Total Social Cost Research Articles

An Analysis of Social Cost in School Level Education of Nepal

Social costs in education plays decisive role for education development and economic growth of a nation. In this context, this article tries to analyze the size, trend and growth rate of social cost in the education sector of Nepal by disaggregating it into total social cost, recurrent social cost, capital social cost, unit cost and marginal cost in community based school education of Nepal. The study is based on the secondary data obtained from official documents of Nepal’s Government such as flash report, budget speech, red book and so on. The time series data from 2011 AD to 2015 AD were collected for the analysis by using convenience non-random sampling method. The overall finding of the study shows that the share of the annual average social cost in education is 15.84 percent of the total cost of the government of Nepal. In other words, the government has allocated annual average Rs 68930697.6 thousands as social cost in educational sector during the study years. The average annual growth rate of this cost is 5.15 percent. The study also indicates that annual average total social cost is Rs 68930697.6 thousands, recurrent social cost is Rs 5,71,63,418.79 thousands and capital social cost is Rs 1,17,67,278.81 thousands in Nepal. Similarly, annual average total social cost is estimated to be Rs 3,33,35,928.80 thousands. The total social unit cost per teacher and total social unit cost per student are Rs 196.39 thousands and 5.51 thousands respectively. The annual average marginal social cost per teacher and marginal social cost per student are Rs 1308.08 thousands and -202.96 thousands respectively. The negative sign indicates that student enrolment has decreased over the study period. The findings of the study conclude that there is no any predictable relationship among student enrolment, teaching and non-teaching staffs and social cost of education in case of Nepal. However, UNESCO (1999) had analyzed public investment on education of 16 countries and it found that their average investment on education was 19.2 percent of GDP. Therefore, Nepal government should increase in educational investment from its current status of 15.80 percent to at least more than it in the coming years to develop educational sector of Nepal.

The total social costs of constructing and operating a maglev line using a case study of the riyadh-dammam corridor, Saudi Arabia

Background: Introducing Magnetic Levitation (Maglev) technology in a developing country is a big challenge that needs huge investments in infrastructure, operations and maintenance. Background information about the development of Maglev worldwide to date is included.
 Aim: Determine a methodology to estimate the full cost of travel and provide insights into the working model developed to include the calculations of the total social costs of building a new Maglev line for the Riyadh-Dammam corridor in Saudi Arabia and understand in what circumstances it is a suitable technology to use.
 Methods: The Spreadsheet Total Cost Model (STCM) is used to determine the calculations of operator costs, user costs, and environmental costs. However, the operator costs are related to infrastructure construction and maintenance costs, and costs associated with the acquisition, operation and maintenance of Maglev rolling stock. The user costs are dependent on the journey time, including access/egress time, waiting time, and in-vehicle time. The value of time is considered in order to get the user costs calculated. The external costs include air pollution, noise pollution, accident, and climate change per passenger-km.
 Results: The travel demand has to be forecasted in order to determine the total social costs, using the elasticity approach between the the proposed HSR and Maglev lines in terms of their number of trips and the generalised journey times. In addition, the generalised journey time is based on the in-vehicle time and service interval penalty. The Maglev system is operated at the capacity limit and the change in service is therefore forecasted to increase the Maglev demand by 24.6 % (3.25 million passengers). In terms of the total infrastructure costs, the infrastructure construction and maintenance costs are included and computed to be about € 835.4 million per year, using the capital recovery factor (0.06) based on 35 years of operation and a 5 % social discount rate. The acquiring, operating, and maintaining train’s unit cost is included in the calculation of rolling stock to achieve results of € 22.4 million, € 22.5 million, and € 40.9 million, respectively. In terms of the user costs, the access/egress time is computed as of 33 minutes, using the car, while the in-vehicle travel time and waiting time are resulted of 61.8 minutes and 7.8 minutes, respectively. The external environmental costs are based on accidents, and climate changes of € 8.87 million per year and € 8.13 million per year, respectively. However, the total social costs of Maglev line are computed as € 1.18 billion for 16.45 million passengers per year. This gives an average social cost of € 71.9 per passenger. The comparable figures for High-Speed Rail (HSR) are € 1.10 billion for 13.21 million passengers per year, giving an average social cost of € 83 per passenger.
 Conclusion: In conclusion, the Riyadh-Dammam Maglev system introduces a new intercity system into Saudi Arabia and brings new competition in the intercity transit market as a part of the future transport developments in the country. The average social cost for HSR is around 16 % higher than Maglev- but that is more proven technology.

