or practice selecting a portfolio of environmental programs for a synthetic fuels facility this article describes how a u s department of energy steering committee used a decision analysis procedure to develop a portfolio of environmental and health research programs for a commercial scale synthetic fuels facility the procedure used information and insights from decision analyses conducted in five technical areas to support decision analysis at the portfolio level the problem was complex because it included many combinations of studies that could be funded multiple objectives in the five technical areas as well as at the portfolio level and uncertainties about research needs the availability of technical data and research costs the article discusses the rationale for using formal decision analysis the main features of the procedure and how the procedure provided the steering committee with a logical basis for evaluating a large number of diverse technical projects and with the help of health and environmental experts established research priorities and budget allocations in a logical and defensible manner

it s not now or never implications of investment timing and risk aversion on climate adaptation to extreme events abstract public investment into risk reduction infrastructure plays an important role in facilitating adaptation to climate impacted hazards and natural disasters in this paper we provide an economic framework to incorporate investment timing and insurance market risk preferences when evaluating projects related to reducing climate impacted risks the model is applied to a case study of bushfire risk management we find that optimal timing of the investment may increase the net present value npv of an adaptation project for various levels of risk aversion assuming risk neutrality while the market is risk averse is found to result in an unnecessary delay of the investment into risk reduction projects the optimal waiting time is shorter when the insurance market is more risk averse or when a more serious scenario for climatic change is assumed a higher investment cost or a higher discount rate will increase the optimal waiting time we also find that a stochastic discount rate results in higher npvs of the project than a discount rate that is assumed fixed at the long run average level

baseline value specification and sensitivity analysis in multiattribute project portfolio selection abstract a key issue in applying multi attribute project portfolio models is specifying the baseline value a parameter which defines how valuable not implementing a project is relative to the range of possible project values in this paper we present novel baseline value specification techniques which admit incomplete preference statements and unlike existing techniques make it possible to model problems where the decision maker would prefer to implement a project with the least preferred performance level in each attribute furthermore we develop computational methods for identifying the optimal portfolios and the value to cost based project rankings for all baseline values we also show how these results can be used to i analyze how sensitive project and portfolio decision recommendations are to variations in the baseline value and ii provide project decision recommendations in a situation where only incomplete information about the baseline value is available

uncertainty and endogenous technical change in climate policy models until recently endogenous technical change and uncertainty have been modeled separately in climate policy models in this paper we review the emerging literature that considers both these elements together taken as a whole the literature indicates that explicitly including uncertainty has important quantitative and qualitative impacts on optimal climate change technology policy

evaluating the impacts of priority dispatch in the european electricity market this paper compares the impact of the nodal pricing and european market coupling organizations on different economic agents of the power system under two main wind policies under the priority dispatch policy transmission system operators tsos must accommodate all wind energy produced which thus has the priority over energy produced by conventional plants in the no priority dispatch policy tsos can decide not to inject all potential wind power in the grid in order to limit congestion problems the effects of these two wind policies are measured by developing simple stochastic programming models that consider cases with different wind penetration levels existing capacities and endogenous investments as well as assumptions on the eu ets our computational experiments show that when there is priority dispatch nodal pricing and market coupling evolve in a similar way as long as wind penetration is not too high in contrast a significant increase of wind penetration causes the collapse of the market coupling organization while nodal pricing continues to perform well on the other hand no priority dispatch removes most of the problems resulting from market coupling which still exhibits a slightly lower efficiency than nodal pricing these outcomes do not depend on the contextual assumptions fixed capacities vs investment eu ets vs non eu ets that characterize the several cases analyzed this suggested that our policy conclusions are robust furthermore our models overestimate the flexibility of conventional plants which means that these conclusions would likely be reinforced with a more detailed model

international portfolio choice and political instability risk a multi objective approach abstract the benefits derived from international portfolio diversification into foreign nations including the less developed countries are well documented yet this practice is discouraged due to market imperfections such as political instability in practice nations may be differentiated further by many aspects such as border controls or political and social trends which constrain private transactions and financial decisions this paper attempts to examine 1 whether the home asset bias in a portfolio holding is associated with higher political instability risk and 2 to what extent international diversification among stocks in the presence of such risk outperforms domestic stock portfolios using alternative instability risk proxies in the context of a discrete time version of mean variance framework we corroborate the impact of this type of risk on international portfolio investment decisions

