern, with promising effectiveness evidence, that may benefit from economic analysis. Financial and economic barriers to implementation are then presented, and strategies to address the barriers and increase investment in the prevention of mental illness are suggested. [ABSTRACT FROM AUTHOR]

Background: Payers frequently rely on budget impact model (BIM) results to help determine drug coverage policy and its effect on their bottom line. It is unclear whether BIMs typically overestimate or underestimate real-world budget impact.Objective: We examined how different modeling assumptions influenced the results of 6 BIMs from the Institute for Clinical and Economic Review (ICER).Study Design: Retrospective analysis of pharmaceutical sales data.Methods: From ICER reports issued before 2016, we collected estimates of 3 BIM outputs: aggregate therapy cost (ie, cost to treat the patient population with a particular therapy), therapy uptake, and price. We compared these against real-world estimates that we generated using drug sales data. We considered 2 classes of BIM estimates: those forecasting future uptake of new agents, which assumed "unmanaged uptake," and those describing the contemporaneous market state (ie, estimates of current, managed uptake and budget impact for compounds already on the market).Results: Differences between ICER's estimates and our own were largest for forecasted studies. Here, ICER's uptake estimates exceeded real-world estimates by factors ranging from 7.4 (sacubitril/valsartan) to 54 (hepatitis C treatments). The "unmanaged uptake" assumption (removed from ICER's approach in 2017) yields large deviations between BIM estimates and real-world consumption. Nevertheless, in some cases, ICER's BIMs that relied on current market estimates also deviated substantially from real-world sales data.Conclusions: This study highlights challenges with forecasting budget impact. In particular, assumptions about uptake and data source selection can greatly influence the accuracy of results. [ABSTRACT FROM AUTHOR]

BACKGROUND: Omadacycline is an oral and intravenous (IV) once-daily aminomethylcycline antibiotic that was recently approved by the US Food and Drug Administration for the treatment of patients with acute bacterial skin and skin structure infections (ABSSSI). In 2 phase 3 clinical trials, IV-to-oral switch and oral-only administration of omadacycline achieved the primary end points of noninferiority compared with linezolid in treating patients with ABSSSI. OBJECTIVE: To estimate the potential cost-savings with bioequivalent IV-to-oral antibiotics, such as omadacycline, compared with the standard of care with IV vancomycin by avoiding hospitalizations and reducing hospital stays in patients presenting from the emergency department for ABSSSI treatment. METHODS: We used hospital avoidance models to examine the potential cost-savings of managing patients with ABSSSI and no or limited comorbidities and without life-threatening conditions by using omadacycline in the outpatient setting compared with the current standard of care. Early hospital discharge models were used to evaluate the hospital stay reduction that would be required to be achieved with omadacycline treatment relative to IV vancomycin to confer cost-savings compared with standard of care among patients with ABSSSI and ≥2 comorbidities but no life-threatening conditions. RESULTS: In the hospital stay avoidance models, cost-savings may be realized by using therapeutically bioequivalent IV-to-oral antibiotics, such as omadacycline, compared with inpatient treatment with IV vancomycin. Based on a sensitivity analysis, further savings could be possible with outpatient administration of omadacycline, even if 20% of omadacycline outpatients were subsequently admitted and incurred the full inpatient cost, with no reimbursement penalties. Of more than 300 patients, only 1 was admitted to the hospital after a full course of omadacycline in the oral-only clinical trial. In the early hospital discharge models, the maximum cost-minimizing daily expense of omadacycline varied from $173 to $936, depending on the presence of active comorbidities or systemic symptoms, hospital stay reduction, and model perspective. CONCLUSION: These results suggest that the targeted use of antibiotics with bioequivalent IV-to-oral formulations, such as omadacycline, for select patients with ABSSSI may lead to cost-savings compared with inpatient IV vancomycin treatment by shifting care to the outpatient setting or by facilitating earlier hospital discharge among hospitalized patients. [ABSTRACT FROM AUTHOR]