Strengthening the evidence-base of integrated care for people with multi-morbidity in Europe using Multi-Criteria Decision Analyses MCDA

The evaluation of integrated care programmes for individuals with multi-morbidity requires a broader evaluation framework and a broader definition of added value than is common in cost-utility analysis. This is possible through the use of Multi-Criteria Decision Analysis MCDA. This paper describes the seven steps of an MCDA approach to evaluate 17 different integrated care programmes for individuals with multi-morbidity in 8 European countries that partake in the SELFIE project, a four-year EU-funded project. In step one, qualitative research is undertaken to better understand the decision-context of these programmes. The programmes face decisions related to their sustainability in terms of their reimbursement, continuation, extension, and/or wider implementation. In step two, a uniform set of decision criteria was defined in terms of eight outcomes measured across the 17 programmes: physical functioning, psychological wellbeing, social relationships and participation, enjoyment of life, resilience, person-centeredness, continuity of care, and total health and social care costs. These are supplemented by programme-type specific outcomes. Step three describes the quasi-experimental studies designed to measure the performance of the programmes on the decision criteria. Step four gives the details of the two methods Discrete Choice Experiment and Swing Weighting to determine the relative importance of the decision criteria among five groups of stakeholders in each country. Step five describes the value-based method of MCDA by which the performance of the programmes on each decision criterion is combined with the weight of the respective criterion, to come to an overall value score. Step six describes how we deal with uncertainty and introduces the Conditional Multi-Attribute Acceptability Curve. Step seven addresses the interpretation of results in stakeholder workshops. By discussing the challenges involved in creating a uniform MCDA approach for the evaluation of different programmes, this paper provides guidance to future evaluations and stimulates debate on how to properly evaluate integrated care for individuals with multi-morbidity.

Supply location and transportation planning for hurricanes: A two-stage stochastic programming framework

We develop a two-stage stochastic programming model with recourse actions for hurricane preparedness. In the first stage, it works to optimize the locations of Points of Distribution (PODs), medical supply levels, and transportation capacity, and in the second, transportation decisions or flow. Our model minimizes the total social cost, comprised of deprivation and commercial logistics costs. Contrary to the extant literature, which typically employs robust optimization, we use probability distributions to avoid overly conservative estimates of hurricane impact. Additionally, our model facilitates the determination of optimal deployment time. We demonstrate the benefits of our approach in a case study. As risk attitude goes from optimistic to pessimistic, decision makers increase the number of PODs exponentially to spread the risk around. A similar trend holds for total costs as a function of hurricane category and its interplay with risk. Further, for lower strength hurricanes, regardless of risk attitude, the optimal decision is to deploy closer to landfall at 12 hours; for higher strength hurricanes, resources are best deployed earlier, at 36 hours, based on an exponential increase in demand for medical supplies. Deployment cost also increases exponentially as landfall approaches. These costs outweigh deprivation savings from an accurate demand estimate closer to landfall. However, when budget is limited, risk attitude is found to influence deployment decisions and a funding preference for lower severity-level supplies.

Strengthening the evidence-base of integrated care for people with multi-morbidity in Europe using Multi-Criteria Decision Analysis (MCDA)