portfolio optimization with stochastic dominance constraints abstract we consider the problem of constructing a portfolio of finitely many assets whose return rates are described by a discrete joint distribution we propose a new portfolio optimization model involving stochastic dominance constraints on the portfolio return rate we develop optimality and duality theory for these models we construct equivalent optimization models with utility functions numerical illustration is provided

active learning and optimal climate policy this paper develops a climate economy model with uncertainty irreversibility and active learning whereas previous papers assume learning from one observation per period or experiment with control variables to gain additional information this paper considers active learning from investment in monitoring specifically in improved observations of the global mean temperature we find that the decision maker invests a significant amount of money in climate research far more than the current level in order to increase the rate of learning about climate change this helps the decision maker make improved decisions the level of uncertainty decreases more rapidly in the active learning model than in the passive learning model with only temperature observations as the uncertainty about climate change is smaller active learning reduces the optimal carbon tax the greater the risk the larger is the effect of learning the method proposed here is applicable to any dynamic control problem where the quality of monitoring is a choice variable for instance the precision at which we observe gdp unemployment or the quality of education

inventories rational expectations and the business cycle abstract the simplest macroeconomic models in which markets clear instantaneously and expectations are rational preclude the existence of business cycles that is of serially correlated deviations of output from trend this paper studies one of several mechanisms that can be used to make these so called new classical models produce business cycles the mechanism is the gradual adjustment of inventory stocks two macroeconomic models of inventory holdings are formulated both imply first that current output should be a decreasing function of the stock of inventories and second that inventories once perturbed from equilibrium levels should adjust only gradually these two features are then embedded into an otherwise standard macroeconomic model in which markets clear instantaneously and expectations are rational two principal conclusions are reached first disturbances such as unanticipated changes in money will set in motion serially correlated deviations of output from trend second if desired inventories are sensitive to the real interest rate then even fully anticipated changes in money can affect real variables

ecological modernization in the electrical utility industry an application of a bads goods dea model of ecological and technical efficiency abstract newly developed data envelopment analysis techniques permit simultaneous consideration of good and bad outputs in evaluating efficiency we use these techniques to determine joint ecological and technical efficiencies of the 437 largest fossil fueled electricity generating plants in the united states utilizing the epa s e grid and clean air markets databases and drawing on ecological modernization theory we evaluate whether innovations in organizational practices and technological solutions help achieve joint technical and environmental performance efficiencies

installed base and compatibility innovation product preannouncements and predation a good is often more valuable to any user the more others use compatible goods the authors show that this effect may inhibit innovation if an installed base exists and transition to a new standard must be gradual early adopters bear a disproportionate share of transient incompatibility costs this can produce excess inertia the installed base however is stranded if the new standard is adopted this may create excess momentum these dynamic effects have strategic implications temporary price cutting can permanently prevent entry and product preannouncements can be critical in innovation these strategic actions have ambiguous welfare effects

a model of competition in the solar panel industry we develop a model of competition in the solar panel industry solar firms manufacture panels that are differentiated both vertically and horizontally and compete by setting quantities the equilibrium of the model is consistent with a set of stylized facts that we document including variation in prices markups and market shares across firms we calibrate the model using a new dataset data on prices costs and shipments of leading solar companies as well as solar sales in four leading markets the calibrated model is applied to evaluate the impact of a decline in the price of polysilicon a key raw material used in the manufacture of solar panels on the equilibrium price of solar panels

the long run implications of the production smoothing model of inventories an empirical test summary this paper provides an empirical test of the long run implications of the production smoothing model of inventories the dominant framework for inventory investment research in the past intertemporal models of a firm holding inventories of finished goods predict a long run relationship between inventories shipments factor input prices and the real interest rate which is tested here using cointegration test procedures these tests provide little support for the predictions of the production smoothing model in most of the data sets used test statistics indicate that inventories shipments factor input prices the nominal interest rate and the inflation rate maintain a long run equilibrium relationship but parameter estimates of cointegrating vectors are often implausible typically rejecting hypotheses implied by structural models of the production smoothing motive for holding inventories

