Marginal Cost Analysis Research Articles

Targeting waterfowl habitat restoration in the Prairie Pothole Region: A spatial analysis of marginal benefits and costs

Federal, state, and local government conservation program operators and policy-makers may wish to maximize benefits relative to costs, but have few economic measures to draw upon. The objective of this research is to estimate the costs of restoring and preserving prairie pothole wetlands and the value of their duck hunting benefits. The Prairie Pothole Region (PPR) lies in the north-central plains of the United States and produces 50% to 80% of all North American ducks. The ducks fly all major US flyways; hence they benefit hunters across the country. Historical data are used to estimate a wetland cost function that generates county-level estimates of the cost of restoring and preserving wetlands. Data availability limited the number of model variables so that coefficients are likely to be bias. Nonetheless, the model demonstrates predictive capability with an adjusted R2 of 0.74. To estimate benefits, we first developed geographic information system (GIS) models—one for each of five species—that predict the numbers of ducks produced by a new wetland by 1 km2 (0.4 mi2) grid point. Findings of previous research provide a quantitative link between changes in duck numbers and changes in hunting quality. We then use benefits transfer to value changes in hunting quality. Results reveal benefit-cost ratios ranging from near-zero to over nine.

Total and Marginal Cost Analysis for a High School Based Bystander Intervention

ABSTRACTCosts of providing the Green Dot bystander-based intervention, shown to be effective in the reduction of sexual violence among Kentucky high school students, were estimated based on data from a large cluster-randomized clinical trial. Rape Crisis Center Educators were trained to provide Green Dot curriculum to students. Implementing Green Dot in schools (N = 13) randomized to the intervention, over five years, cost $1.6 M and included start-up ($58 K) and ongoing implementation ($1.55 M). Costs for adding a school ($25,510) were calculated based on the final year, where no start-up costs were incurred. Knowing the $25,510 cost estimate for adding Green Dot may be particularly useful for high school administrators or school boards when they were making economic decisions based on strong evidence of program effectiveness to reduce violence.

Assessment on the Cohesion Pattern of Rail Transit: Integration of Rough Set and Grey Correlation Theory

Most existing project assessment relies on expert scoring, whose precision can be deteriorated by personal subjectivity. This paper presents an assessment method to compare the advantages and disadvantages of three cohesion patterns between suburban and urban rail transit network, which reduces the influence of subjective score. A modified rough set – grey correlation model is developed as a core of this assessment, based on the integration of rough set theory and grey correlational analysis, where an index system is set up for model calculation. A case study using the network in Ningbo is applied to demonstrate the effectiveness of the method, the results show that the method is more effective using discretely distributed data sensitive to sample size. The consistency of the results in comparison with marginal cost analysis can be a preliminary verification of the model.

상향식 접근법에 의한 국내 시설재배 에너지부분의 온실가스 배출량 및 감축 잠재량 분석

A bottom-up approach has been conducted to estimate greenhouse gas (GHG) emission and to analyze the marginal abatement cost for the Korean horticulture energy sector. With the systematically derived activity and energy balance data, the BAUs have been estimated, along with the marginal abatement cost over the period 2010 through 2030. The result from the marginal abatement cost analysis may provide general guidelines and procedures for the establishment of GHG abatement polices.

Optimal economic dispatch model based on risk management for wind‐integrated power system

In recent years, the proportion of wind power capacity is increased dramatically for carbon emissions reduction in several countries. However, wind power generation cannot be dispatched as conventional thermal power generation because of its randomness and intermittency. To deal with the increased uncertainty, a probabilistic model is established to analyse the uncertainty of wind power and load. Conditional value at risk index is applied to assess risk including the loss of load and `spilling' wind energy associated with unpredictable imbalances between generation and load. The cost-risk model is proposed by minimising the operation cost and risk in optimal economic dispatch problem. The study uses multiple objective particle swarm optimisation to solve the model and obtain the Pareto-optimal solutions, which can reflect the relationship between risk and cost. The optimal solution can be determined in Pareto-optimal set by risk management method based on analysis of the risk marginal cost. The model and methods are tested on the IEEE 30-bus power system. The results demonstrate the proposed method can control the cost and risk in effective way.