BackgroundEvaluation of integrated care programmes for individuals with multi-morbidity requires a broader evaluation framework and a broader definition of added value than is common in cost-utility analysis. This is possible through the use of Multi-Criteria Decision Analysis (MCDA).Methods and resultsThis paper presents the seven steps of an MCDA to evaluate 17 different integrated care programmes for individuals with multi-morbidity in 8 European countries participating in the 4-year, EU-funded SELFIE project. In step one, qualitative research was undertaken to better understand the decision-context of these programmes. The programmes faced decisions related to their sustainability in terms of reimbursement, continuation, extension, and/or wider implementation. In step two, a uniform set of decision criteria was defined in terms of outcomes measured across the 17 programmes: physical functioning, psychological well-being, social relationships and participation, enjoyment of life, resilience, person-centeredness, continuity of care, and total health and social care costs. These were supplemented by programme-type specific outcomes. Step three presents the quasi-experimental studies designed to measure the performance of the programmes on the decision criteria. Step four gives details of the methods (Discrete Choice Experiment, Swing Weighting) to determine the relative importance of the decision criteria among five stakeholder groups per country. An example in step five illustrates the value-based method of MCDA by which the performance of the programmes on each decision criterion is combined with the weight of the respective criterion to derive an overall value score. Step six describes how we deal with uncertainty and introduces the Conditional Multi-Attribute Acceptability Curve. Step seven addresses the interpretation of results in stakeholder workshops.DiscussionBy discussing our solutions to the challenges involved in creating a uniform MCDA approach for the evaluation of different programmes, this paper provides guidance to future evaluations and stimulates debate on how to evaluate integrated care for multi-morbidity.

A scenario-based planning framework for energy storage systems with the main goal of mitigating wind curtailment issue

This paper provides a new multi-objective (MO) framework for expansion studies of energy storage systems (ESSs) in high wind penetrated power system. The proposed approach well considers the issues originated from the wind power curtailment via introducing expected of wind curtailment cost as an objective function of the studies. All other imposed costs of installing storage units are modeled as expected of total social cost. Also, the effect of uncertainties is modeled through an internal scenario analysis. In this regard, two criteria including maximum regrets of wind curtailment cost and total social cost are considered as the other objectives of the proposed MO optimization procedure. These all the crucial and maybe contradictory aspects of the ESSs expansion problem are treated via a Posteriori MO optimization algorithm, i.e. the Non-dominated Sorting Genetic Algorithm II (NSGA II). The proposed methodology is implemented on the modified IEEE 24-bus test system and its anticipated applicability is well verified.

A Green Quality Management Decision Model with Carbon Tax and Capacity Expansion under Activity-Based Costing (ABC)—A Case Study in the Tire Manufacturing Industry

Issues related to global environmental protection are highly important. Under the global trend of energy saving and carbon reduction, in order to lower the carbon emissions of products or services offered by enterprises, the Taiwanese government aims to control carbon emissions by constructing a carbon tax system and mandating enterprises to pay a carbon tax. The collection of a carbon tax can minimize the total social environmental cost and increase the efficiency of carbon reduction; the need to control the green quality cost can serve as a criterion of green management decision-making. This study aimed to reorganize carbon emissions in different stages of production in order to lower the total carbon emissions of products. Activity-based costing (ABC) was adopted to assess green quality management and production cost. The optimal green quality production portfolio was selected via a mathematical programming model to focus on the expansion of productivity and outsourcing strategy in order to effectively lessen the harmful effects on the environment and maximize profits. Besides academic contributions, the findings of this study could serve as a reference to enterprises on assessing the effects of carbon emissions, carbon taxes, and environmental management on production decision-making.

Bi-Level Planning Model of Charging Stations Considering the Coupling Relationship between Charging Stations and Travel Route

The major factors affecting the popularization of electric vehicles (EV) are the limited travel range and the lack of charging infrastructure. Therefore, to further promote the penetration of EVs, it is of great importance to plan and construct more fast charging stations rationally. In this study, first we establish a travel pattern model based on the Monte Carlo simulation (MCS). Then, with the traveling data of EVs, we build a bi-level planning model of charging stations. For the upper model, with an aim to maximize the travel success ratio, we consider the influence of the placement of charging stations on the user’s travel route. We adopt a hybrid method based on queuing theory and the greedy algorithm to determine the capacity of charging stations, and we utilize the total social cost and satisfaction index as two indicators to evaluate the optimal solutions obtained from the upper model. Additionally, the impact of the increase of EV ownership and slow charger coverage in the public parking lot on the fast charging demands and travel pattern of EV users are also studied. The example verifies the feasibility of the proposed method.