Abstract We apply the terrorist attack vulnerability evaluation model (TAVE-Model) to evaluate the effect of terrorism on the economic performance of Turkey. We examine both the short run and long-run economic impact of terrorist attacks in Turkey. The TAVE-Model deploys a number of indicators to evaluate the economic impact. The indicators are economic desgrowth (- δ), intensity of terrorist activities (α i), terrorist attack losses (- π), economic wear (Π), level of terrorist attack tension (ζ), level of terrorist attacks monitoring (η), and total economic leaking (Ω t) under a terrorist attack. The basic underlying idea of TAVE-Model is that the economic impact of a terrorist attack depends on a country's vulnerability to attacks from domestic and international terrorist groups. The application of a model to Turkey is highly topical in light of the spate of terrorist attacks the country suffered in recent years. The results of TAVE-Model confirm that economic leaking, economic desgrowth, and economic wear has increased between 1990 and 2016. The issue of terrorism in Turkey is multidimensional, and tackling it requires an effective social assistance program as well as a stronger and impartial justice system. These reforms will render poorer Turks less vulnerable and increase the opportunity cost of terrorism. [ABSTRACT FROM AUTHOR]

• Process models were developed to compare traditional stainless-steel and flexible facilities. • J.POD®, a flexible facility employing single-use, portable cleanroom technologies is introduced. • Varying cost structures and utilization rates are compared across different facility types. • A dynamic simulation approach is used to model a low-cost biologic drug with uncertain demand. In this work, process models were developed to capture the impact of biomanufacturing costs on a commercial scale and emphasize the way in which facility design and operation must balance meeting product demand while minimizing production costs. Using a scenario-based modeling approach, several facility design strategies were evaluated, including a traditional large stainless-steel facility and a small footprint, portable-on-demand (POD)-based facility. Bioprocessing platforms were compared by estimating their total production costs across different facility types and specifically illustrating how continuous bioprocessing has gained in popularity as a novel and cost-effective approach to manufacture high-quality biopharmaceuticals. The analysis showed how fluctuations in market demand have a dramatic effect on manufacturing costs and plant utilization, with far-reaching implications on the total cost to patients. [ABSTRACT FROM AUTHOR]

Noble Laureates Thomas Sargent and Christopher Sims have been granted the 2011 Noble Prize in economic sciences in appreciation of their empirical research on causes and effects in macroeconomics. The controversy on causality in macroeconomics was discussed in both of Sargent’s and Sims’s 2011 Prize lectures. While Sargent attempts to use the economic theory to interpret some historical events in order to gain insights on some contemporary issues, such as sovereign defaults, federal bailouts, and the coordination of monetary and fiscal policies, Sims is emphasizing the importance of large-scale economic models and calling for more research to be done in that area.

Within the framework of a model describing real-functioning association of three enterprises, numerical calculations of economic dynamics parameters considering fluctuating market demand for the goods were performed. A methodology was suggested for approximated consideration of both seasonal and random demand fluctuations at the market of textile garments; the main steps of the suggested methodology were described. The main exogenous random factors within this model include, as stated above, the volume of market demand for the goods produced by the enterprises of the group. The basic volume of market demand is considered at the average actual level according to the results of the enterprises’ analysis, and additionally we take into account the influence of non-price factors, such as random changes in the consumers’ tastes, consumers’ income, and other random factors on the market demand. By volume of market demand, we consider the total amount of goods produced by the enterprises of the group that all consumers are willing and able to purchase at a specific price in a marketplace. The calculations were made based on actual values of external economic parameters, such as labor cost, product prices, etc. Influence of the market demand fluctuations on the companies’ activity has been illustrated both numerically and graphically, allowing the analysis of the impact of exogenous parameters on the companies output and profits. The suggested approach creates a basis for further analysis of the impact of random factors of a similar nature, i.e., stochastic shocks related to the level of interest rates, shifts and turnabouts in the social environment, as well as the market transformations due to annual/seasonal epidemics.