Integration of optimal storage operation into marginal cost curve representation

In the economic dispatch problem, the objective is to supply the demand at least cost. It is a well known fact that the solution to this problem corresponds to the generation settings that lead to equal marginal/incremental costs for all generators and for which the total generation output is equal to the total load. This provides a way to determine the solution to the economic dispatch problem by simply considering the marginal cost curves of the generators and the demand curve. In this paper, we integrate the effect of storage into this marginal cost analysis. This requires the consideration of conversion losses occurring in the storage converter, the extension to a multi-step optimization problem and the limitations imposed by the limited energy storage capacity. A method is provided by which the optimal generation and storage settings can be determined by only using marginal cost curves and the intersections thereof. Simulation results provide insights into how the theory translates into solving a multi-step optimization problem including storage.

상향식 모형을 이용한 국내 주거부문의 온실가스 한계감축비용 분석

A marginal abatement cost analysis has been conducte d to analyze the effects of abatement measures on greenhouse gas (GHG) emissions for the Korean residential sector. A bottom-up model using MESSAGE has been developed by defining the energy demand and constructing the reference energy system for the residential sector. A great amount of activity data has also been analyzed. Abatement potentials and related costs of individual abatement measures are investigated. The result from the marginal abatement cost analysis may provide general guidelines and proc edures for the establishment of GHG abatement polices.

Quantifying the Optimum Number of Proton Fields in Treatment of Midline Tumors Using a Marginal Cost Analysis

We have previously described the application of proton therapy for midline central nervous system (CNS) tumors, using from 1 to 5 midline sagittal beams to target superficial and deep seated tumors while sparing the hippocampi and temporal lobes. In our previously reported cohort, the number of beams used was driven by individual physician judgment, balancing improved dose conformality against the cost of increased integral brain dose. We sought to build a model of proton treatment to quantify the competing demands of conformality and integral dose in an effort to identify the optimal number of beams in this technique.

Marginal cost analysis of two train-the-trainer models for implementing SafeCare(®).

In adopting evidence-based practices (EBP), program administrators most frequently focus on program effectiveness. But there is growing recognition of the importance of program cost and of economic analysis for allocating scarce resources for prevention and intervention programs.1 Economic analysis includes the assessment of programmatic costs using a micro-costing approach (precise individual resource valuation) to value the resources required to implement programmatic processes and activities so that programs can be compared to each other.2–5 Differences in program cost are typically driven by differences in program length, staff requirements to implement the program and materials. However, another key source of program cost is the implementation strategy. Program administrators must consider the costs to adopt or implement a program. Translation or implementation science focuses on the processes by which EBP are implemented. Less rigorous implementation procedures often fail to yield implementation with fidelity, which is needed to achieve program outcomes.6 More rigorous strategies are more expensive, but there is evidence that they are needed to achieve implementation with fidelity.7,8 Thus, the consideration of implementation costs is an important area of study. That is, just as intervention scientists have studied how much intervention is needed for behavior change, implementation scientists must study how much implementation is necessary to achieve fidelity. To date, however, few studies have considered costs in implementation research,9 and fewer still have specifically focused on the costs of implementing EBP in the field of child maltreatment (CM) prevention.10 To our knowledge there are no studies that have calculated implementation costs for variants on a model and then related those costs to implementation outcomes. This paper presents a calculation of marginal implementation costs for 2 variants of a training program for the SafeCare® model, an evidence-based parenting model for child maltreatment prevention. SafeCare® has been disseminated to child welfare systems across 20 U.S. states. The SafeCare® dissemination model includes a “train-the-trainer” component in which staff external to the purveyor (the National SafeCare® Training and Research Center [NSTRC]) are trained over time to train local staff. The training of trainers is notoriously difficult and often fails because of the lack of follow-up support.11 In the study reported here, we trained trainers under 2 different models to examine the impact of trainee and client outcomes. A first step in understanding the impact of the 2 models is to calculate marginal cost differences in the 2 training models. The 2 training models differed primarily in their provision of support to new trainers following completion of the train-the-trainer program. Trainers were randomly assigned into 1 of 2 models for training, standard or enhanced. In the “standard” approach, the model includes a 5-day workshop with skill demonstration and proficiency improvement through role-playing activities and live training sessions. The model includes some ongoing support from NSTRC training staff, and in turn, trainers provide some support to the providers they train. The second model, the “enhanced” approach, provided extensive ongoing consultation from NSTRC training staff for 6 months upon completion of the trainer training workshop. In this paper, we present data collected to determine marginal cost differences between the 2 models. Although we do not present data on implementation and client outcomes, this paper serves as an example of how data collection on this topic can be accomplished and how marginal costs are computed.