Optimal quotation and institutional cost model in market maker quotation transaction

Emission trading can not only significantly improve the environment quality, but also save the total social cost. The emission trading market can only overcome the market failure caused by externalities only if it has good transaction efficiency, and the market pricing system is the most direct factor that affects transaction efficiency. This paper constructs a three-party dynamic game model for market maker’s quotation trading to study the forming mechanism of the market maker’s optimal quotation, and constructs an institutional cost model for market maker’s quotation trading to compares the institutional costs of the market maker system. The study found that: (1) The optimal quotation of market makers is affected by marginal information costs, marginal pollution control costs, and initial allocation of emission permits. (2) The high cost of market information, the extremely uneven initial allocation of emission permits, and the free allocation scheme based on historical emissions may all lead to inefficient transactions. (3) When the trading volume is the same, compared with the competitive bidding mechanism, market maker quotes can save social information costs in the large-scale market. The study results of this paper can provide a theoretical basis for the development of China’s emission permits trading.

Improving the Penetration of Wind Power with Dynamic Thermal Rating System, Static VAR Compensator and Multi-Objective Genetic Algorithm

The integration of renewable energy sources, especially wind energy, has been on the rise throughout power systems worldwide. Due to this relatively new introduction, the integration of wind energy is often not optimized. Moreover, owing to the technical constraints and transmission congestions of the power network, most of the wind energy has to be curtailed. Due to various factors that influence the connectivity of wind energy, this paper proposes a well-organized posterior multi-objective (MO) optimization algorithm for maximizing the connections of wind energy. In this regard, the dynamic thermal rating (DTR) system and the static VAR compensator (SVC) have been identified as effective tools for improving the loadability of the network. The propose MO algorithm in this paper aims to minimize: (1) wind energy curtailment, (2) operation cost of the network considering all investments and operations, also known as the total social cost, and (3) SVC operation cost. The proposed MO problem was solved using the non-dominated sorting genetic algorithm (NSGA) II and it was tested on the modified IEEE reliability test system (IEEE-RTS). The results demonstrate the applicability of the proposed algorithm in aiding power system enhancement planning for integrating wind energy.

Network-based optimization modeling of manhole setting for pipeline transportation

This study proposes a network-based methodology for the optimization of manhole setting problem, which is a key component of pipeline transportation. The objective is to minimize the total social cost which involves the construction cost and the maintenance cost including the negative impact of manholes on the ground transportation. We first consider a special model which is efficiently solved by a topological sort-based approach. Later, we build a generic model and prove it to be NP-hard. A metaheuristic method is developed to obtain good-quality solutions. Finally, the models and solution methods are validated by numerical examples.

Including deprivation costs in facility location models for humanitarian relief logistics

Humanitarian assistance is meant to save lives and alleviate human suffering during and in the aftermath of man-made and natural disasters. To prevent and strengthen preparedness for the occurrence of such situations, having available relief supplies in the short-term becomes crucial. The lack of access to life-sustaining items implies a loss in people's welfare, treated as an externality called deprivation costs which must be incorporated into decision-making processes. Since typical humanitarian applications are extensions of commercial logistic models, they usually do not account for externalities, leading to high social costs and likely to unfeasible or suboptimal solutions.This paper develops a facility location model for prepositioning supplies in preparation for disasters; the key feature of this formulation being the fact that it explicitly considers deprivation costs in the objective function. The model attempts to minimize the global social costs, as the sum of both private costs (i.e. costs of transportation, inventory costs and fixed costs of facilities) and deprivation costs, determining the amount per type of product to be prepositioned for serving the areas affected by a disaster during the initial response. The model focuses on those assistance interventions that should be carried out immediately, i.e. within the first 24 h of a humanitarian crisis. We applied the model, using real information, to the Colombian Caribbean region, which was affected by floods in 2010 and 2011. Results demonstrate that deprivation costs represent more than 50% of the total social cost.

A Comparison of Different Approaches for Costing Medication Use in an Economic Evaluation