The objective of this study was to estimate, from an obesity prevention perspective, the cost-effectiveness of two potential policies that increase the price of alcohol in Australia: a volumetric tax applied to all alcohol (Intervention 1) and a minimum unit floor price (Intervention 2). Estimated changes in alcoholic drink consumption and corresponding changes in energy intake were calculated using the 2011−12 Australian Health Survey data, published price elasticities, and nutrition information. The incremental changes in body mass index (BMI), BMI-related disease outcomes, healthcare costs, and Health Adjusted Life Years (HALYs) were estimated using a validated model. Costs associated with each intervention were estimated for government and industry. Both interventions were estimated to lead to reductions in mean alcohol consumption (Intervention 1: 20.7% (95% Uncertainty Interval (UI): 20.2% to 21.1%); Intervention 2: 9.2% (95% UI: 8.9% to 9.6%); reductions in mean population body weight (Intervention 1: 0.9 kg (95% UI: 0.84 to 0.96); Intervention 2: 0.45 kg (95% UI: 0.42 to 0.48)); HALYs gained (Intervention 1: 566,648 (95% UI: 497,431 to 647,262); Intervention 2: 317,653 (95% UI: 276,334 to 361,573)); and healthcare cost savings (Intervention 1: $5.8 billion (B) (95% UI: $5.1B to $6.6B); Intervention 2: $3.3B (95% UI: $2.9B to $3.7B)). Intervention costs were estimated as $24M for Intervention 1 and $30M for Intervention 2. Both interventions were dominant, resulting in health gains and cost savings. Increasing the price of alcohol is likely to be cost-effective from an obesity prevention perspective in the Australian context, provided consumers substitute alcoholic beverages with low or no kilojoule alternatives.

The investigation presents scientific and methodological approach of evaluation of efficiency of the banking system through a generalized Harrington function (desirable function) that allows to determine the current state of the banking system and to predict the perspectives of its development. In the simulation of assessment of the banking system were used data from 49 banks operating in Ukraine for 2003–2016 and 15 financial indicators, which provide formation of input variables of the model. The method of data processing is implemented in the package Viscovery SOMine. The approach is based on the analysis of the dynamics of patterns of banks and building self–organizing Kohonen maps which enables to determine the trajectory of activity of individual bank. This approach enables forecasting of individual bank crisis and the potential crisis of banking system of a country. Conducted trend forecast of the Harington function suggests potential of improving of Ukrainian banking system over the next 3 years.

A model is proposed for economic assessment of projected airplane engines, in terms of life-cycle costs. Adoption of a new strategy is recommended: management of engine life on the basis of the current state of the system (on-condition maintenance) and increase in economic efficiency at the operational stage. A conceptual approach to extending the life of promising aircraft engines is outlined, on the basis of a diagnostic system (real-time performance assessment). That permits decisions regarding the engine's potential for continued operation. [ABSTRACT FROM AUTHOR]

The research is focused on efficiency assessment of economic cooperation in development of Arctic offshore oil and gas resources. The author developed an economic model based on cost-benefit analysis (CBA). CBA is used in some countries (EU, USA, Australia) as an analytic tool to make public policy decisions. CBA is based on the method of discounting cash flows associated with costs and benefits of public policy. It is assumed that all public goals are equally important inter alia, hence public bodies should opt for those initiatives that maximize public benefits for every dollar spent from the state budget. There are five stages of economic modeling: 1) the definition of public benefits and costs associated with the public initiative; 2) monetary valuation of costs and benefits; 3) the definition of discounting period and discounting rate; 4) the calculation of net present value of cash flows; 5) the comparison of initiatives' net present values. The model is built with a number of hypotheses assumed. It allows making evaluation of investments into the technology to decrease the cost of Arctic offshore oil and gas development. Moreover, the model has two scenarios describing a public policy to support technology development with international economic cooperation and without it. Under given hypotheses both scenarios return positive net present value of policies which proves that governmental initiative to support Arctic technology development is economically justified. Also the model sows that the scenario with international cooperation is more efficient from economic point of view. It is explained by two factors: the higher speed of technology transfer (due W international cooperation) and the opportunity to use financial leverage (attracting the funds from foreign partners). The model allows closing the existing scientific gap between the theory of CBA method and its practical use in public decision making.

The research is focused on efficiency assessment of economic cooperation in development of Arctic offshore oil and gas resources. The author developed an economic model based on cost-benefit analysis (CBA). CBA is used in some countries (EU, USA, Australia) as an analytic tool to make public policy decisions. CBA is based on the method of discounting cash flows associated with costs and benefits of public policy. It is assumed that all public goals are equally important inter alia, hence public bodies should opt for those initiatives that maximize public benefits for every dollar spent from the state budget. There are five stages of economic modeling: 1) the definition of public benefits and costs associated with the public initiative; 2) monetary valuation of costs and benefits; 3) the definition of discounting period and discounting rate; 4) the calculation of net present value of cash flows; 5) the comparison of initiatives' net present values. The model is built with a number of hypotheses assumed. It allows making evaluation of investments into the technology to decrease the cost of Arctic offshore oil and gas development. Moreover, the model has two scenarios describing a public policy to support technology development with international economic cooperation and without it. Under given hypotheses both scenarios return positive net present value of policies which proves that governmental initiative to support Arctic technology development is economically justified. Also the model sows that the scenario with international cooperation is more efficient from economic point of view. It is explained by two factors: the higher speed of technology transfer (due W international cooperation) and the opportunity to use financial leverage (attracting the funds from foreign partners). The model allows closing the existing scientific gap between the theory of CBA method and its practical use in public decision making.

