A microsimulation model of the health care system: the role of the hospital sector

A microeconometric model of the health care system of the United States was estimated by applying econometric techniques to extensive data. The model treats the microanalytic behavior of individuals and institutions comprising the health care system, and is structured in terms of five submodels pertaining to consumers, hospital and physician services, physician and nonphysician manpower. In each submodel there is an economic market on which demands and supplies from the individuals and institutions interact and on which the allocation of resources is determined. A detailed treatment of participant attributes facilitates study of the distributional impacts of alternative policies. This paper presents an overview of the complete system, and summarizes the relationships used for the hospital sector.     

Cross-country comparison of the efficiency of the European forest sector and second stage DEA approach

In this paper the relative efficiency of the forest sector of 28 EU/EFTA countries during the period 2010–2015 is assessed using Data Envelopment Analysis (DEA). Three non-discretionary inputs (persons employed, forest available for wood supply and initial growing stock) are considered. The outputs are roundwood production, gross value added and final growing stock. The proposed DEA model not only computes efficiency scores but also improvement targets. The countries with the lowest efficiency scores during the period under study are Greece, Bulgaria and Italy. In the second stage, a fractional regression model is fitted and the factors that have an influence on the estimated efficiency are identified. The factors that have an influence are GDP and belonging to the NORTH Europe and CENTRAL-WEST Europe regions. Quantitative estimates of the partial effects of these factors are provided. The results can contribute in providing guidance towards the best practice in roundwood production.

     

The computation of regionalized short-run marginal costs of electricity: The ARCOMALT model

Generation operation models, giving expected values of marginal fuel and failure costs, have been developed at EDF since about fifteen years. In order to study the regionalization of the future tariffs, we have recently developed a model for computing short-run marginal costs including not only generation but also the interconnection network. We shall first deal below with the necessary reduction of the general problem of optimization of the interconnection network operation before explaining how we solve the reduced problem.The French 400 kV interconnection network enables more than hundred plants to deliver electricity to consumers through more than hundred main nodes. The optimization of the operation has been examined for network planning and has led to a separation between shortage cases (for which additional outage due to the network is minimized) and normal cases (for which economic dispatching, taking into losses account, is established). In order to deal with these two cases with ARCOMALT, and to be able to introduce the randomness of all the variables concerned, we have reduced the number of nodes to about a dozen, which will be justified by both technical and economic reasons. It will also be shown that a good way to represent the interconnection network, from an economic point of view, is to let the various regions exchange electricity at marginal cost (either fuel or failure cost) with a transaction cost (a polynome, the degree of shich will be discussed) and bounds on exchange capacities.The reduced problem is neither linear (both criteria and constraints are not) nor of a small size, so that usual methods cannot be applied. Graph theory cannot be used in this case because it is a problem with variable gains related to the links, and not a problem with fixed gains related to the nodes (which could be solved). It will be proved that, using the additive properties of the criteria, the main problem can be decomposed into smaller sub-problems and the optimal size of these sub-problems being the 3 nodes-problem. Finally, the relaxation method, which proceeds in two steps, is described: a rough solution is first obtained through a primal approach before using a dual approach to complete the computation of the marginal costs.     

The EU regulation on cross-border trade of electricity: A two-stage equilibrium model

The regulation on cross-border exchanges of electricity in the European Union is meant to enhance the trade of electricity between Member States, by facilitating access to the network and improving the management of congestion at the interconnections. This paper presents a computational model that embeds these two features. The problem is cast in the form of a two-stage equilibrium between regional Regulators. In the first stage, they decide on the allocation of their regional network costs between generators and customers. Either they maximise their regional welfare non-cooperatively (Nash equilibrium), or they centralise the decision as a super-regulator (leading to a cooperative equilibrium). In the second-stage equilibrium, the consequences of first-stage’s decisions are assessed by modelling the energy market as the result of imperfect competition equilibrium on competitive market, coupled with regulated pricing on the domestic less competitive markets. The “rules” that come out of the first-stage game largely influence the final equilibrium. We illustrate this on an extensive numerical example, showing that the model behaves properly and identifying policy issues worth of further investigations.     