BackgroundEstimating individual-level medication costs in an economic evaluation can involve extensive data collection and handling. Implications of detailed versus general approaches are unclear. ObjectivesTo compare costing approaches in a trial-based economic evaluation. MethodsWe applied four costing approaches to prescribed medication data from the Tumour necrosis factor inhibitors Against Combination Intensive Therapy randomized controlled trial. A detailed micro-costing approach was used as a base case, against which other approaches were compared: costing medications used by at least 1.5% of patients; costing medications on the basis of only chemical name; applying a generic prescription charge rather than a medication-specific cost. We quantitatively examined resulting estimates of prescribed medication and total care costs, and qualitatively examined trial conclusions. ResultsMedication costs made up 6% of the total health and social care costs. There was good agreement in prescribed medication costs (concordance correlation coefficient [CCC] 0.815, 0.819, and 0.989) and excellent agreement in total costs (CCC 0.990, 0.995, and 0.995) between approaches 1 and 2. Approaches 3 and 4 had poor agreement with approach 1 on prescribed medication costs (CCC 0.246–0.700 and 0.033–0.333, respectively), but agreement on total care costs remained good (CCC 0.778–0.993 and 0.729–0.986, respectively). ConclusionsBecause medication costs comprised only a small proportion of total costs, the less resource-intensive approaches had substantial impacts on medication cost estimates, but had little impact on total care costs and did not significantly impact the trial’s cost-effectiveness conclusions. There is room for research efficiencies without detriment to an evaluation in which medication costs are likely to form a small proportion of total costs.

Risk-sharing agreements to cover environmental damage: theory and practice

Mordernization has witnessed increasingly new industrial sectors which have the potential to create environmental disasters. The insolvency of risk creators in case of such disasters may lead to insufficient compensation as well as to a dilution of preventive incentives. Insurance is a traditional instrument to address these problems, but is subject to limitations such as the lack of information by the insurers on the risk and limited insurance capacity. The risk-sharing agreement is an alternative which is widely used in high-risk sectors but it received relative little attention in academic literature. This paper analyses the potential of risk-sharing agreements in minimizing total social costs of environmental harmful activities, in comparison with insurance. The comparison shows the advantage of risk-sharing agreements in terms of less demanding information requirements, allowing for mutual monitoring and the potential to reduce administrative costs. However, the analysis also shows that a few conditions need to be met for such advantages to be materialized. This paper then discusses a typology of various risk-sharing agreements and illustrates the different categories with examples from the maritime and nuclear sectors. Based on these experiences, this paper explores the possibilities to expand risk-sharing agreements to other policy areas where environmental risks may emerge.

Randomised controlled trial to improve health and reduce substance use in established psychosis (IMPaCT): cost-effectiveness of integrated psychosocial health promotion

BackgroundThere is mounting evidence that people with severe mental illness have unhealthy lifestyles, high rates of cardiovascular and metabolic diseases, and greater risk of early mortality. This study aimed to assess the cost-effectiveness of a health promotion intervention seeking to improve physical health and reduce substance use in people with psychosis.MethodsParticipants with a psychotic disorder, aged 18-65 years old and registered on an enhanced care approach programme or equivalent were recruited from community mental health teams in six mental health trusts in England. Participants were randomisation to either standard community mental health team care (treatment as usual) or treatment as usual with an integrated health promotion intervention (IMPaCT). Cost-effectiveness and cost-utility analyses from health and social care and societal perspectives were conducted alongside a cluster randomised controlled trial. Total health and social care costs and total societal costs at 12 and 15 months were calculated as well as cost-effectiveness (incremental cost-effectiveness ratios and cost-effectiveness acceptability curves) at 15 months based on quality of life (SF-36 mental and physical health components, primary outcome measures) and quality adjusted life years (QALYs) using two measures, EQ-5D-3 L and SF-36. Data were analysed using bootstrapped regressions with covariates for relevant baseline variables.ResultsAt 12-15 months 301 participants had full data needed to be included in the economic evaluation. There were no differences in adjusted health and social care costs (£95, 95% CI -£1410 to £1599) or societal costs (£675, 95% CI -£1039 to £2388) between the intervention and control arms. Similarly, there were no differences between the groups in the SF-36 mental component (−0.80, 95% CI -3.66 to 2.06), SF-36 physical component (−0.68, 95% CI -3.01 to 1.65), QALYs estimated from the SF-36 (−0.00, −0.01 to 0.00) or QALYs estimated from the EQ-5D-3 L (0.00, 95% CI -0.01 to 0.02).Cost-effectiveness acceptability curves for all four outcomes and from both cost perspectives indicate that the probability of the health promotion intervention being cost-effective does not exceed 0.4 for willingness to pay thresholds ranging from £0-£50,000.ConclusionsAlongside no evidence of additional quality of life/clinical benefit, there is also no evidence of cost-effectiveness.Trial registrationISRCTN58667926. Date retrospectively registered: 23/04/2010. Recruitment start date: 01/03/2010.