Computable general equilibrium (CGE) models provide valuable insights into economy-wide impacts of anticipated future structural changes in the transportation sector, yet few CGE models offer detailed transportation representations. We use an enhanced Applied Dynamic Analysis of the Global Economy (ADAGE) CGE model to incorporate disaggregated transportation modes and technologies in on-road passenger and freight transportation. We assess the impacts of these inclusions on U.S. transportation patterns, energy consumption and greenhouse gas emissions. Simulating illustrative global oil price cases with and without transportation detail, we find subsector mode disaggregation and technology additions in a CGE model significantly alter the impacts of oil prices on global trade and freight patterns, energy consumption, and greenhouse gas (GHG) emissions. We find that: (1) alternative technologies are essential for capturing transportation sector impacts, (2) electrification may reduce emissions with electricity decarbonization, and (3) higher oil prices may hasten electrification.

This paper compares hard-linked and integrated approaches of hybrid top-down and bottom-up models in terms of equilibria and convergence. Four setups where a bottom-up linear programming model is hard-linked with a top-down computable general equilibrium model are implemented. A solution is found by iterating between the two models, until convergence is reached. The same equilibrium solution is found by all hard-linked setups in all problem instances. Next, one integrated model is introduced by extending the computable general equilibrium mixed complementarity model with the Karush-Kuhn-Tucker conditions that represent the bottom-up linear programming model. This integrated model provides the same solutions as the hard-linked models. Also, an alternative integrated model is provided, where the bottom-up model objective is optimized while the top-down model is included as additional constraints. This nonlinear program corresponds to a multi-follower bilevel formulation, with the energy system model as the leader and the general equilibrium players (firms and household) as followers. The Stackelberg equilibrium from this bilevel formulation pareto-dominates the Nash equilibrium from the other model setups in some problem instances, and is identical in the remaining problem instances. Different ways to couple the mathematical models may result in different solutions, because the coupling represents different real-world situations. [ABSTRACT FROM AUTHOR]

Our objectives were to develop an economic model to estimate the economic impact of twinning in dairy cows and to evaluate management strategies to mitigate the negative economic impact of twinning in dairy herds. A probabilistic tree considering spontaneous embryo reduction, early pregnancy loss, abortion, metritis, retained placenta, and culling rate at 120 d of the second, at the end of the second, and at the end of the third lactation was developed for a single pregnancy; we also developed 3 management options upon diagnosis of a twin pregnancy: (1) do nothing, (2) induce abortion using PGF2α, or (3) attempt manual embryo reduction. A value was given to each branch of the tree by simulating cow states on a farm for 1,400 d to encompass 4 consecutive lactations. The incomes considered in the simulations included milk income over feed cost, income from calves, and slaughter value upon culling. The expenses taken into account depending on each branch included additional inseminations and synchronization protocols, embryo reduction, induction of abortion, replacement heifers, and costs due to metritis and retained placenta. The gross value for a singleton pregnancy and the 3 management options upon diagnosis of a twin pregnancy were calculated by adding the value of all braches multiplied by their probability. The costs for the 3 management options were calculated by subtracting its gross value minus the gross value of a singleton pregnancy. The negative economic impact of a twin pregnancy ranged from $97 to $225 depending on the type of twin pregnancy (unilateral vs. bilateral), parity, and DIM when the twin pregnancy occurred. The overall negative economic impact of twinning on dairy farm profitability in the United States was estimated to be $96 million per year. Attempting manual embryo reduction early during gestation upon diagnosis of a twin pregnancy was the optimal management strategy for mitigating the negative economic impact of twinning under a wide variety of scenarios. [ABSTRACT FROM AUTHOR]