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

inventory and price behaviour the point of this paper is that inventory adjustment attenuates downward pressure on price when realized demand is low because firms accumulate inventory hold overs speculating that demand will be stronger in the succeeding period when realized demand is high the firm draws down its inventories until a stock out occurs and price rises to clear the market

the transmission of sustainable harvesting norms when agents are conditionally cooperative experimental and observational studies have highlighted the importance of agents being conditionally cooperative when facing a social dilemma we formalize this mechanism in a theoretical model that portrays a small community having joint access to a common pool resource the diffusion of norms of cooperation takes place via interpersonal relations while individual agents face the temptation of higher profits by overexploiting the resource agents remain conditionally cooperative unless other individuals are misbehaving already we can observe a bubble of conditional cooperators slowly building up followed by a sudden burst which means that a transition from a cooperative social norm to non cooperation occurs interestingly in some parameter regions alternative stable states and limit cycles arise the latter implies that the same community goes through such a transition repeatedly over long time spans history thus repeats itself in the form of the creation and erosion of social capital

vintage production models of u k manufacturing industry vintage production models for the u k are extended to cover hours worked as a separate element of labour input the main purpose of the analysis is then to ascertain whether the output of manufacturing as measured by some index can be satisfactorily explained as a simple stable function of a small number of input aggregates

climate change and optimal energy technology r d policy public policy response to global climate change presents a classic problem of decision making under uncertainty theoretical work has shown that explicitly accounting for uncertainty and learning in climate change can have a large impact on optimal policy especially technology policy however theory also shows that the specific impacts of uncertainty are ambiguous in this paper we provide a framework that combines economics and decision analysis to implement probabilistic data on energy technology research and development r d policy in response to global climate change we find that given a budget constraint the composition of the optimal r d portfolio is highly diversified and robust to risk in climate damages the overall optimal investment into technical change however does depend in a non monotonic way on the risk in climate damages finally we show that in order to properly value r d abatement must be included as a recourse decision

a disequilibrium model with smooth regime transitions and a keynesian spillover for switzerland s labor market abstract this paper presents a disequilibrium labor market model in which aggregation over a continuum of micro markets with different demand supply ratios produces smooth macro relationships mapping aggregate demand and supply onto actual employment and regime proportions aggregate labor demand consists of a classical part derived on a putty clay assumption and a keynesian spillover from the goods market the specification of labor supply incorporates intertemporal substitution the degree of aggregate imbalances on labor and goods markets is measured by business survey data the estimated model indicates a growing mismatch between the micro structures of demand and supply of labor the short run fluctuations of employment are primarily traced back to the keynesian spillover classical determinants of labor demand are relevant as well but only in the medium term labor supply is rather inert and thus absorbs the swings of labor demand only partly

large scale scenario analysis of future low carbon energy options abstract in this study we use a multi model framework to examine a set of possible future energy scenarios resulting from rd and portfolios lacking ccs and nuclear tend to be stochastically dominated by others we find that the dominance of ccs becomes even stronger as uncertainty in climate damages increases finally we show that there is significant value in carefully choosing a portfolio as relatively small portfolios can dominate large portfolios

a portfolio model for siting offshore wind farms with economic and environmental objectives abstract siting offshore wind farms is a complex problem due to the wake interactions between wind farms we develop a profit maximizing portfolio model based on underlying network models to track the wake effects through a series of wind farms our portfolio model optimizes the siting of wind farms considering multiple wind directions and wind speeds and performs better than simple decision heuristics excluding sites from the portfolio has nonlinear impacts on the profitability of the portfolio of sites in that areas excluded from consideration have greater impacts on profit if they are grouped together or aligned parallel to the prevailing wind direction the model can be readily adapted to include additional cost factors

price smoothing and inventory this paper explains the phenomenon of price rigidity or price smoothing as the outcome of the optimal inventory policy of a multi period profit maximizing firm under demand and output uncertainties price smoothing may be manifested in two forms first price changes may be moderated with respect to those implied by the demand function and second the firm may choose to restrict price fluctuations by establishing upper and or lower bounds on prices we show that the extent of the asymmetry in price smoothing depends on the relationship between the inventory holding cost and the backlog penalty cost our model accommodates a wide range