Optimization of the gas production rate by marginal cost analysis: Influence of the sales gas pressure, gas price and duration of gas sales contract

The development of a gas field requires accurate planning, but the gas production rate is one of the main challenges in determining the feasibility of a gas project. An optimum gas production rate is determined not only by the gas reserve and reservoir characteristics but also by the consumer's requirements of the sales gas pressure, duration of the gas sales contract and gas price. This paper presents a gas production optimization model based on the marginal cost approach to maximize economic profit using a case study in the Donggi gas field. The results reveal that increasing the sales gas pressure and gas price raises the optimum gas production rate and increases the maximum profit; meanwhile, increasing the duration of a gas sales contract will reduce the optimum gas production rate and reduce or increase the maximum profit depending on the gas reserve and reservoir characteristics. This work clearly shows the relationship between the user's requirements and optimum gas production rate, which is an important piece of information for negotiating the gas price and planning production.

Low carbon society scenario 2050 in Thai industrial sector

Energy plays a dominant role in determining the individual competitiveness of a country and this is more relevant to emerging economies. That being said, energy also plays an important and ever expanding role in carbon emissions and sustainability of the country. As a developing country Thailand’s industrial sector is vibrant and robust and consumes majority of the energy. In addition, it also has the highest CO2 emissions, provided the emissions of power generation are taken into account. Industry also accounts for the highest consumption of electricity in Thailand. The objective of this study is to model the Thai industrial energy sector and estimate the mitigation potential for the timeframe of 2010–2050 using the principles of Low Carbon Society (LCS). In addition, the paper would also evaluate emission tax as a key driver of Greenhouse Gas (GHG) mitigation along with Marginal Abatement Cost (MAC) analysis. Another secondary objective is to analyse the impact of mitigation on energy security of the industrial sector. The Thai industrial sector was modelled using AIM/Enduse model, which is a recursive dynamic optimisation model belonging to the Asia–Pacific Integrated Model (AIM) family. Thai industrial sector was divided into nine sub-sectors based on national economic reporting procedures. Results suggest that the mitigation potential in 2050, compared to the Baseline scenario, is around 20% with positive impacts on energy security. The Baseline emission will approximately be 377 Mt-CO2 in the industrial sector. All four indicators of energy security, Primary Energy Intensity, Carbon Intensity, Oil Share and Diversification of Fuel Share would exhibit enhanced energy security levels. The new Counter Measures (CM) proposed, such as, new and advanced technologies and fuel switching would drive the mitigation levels. Increase in energy efficiency of heating and electricity use would reduce the primary energy demand and intensity.