The optimal research and development portfolio of low-carbon energy technologies: A study of China

To support decision-making for an optimal portfolio strategy for low-carbon energy technology research and development (R&D), this study proposes a dynamic two-stage stochastic programming model, taking into account both the uncertainty of technological change and damages of climate change. Based on China's economic and technology level and expert elicitation, an R&D investment portfolio strategy looking at three low-carbon technologies (carbon capture and storage [CCS], solar photovoltaic [PV], and nuclear), including nine projects, is investigated through the proposed model. The optimized results show that the optimal R&D technology portfolio is robust to different levels of risk in climate damage. However, the total social costs for the optimal R&D technology portfolio is lowest in the medium risk of climate damage scenario. Under different opportunity costs, the composition of the optimal R&D portfolio varies. However, projects for each of the three technologies always constitute the optimal R&D portfolio. Furthermore, the implication is that a technology synergistic R&D strategy is conducive to enhancing the level of CO2 abatement and reducing the total social cost.

SOCIAL COST OF IMPROPER LAND AND VARIETY SELECTION IN PADDY PRODUCTION IN TURKEY

For last decades, efficient use of land as a natural resources has the priority at the agenda of policy makers. Allocating farm land to optimal crop and selecting proper crop variety is vital to reach not only economically, but also environmentally efficient farming. Therefore, the study examined the social cost of improper land and crop variety selection in paddy production in Samsun province of Turkey. Research data were collected from both field experiment and 45 paddy producers by using questionnaire. Classical economic analysis procedures and cost calculation methods were followed. Economic losses sourced from improper land allocation and wrong variety selection in paddy production was calculated by combining individual and social losses. Research results showed that average paddy producers conducted their activities in S2 class lost 1983 kg per hectare of paddy, which was valued $595, due to improper land and variety selection. 64% of it was sourced from improper land selection, while that of improper paddy variety selection was 36%. However, average paddy producers conducted their activities in S3 class lost 3012 kg of paddy per hectare, which was valued $900. Research results also showed that social cost of improper land and variety selection in Samsun was $2,1 million. 62% of total social cost sourced from S2 class land, while that of S3 and S1 were 23% and 15%, respectively. 24% of the total social cost resulted from opportunity cost, while the rest attributed to improper land and variety selection in paddy production. Completing preparing activities the detail land use map and sharing with farmers in the research area may decrease the social cost of improper land and variety selection. Designing education program for farmers in order to make better variety and land selection and disseminate the information related variety and land selection via extension services may reduce the social cost of improper decision in the research area. Keywords: Turkey, paddy production, economic losses, improper selection, social cost

A dynamic parking charge optimal control model under perspective of commuters’ evolutionary game behavior

In this research we consider commuters’ dynamic learning effect by modeling the trip mode choice behavior from a new perspective of dynamic evolutionary game theory. We explore the behavior pattern of different types of commuters and study the evolution path and equilibrium properties under different traffic conditions. We further establish a dynamic parking charge optimal control (referred to as DPCOC) model to alter commuters’ trip mode choice while minimizing the total social cost. Numerical tests show. (1) Under fixed parking fee policy, the evolutionary results are completely decided by the travel time and the only method for public transit induction is to increase the parking charge price. (2) Compared with fixed parking fee policy, DPCOC policy proposed in this research has several advantages. Firstly, it can effectively turn the evolutionary path and evolutionary stable strategy to a better situation while minimizing the total social cost. Secondly, it can reduce the sensitivity of trip mode choice behavior to traffic congestion and improve the ability to resist interferences and emergencies. Thirdly, it is able to control the private car proportion to a stable state and make the trip behavior more predictable for the transportation management department. The research results can provide theoretical basis and decision-making references for commuters’ mode choice prediction, dynamic setting of urban parking charge prices and public transit induction.