the recent slowdown of productivity growth the slowdown of productivity growth in the developed countries during the seventies will in this paper be viewed as a combined effect of three closely interacting forces i a long term deterioration in the efficiency and flexibility of some basic mechanisms of the economic and political systems of these countries ii the fading away of a number of uniquely favourable circumstances for productivity growth during the fifties and sixties and iii the exposure of these economies to unusually severe macroeconomic disturbances in the seventies careful inspection of time series with attempted modifications for cyclical factors suggests that there was hardly any general slowdown of productivity growth among developed countries before approximately i972 4 1 as we know the situation is radically different since then labour productivity growth per year for the entire national economy gdp per man hour seems to have fallen between the periods i960 73 and i973 9 by about i 2 percentage points in the united states 45 by about 24 percentage points in western europe2 45 and by about 5 9 percentage points in japan 6o table i see also fig i the slowdown was of about the same size in the business and manufacturing sectors see table i to calculate the extent of the slowdown of total factor productivity growth is of course a much more hazardous matter to which i will return later if just the various system changes and the fading away of the uniquely favourable factors had been the dominating forces behind the productivity growth slowdown we would expect the slowdown to have been gradual rather than abrupt as it turned out to be this abruptness as well as its timing makes the dramatic macroeconomic disturbances around i972 4 a prime suspect when looking for the villain behind the productivity growth slowdown indeed it is a basic hypothesis of the paper that these macroeconomic disturbances were not only by themselves strongly unfavourable for productivity growth but that they also revealed and accentuated the gradual deterioration of the

the interrelationship between price and output decisions and investment decisions microfoundations and aggregate implications abstract this paper develops a model of firm behavior in which both price and output decisions and investment decisions are made the model permits an analysis of the dynamics of inventory and capital accumulation on price and output behavior there are two main results 1 short run price and output levels will differ from long run levels as desired stocks of inventory and capital diverge from actual levels 2 the size of the elasticities of price and output to changes in demand and cost variables depends on the speed with which gaps between desired and actual stocks are closed through investment

social norms and pro environmental behavior a review of the evidence in light of the growing attention that social norm interventions have garnered as policy tools we review the current body of evidence on their effectiveness with respect to pro environmental behaviors we identify the various conceptualizations of social norms currently in use and inventory the experimental economics and social psychology literature that has examined the impacts of social norm interventions on pro environmental behavior for each study included in this inventory we note several contextual features the data collection and analytical methods used and any significant main effects attributed to the social norm intervention we also review several theoretical models of behavior that incorporate social norms based on this empirical and theoretical review we draw a number of policy implications and identify avenues for future research on the role of social norms with respect to pro environmental behavior

bayesian estimation of the global minimum variance portfolio in this paper we consider the estimation of the weights of optimal portfolios from the bayesian point of view under the assumption that the conditional distribution of the logarithmic returns is normal using the standard priors for the mean vector and the covariance matrix we derive the posterior distributions for the weights of the global minimum variance portfolio moreover we reparameterize the model to allow informative andnon informative priors directly for the weights of the global minimum variance portfolio the posterior distributions of the portfolio weights are derived in explicit form for almost all models the models are compared by using the coverage probabilities of credible intervals in an empirical study we analyze the posterior densities of the weights of an international portfolio

capacity growth in a clay clay vintage model in this paper the growth rates of capacity output and capacity demand for labour are derived for a clay clay vintage model the results are simple and directly applicable in the sense that they only depend on parameters and measurable variables

representing induced technological change in models for climate policy analysis induced technological change itc whereby the relative price effects of reducing greenhouse gas emissions stimulate innovation that mitigates the cost of abatement is both tantalizing to decision makers and challenging to represent in the computational economic and engineering models used to analyze climate change policy this overview reconciles the divergent views of technology and technological change within different types of models elucidates the theoretical underpinnings of itc introduces the reader to the techniques of their practical implementation and evaluates the implications for models results

a stochastic two settlement equilibrium model for electricity markets with wind generation incentives to encourage the uptake of renewable energy generation have fostered wind energy in many power systems these incentives usually take the form of market instruments e g feed in tariff or premium that are not directly amenable to optimization representations of the market in this paper we propose an equilibrium model of the short term market to address the impact of wind operation under different structural assumptions the model is formulated for several price taking risk averse firms in competition it accounts for wind generation uncertainty and embeds a representation of the day ahead and balancing mechanisms the consumer is modeled by a linear inverse demand function we focus on feed in premium as the incentive to wind as this is the instrument most favored today in european discussions the model is formulated as a stochastic equilibrium problem where the karush kuhn tucker kkt conditions from the optimization problem of each firm are simultaneously solved together with market clearing conditions on energy capacity for reserve and energy for reserve the problem for each firm consists of a two stage stochastic optimization problem with a recourse function based on the conditional value at risk cvar as a risk measure due to price taking assumptions the model is a single stage complementarity problem it is implemented and solved using the software gams an example based on a stylized simplification of the spanish power market and motivated by the impact of wind penetration on the revenue of conventional plants is used to illustrate the proposed approach