BBLAWN: A Combined Use of Best Management Practices and an Optimization Model Based on a Pseudo-Genetic Algorithm

Abstract The paper presents a solution to the problem of the Battle of Background Leakage Assessment for Water Networks (BBLAWN) using a methodology that combines the use of Best Management Practices (BMPs) and an optimization model based on a Pseudo-Genetic Algorithm (PGA) as described in [1] . In a first stage, an analysis of marginal costs of pipes whose replacement would be potentially recommended was performed. Next, a network topological analysis to study the pipes that could potentially be closed in order to facilitate pressure control was done. Furthermore, a methodology for studying branched areas was also developed, determining possible location for pressure reducing valves (PRV). A significant reduction in the number of decision variables was obtained and a specific optimization model was developed.

Production Optimization for Plan of Gas Field Development Using Marginal Cost Analysis

Gas production rate is one of the most important va riables affecting the feasibility plan of gas field development. It take into account reservoir characteristics, gas reserve s, number of wells, production facilities, governme nt take and market conditions. In this research, a mathematical model of gas production optimization has been developed u sing marginal cost analysis in determining the optimum gas produc tion rate for economic profit, by employing the cas e study of Matindok Field. The results show that the optimum gas production rate is mainly affected by gas price duration and time of gas delivery. When the price of gas increas es, the optimum gas production rate will increase, and then it will become closer to the maximum production rate of the reservoir. Increasing the duration time of gas del ivery will reduce the optimum gas production rate and increase maximum profit non-linearly.

Modeling and Analysis of Integrated Planning of Production and Engineering Process Improvement

A clearing function that can capture the nonlinear relationship between workloads and throughput and also reflect capacity improvement by engineering activities on a multioperation workcenter is developed. The clearing function is then used to formulate an integrated optimization model for planning both production and engineering process improvement. Marginal cost analysis using the Karush-Kuhn-Tucker optimality conditions provides useful insights into effective management of resources in a reentrant manufacturing system.

Abstract P38: The BRIDGE Transitional Care Model Demonstrates Cost-Effectiveness

Background: Readmission rates following discharge for a cardiac condition are common and costly. Compared to usual care (UC) the NP transitional care model (BRIDGE) reduced hospital readmissions in the pilot study. To determine if there is also a cost savings, we compared the costs of BRIDGE against avoided readmission and hypothesized that participation would reduce overall costs. Methods: Demographic, clinical, and f/u data were collected retrospectively on all pts referred to BRIDGE June 2008 to Aug 2009. Pts readmitted before their BRIDGE appt were excluded. Incremental costs were obtained from the institution's finance dept. MEDPAR charge data were obtained from the American Hospital Directory for the MS-DRG of cardiology. Results: Of 426 patients referred to BRIDGE, 284 (69.8%) attended, the rest received UC. Most were male (56.6%), mean age 63.4, without significant baseline differences between groups. BRIDGE participants were readmitted less frequently and were less costly (17.4% vs. 19.6%, p=.65). The incremental cost for a BRIDGE visit was $43.85 per pt compared to the avg Medicare charge for a cardiology admission of $27,558. The reduction in expected readmissions for BRIDGE pts, compared to incremental BRIDGE costs, translates into a $562 per patient savings, or a $145,106 program savings in readmission costs over UC. Because this is a marginal cost analysis, a conservative adjustment was made to account for nonproductive time. Using a multiplier of 2.63%, there was still a per pt savings of $502 and a program savings of $129,618 in readmission costs over UC. Cost savings varied by readmission rates for primary diagnosis. ACS pts have an unadjusted per pt savings of $5,412 ($357,234 program savings) and CHF pts $149 per pt savings ($225,722 program savings) while afib pts increase cost by $3,599 per pt ($179,942 program cost). Conclusions: This analysis demonstrates that the BRIDGE model reduces health care costs associated with readmissions that are in excess of program costs despite the diverse population. Hospital revenue is not addressed because our perspective assumes that lower health care costs benefit all. Further, proposed legislation to reduce hospital reimbursement for readmissions may make this a mute issue.