Multiobjective optimization and marginal pollution abatement cost in the electricity sector – An Israeli case study

The multiple objective optimization models for capacity expansion problem of power generation system in the long run as a base for setting up the marginal abatement cost were examined. In the optimization model the objective function is considered as the weighted sum of several objective functions. Air pollutants are taken into account in both the objective function and the constraints. Different scenarios of pollutant reduction were analyzed. The periods of the years 2003–2013 were taken into account and the results are based on the real data of the Israel electricity sector. Several environmental policies were considered by using the CAPEX system to evaluate the environmental and economic deficiencies in different abatement cost scenarios. The following are obtained: abatement cost for each pollutant, amount of emissions and additional cost connected with the pollutants. Modern decision tools are implemented, such as data envelopment analysis (DEA) and reasonable goal method/interactive decision maps (RGM/IDM) technique as a base for decision-makers to make decisions on energy and environmental policy.     

A planning model for crisis management in the tourism sector

The article proposes an analytical planning framework for managing crisis situations in the tourism industry. It applies the principle of acting in successive phases by which each stage aims to reduce the residual negative effects remaining after implementing the preceding one. The first phase relates to pre-crisis policy measures designed to reduce the overall sensitivity of the industry to crisis situations, the second phase deals with response policies to be implemented when conditions of crisis-certainty exist, and the third phase considers various specific short-term supplementary measures.The optimization process employs portfolio theory and linear programming models. It can be used by governmental agencies in charge of long-range countrywide or regional planning as an auxiliary tool for policy decesions.     

A mathematical model of a technology sector with investment

We describe a method of constructing production functions for a distributed single-factor model of an economy with a homogeneous product. We study the optimal control of investment.Translated fromMatematichni Metodi ta Fiziko-Mekhanichni Polya, Vol. 40, No. 4, 1997, pp. 155–157.     

Pricing electricity derivatives within a Markov regime-switching model: a risk premium approach

In this paper we derive analytic formulas for electricity derivatives under assumption that electricity spot prices follow a 3-regime Markov regime-switching model with independent spikes and drops and periodic transition matrix. Since the classical derivatives pricing methodology cannot be used in the case of non-storable commodities, we employ the concept of the risk premium. The obtained theoretical results are then used for the European Energy Exchange data analysis. We calculate the risk premium in the case of the calibrated 3-regime MRS model. We find a time varying structure of the risk premium and an evidence for a negative risk premium (or positive forward premium), especially at short times before delivery. Finally, we use the obtained risk premium to calculate prices of European options written on spot, as well as, forward prices.     

Evaluating the impact of average cost based contracts on the industrial sector in the European emission trading scheme

The degradation of the competitiveness of part of the European industry is progressively emerging as one of the possible consequences of the combination of the European Emission Trading Scheme (EU-ETS) and the restructuring of the electricity sector. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Evaluating the impact of average cost based contracts on the industrial sector in the European emission trading scheme

The inception of the emission trading scheme in Europe has contributed to power price increases. Energy intensive industries have reacted by arguing that this may affect their competitiveness and will induce them to leave Europe. Taking up a proposal of these industrial sectors, we explore the possible application of special contracts, where electricity is sold at average generation cost to mitigate the impact of CO₂ cost on power prices. The model supposes fixed generation capacities. We first consider a reference model representing a perfectly competitive market where all consumers (industries and the rest of the market) are price-takers and buy electricity at short-run marginal cost. We then change the market design by assuming that energy intensive industries pay power either at a regional or at a zonal average cost price. The analysis is conducted with simulation models applied to the Central Western European power market. The models are implemented in GAMS/PATH. This work has been financially supported by the Chair Lhoist Berghmans in Environmental Economics and Management and by the Italian project PRIN 2006, Generalized monotonicity: models and applications, whose national responsible is Prof. Elisabetta Allevi.     