Flood footprint of the 2007 floods in the UK: The case of the Yorkshire and The Humber region

International headlines over the last few years have been dominated by extreme weather events, and floods have been amongst the most frequent and devastating. These disasters represent high costs and functional disruptions to societies and economies. The consequent breakdown of the economic equilibrium exacerbates the losses of the initial physical damages and generates indirect costs that largely amplify the burden of the total damage. Neglecting indirect damages results in misleading results regarding the real dimensions of the costs and prevents accurate decision-making in flood risk management. To obtain an accurate assessment of total flooding costs, this paper introduces the flood footprint concept, as a novel accounting framework that measures the total economic impact that is directly and indirectly caused to the productive system, triggered by the flooding damages to the productive factors, infrastructure and residential capital. The assessment framework account for the damages in the flooded region as well as in wider economic systems and social networks. The flood footprint builds on previous research on disaster impact analysis based on Input-Output methodology, which considers inter-industry flows of goods and services for economic output. The framework was applied to the 2007 summer floods in the UK to determine the total economic impact in the region of Yorkshire and The Humber. The results suggest that the total economic burden of the floods was approximately 4% of the region's GVA (£2.7 billion), from which over half comes from knock-on effects during the 14 months that the economy of Yorkshire and The Humber last to recover. This paper is the first to apply the conceptual framework of flood footprint to a real past event, by which it highlights the economic interdependence among industrial sectors. Through such interrelationships, the economic impacts of a flooding event spill over into the entire economic system, and some of the most affected sectors can be those that are not directly damaged. Neglecting the impact of indirect damages would underestimate the total social costs of flooding events, and mislead the correspondent actions for risk management and adaptation.

Alternative representation of the deadweight loss triangle in oligopoly

PurposeThe purpose of this paper is to provide an alternative way of calculating the deadweight loss triangle in oligopolistic markets which takes inefficient use of inputs into account. The author shows that the result of the approach coincides with the one that exists in the economics literature. However, the author explicitly accounts for the inefficient use of inputs.Design/methodology/approachThe market supply curve that is extensively used for competitive markets has been reconsidered for the imperfectly competitive markets. The necessary condition for the efficient use of resources is investigated and a price level is derived at which the market output of oligopoly is produced efficiently. The degree of inefficient use of inputs is reported via the definitions of Input Inefficiency Measure (IIM) and the Ratio of Inefficient usage of Inputs to Total Deadweight Loss (RITD).FindingsThe author discovers that the area under the supply curve of the competitive market corresponds precisely to the minimum total costs of producing any given market output. To make this important finding operational in imperfectly competitive markets, the IIM reports the degree of distorted input allocation among firms with differentiated cost structures in producing a given equilibrium imperfectly competitive market output. In measuring the monopoly power, it is known that CRn or HHI market concentration indexes, which are calculated based on the market shares of firms regarding the demand side of the market, are widely used. The measures, which take into account of the distortions in input usage, and hence, the supply side may be considered as an additional index. For example, if the market demand were shared equally by two firms (no dominant firm with respect to the demand side), it is known that the leadership would still arise when the costs of firms differed as in the dominant firm model in favor of the lower cost producing firm.Research limitations/implicationsThe author recommends some more theoretical research extensions of the approach suggested here to other oligopolistic markets like the Cournot-Nash, the Stackelberg and other models. In all cases, there is a need for additional work to find some measurable variables in practice in order to estimate the input inefficiency given by the two measures and differentiate it from the inefficiency of units of outputs that are not produced.Practical implicationsIt may be interesting to decompose the various estimates of welfare losses due to monopoly power as a percentage of GNP that were discussed in the literature into two inefficiency components: units of outputs that are not produced and units of inputs that are misallocated among firms.Social implicationsThe government officials might be interested in assessing the degree of loss of input usage by firms in addition to output loss in oligopolistic markets summarized by the two inefficiency indexes. Law economists may be inspired in discussing the issue of input inefficiency in the context of on antitrust policy.Originality/valueThe author emphasized that the area under the market supply curve minimized the aggregate cost of producing a given total market output in competitive markets. Having recognized the importance of this finding, the author tried to apply it to imperfectly competitive markets and especially to the calculation of deadweight loss in such markets. The author showed that the total social cost could be calculated by including the input inefficiency which can be defined as the extra cost to society arising from not using the most appropriate economic resource allocation among firms in addition to the usual deadweight loss triangle. Moreover, the author had to introduce some more new terms like the market supply curve allocation, the adjusted competitive price, efficiency gain and so on, as they were necessary along the course of the analysis.