A THEORY OF MULTIPLE VEHICLE TYPE DYNAMIC MARGINAL COST CONSIDERING DEPARTURE TIME CHOICES

The analysis of single vehicle type dynamic marginal cost is extended to multiple vehicle type dynamic one based on time‐dependent multiple vehicle type queue analysis at a bottleneck. First, a dynamic link model to rep‐ resent the interactions between cars and trucks is provided. Then, the analytic expression of a multiple vehicle type dynamic marginal cost function considering departure time choices is deduced under congested and un‐congested conditions and consequently, a dynamic toll function is given. A heuristic algorithm is introduced to solve multiple vehicle type dynamic queues and toll under system optimum and user equilibrium conditions taking into account traveler's departure time. A numerical example shows that a dynamic congestion toll can diminish queues and improve system conditions when traffic demand is not changed.

A note on how to compute economic order quantities without derivatives by cost comparisons: some comments

This paper discusses some points of the algebraic optimisation method and the cost comparisons optimisation method. Moreover, mathematical expressions are derived for the backorders level for the EOQ and EPQ inventory models with planned backorders that were not provided by the cost comparisons method using the well known marginal cost analysis and simple geometric relations.

Salient Features of a Lecture Course on Reliability Theory

The module ‘oReliability Modelling and Analysis’ has been taught by the author at the University of Bradford in the School of Informatics over several years. In this paper, four aspects of the lecture course are described. After reviewing the general course structure, we examine within the field of maintenance modelling the method of marginal cost analysis. The application of this technique is deemed to be novel in the present (teaching) context and it is intended to make a basically mathematical subject amenable also to engineers and economists. Next, we outline the use of the computer algebra package Maxima in teaching ‘reliability’. This is exemplified with a classroom example, an exercise and a coursework assignment. Experience shows that the use of Maxima enriches the teaching of reliability to aspiring practitioners. Finally, some general principles are reviewed which help the learner to keep an eye on the reasonableness of purported results, using properties such as model structure, model symmetry, dimensional correctness, boundary conditions, specialization and generalization.

Evaluation of exposure factors applied in marginal external cost analysis of transportation related air pollution

This paper evaluates different air quality models for estimation of exposure factors and their implication for assessing the marginal external pollution costs of transportation using the impact pathway methodology. An element of the impact chain is the relation between changes in population exposure due to a change in emissions including a regional exposure factor and a local exposure factor. The focus is on Danish national air quality and human exposure models. Comparisons are made with similar calculations using the European Commission’s EcoSenseTransport model that is based on a simpler regional air quality exposures model that generates regional exposure factors that are higher than the Danish models. These differences may be explained by variations in geographical coverage, and by different estimations of absolute levels of exposures within the same area. Local exposure factors are derived for different city sizes as well as rural areas to differentiate the marginal external costs by degree of urbanisation. The Danish models produced lower marginal external costs than the EcoSenseTransport model.

Very low risk for subsequent breast cancer in BRCA1/2 carriers after prophylactic mastectomy

Women with germline BRCA1 mutation have a significant risk of breast and/or ovarian cancer. Prophylactic bilateral mastectomy (PBM) and prophylactic bilateral salpingo-oophorectomy (PBSO) prevent cancer in mutation carriers.The cost-effectiveness of PBSO (age of 35 years) with or without PBM five years earlier was compared to a no intervention setting employing a marginal cost analysis. National data on cancer incidence, mortality rates and costs were implemented together with observed Norwegian BRCA1 data in a Markov model and PBSO was assumed to reduce the risk of ovarian cancer by 90%. A 3% discount rate was used.The additional health care cost per mutation carrier undergoing PBSO and PBM was €15,784, and 6.4 discounted life years gained (LYG) was indicated (PBSO alone with 100% acceptance 3.1 LYG). The additional cost per LYG was €1973 (PBSO alone €1749/LYG). Including all resource use, the figure was a cost of €496 and €1284 per LYG, respectively.PBSO with or without PBM in BRCA1 mutation carriers is cost-effective. A testing of all incident breast cancers to identify mutation carrying families should be explored.