A stochastic multiscale model for electricity generation capacity expansion

Long-term planning for electric power systems, or capacity expansion, has traditionally been modeled using simplified models or heuristics to approximate the short-term dynamics. However, current trends such as increasing penetration of intermittent renewable generation and increased demand response requires a coupling of both the long and short term dynamics. We present an efficient method for coupling multiple temporal scales using the framework of singular perturbation theory for the control of Markov processes in continuous time. We show that the uncertainties that exist in many energy planning problems, in particular load demand uncertainty and uncertainties in generation availability, can be captured with a multiscale model. We then use a dimensionality reduction technique, which is valid if the scale separation present in the model is large enough, to derive a computationally tractable model. We show that both wind data and electricity demand data do exhibit sufficient scale separation. A numerical example using real data and a finite difference approximation of the Hamilton–Jacobi–Bellman equation is used to illustrate the proposed method. We compare the results of our approximate model with those of the exact model. We also show that the proposed approximation outperforms a commonly used heuristic used in capacity expansion models.     

The credit risk+ model with general sector correlations

We consider an enhancement of the credit risk⁺ model to incorporate correlations between sectors. We model the sector default rates as linear combinations of a common set of independent variables that represent macro-economic variables or risk factors. We also derive the formula for exact VaR contributions at the obligor level.     

A discrete model for optimal operation of fossil-fuel generators of electricity

This paper presents a new discrete approach to the price-based dynamic economic dispatch (PBDED) problem of fossil-fuel generators of electricity. The objective is to find a sequence of generator temperatures that maximizes profit over a fixed-length time horizon. The generic optimization model presented in this paper can be applied to automatic operation of fossil-fuel generators or to prepare market bids, and it works with various price forecasts. The model’s practical applications are demonstrated by the results of simulation experiments involving 2009 NYISO electricity market data, branch-and-bound, and tabu-search optimization techniques.     

Strategic bidding in continuous electricity auctions: an application to the Spanish electricity market

In this paper we introduce an asymmetric model of continuous electricity auctions with limited production capacity and bounded supply functions. The strategic bidding is studied with this model by means of an electricity market game. We prove that for every electricity market game with continuous cost functions a mixed-strategy Nash equilibrium always exists. In particular, we focus on the behavior of producers in the Spanish electricity market. We consider a very simple form for the Spanish electricity market: an oligopoly consisting just of independent hydro-electric power production units in a single wet period. We show that a pure-strategy Nash equilibrium for the Spanish electricity market game always exists.     

A semi-implicit tidal model of the North European Continental Shelf

A semi-implicit scheme for the numerical solution of the shallow water equations is proposed. An example of successful application is the simulation of the major tidal constituent (M₂) on the European Shelf. Good agreement is found both qualitatively and quantitatively. The basic outlines of the method are presented and some practical aspects of computation are discussed. Apart from accuracy, compared to explicit or to existing semi-implicit schemes, this approach has another important feature: its economy and simplicity.     

Market power analysis in electricity markets using supply function equilibrium model

This paper presents a surveillance method based on the gametheory which is used by the ISO to find whether a power supplierin an electricity market has market power. The paper uses thesupply function equilibrium model to analyse the generationsuppliers’ bidding behaviour and models the ISO's marketpower monitoring problem as a bi-level multi-objective problem.The outer sub-problem is a multi-objective problem which maximizessuppliers’ payoffs, while the inner one is the ISO's marketclearing problem based on the locational marginal pricing mechanism.A discrete method is adopted to find ‘good enough’solutions, in a continuous bidding strategy space, which arethe intersection of all suppliers’ optimal response spacesaccording to Nash equilibrium. The paper utilizes the IEEE 118-bussystem to illustrate the application of the proposed methodwith three suppliers as price setters in the energy market andthe other generators as price takers. The numerical resultsshow that the transmission congestion may enhance the suppliers’ability to exercise market power. Likewise, suppliers’gaming behaviour could relieve the transmission congestion.It is shown that applying price caps is an efficient way ofmitigating market power.     

A stochastic Bass innovation diffusion model for studying the growth of electricity consumption in Greece

In this paper a stochastic innovation diffusion model is proposed derived by introducing stochasticity into the well-known Bass model. The stochastic model is solved analytically by using the theory of reducible stochastic differential equations and the first moment of the resulting stochastic process is presented. The parameter estimators of the model are derived by using a procedure which provides the maximum likelihood estimators (MLE) using time series data. Finally, the model is applied to the data of electricity consumption in Greece. Using a simulation technique, it is possible to predict the performance of the consumption process by defining a subdomain to which all possible trajectories of the process should belong with a predefined probability. © 1997 by John Wiley & Sons, Ltd.