an admm based method for computing risk averse equilibrium in capacity markets uncertainty in electricity markets introduces risk for investors high fixed cost and increased dependency on infrequent and uncertain price spikes characterize investments the risk averse behavior of investors might lead to poor decision making and undermines generation adequacy electricity market models rarely treat the interaction of market design and risk aversion the representation of capacity mechanisms in modeling approaches focusing on risk aversion is limited our contribution addresses two problems first we propose a stochastic market equilibrium model investors are represented as risk averse agents the conditional value at risk is used as risk measure second we propose an algorithm based on the alternating direction method of multipliers to compute a risk averse equilibrium we benchmark our approach with a state of the art solver relying on a mixed complementarity problem reformulation we show that for larger case studies our proposed approach is preferable the algorithm converges in all cases while conventional solvers fail to compute a risk averse equilibrium the methodology is transferable to other risk averse equilibrium models with reference to capacity markets we conclude that they are more beneficial in a risk averse market capacity markets result in lower total cost while avoiding expected energy not served this statement still holds with increased price caps in energy only markets

network externality an uncommon tragedy economists have defined network externality and have examined putative inframarginal market failures associated with it this paper distinguishes between network effects and network externalities where the latter are market failures the authors argue that while network effects are important network externalities are theoretically fragile and empirically undocumented some network externalities are merely pecuniary network ownership or transactions among network participants can internalize some network effects the type of market failure that has been associated with these externalities is a transition problem that has little to do with externality

preference programming for robust portfolio modeling and project selection in decision analysis difficulties of obtaining complete information about model parameters make it advisable to seek robust solutions that perform reasonably well across the full range of feasible parameter values in this paper we develop the robust portfolio modeling rpm methodology which extends preference programming methods into portfolio problems where a subset of project proposals are funded in view of multiple evaluation criteria we also develop an algorithm for computing all non dominated portfolios subject to incomplete information about criterion weights and project specific performance levels based on these portfolios we propose a project level index to convey i which projects are robust choices in the sense that they would be recommended even if further information were to be obtained and ii how continued activities in preference elicitation should be focused the rpm methodology is illustrated with an application using real data on road pavement projects

scenario based portfolio selection of investment projects with incomplete probability and utility information abstract in the selection of investment projects it is important to account for exogenous uncertainties such as macroeconomic developments which may impact the performance of projects these uncertainties can be addressed by examining how the projects perform across several scenarios but it may be difficult to assign well founded probabilities to such scenarios or to characterize the decision makers risk preferences through a uniquely defined utility function motivated by these considerations we develop a portfolio selection framework which i uses set inclusion to capture incomplete information about scenario probabilities and utility functions ii identifies all the non dominated project portfolios in view of this information and iii offers decision support for rejection and selection of projects the proposed framework enables interactive decision support processes where the implications of additional probability and utility information or further risk constraints are shown in terms of corresponding decision recommendations

a single settlement energy only electric power market for unpredictable and intermittent participants we discuss a stochastic programming based method for scheduling electric power generation subject to uncertainty such uncertainty may arise from either imperfect forecasting or moment to moment fluctuations and on either the supply or the demand side the method gives a system of locational marginal prices that reflect the uncertainty and these may be used in a market settlement scheme in which payment is for energy only we show that this scheme is revenue adequate in expectation

optimal strategies for selecting project portfolios using uncertain value estimates abstract practically all organizations seek to create value by selecting and executing portfolios of actions that consume resources typically the resulting value is uncertain and thus organizations must take decisions based on ex ante estimates about what this future value will be in this paper we show that the bayesian modeling of uncertainties in this selection problem serves to i increase the expected future value of the selected portfolio ii raise the expected number of selected actions that belong to the optimal portfolio ex post and iii eliminate the expected gap between the realized ex post portfolio value and the estimated ex ante portfolio value we also propose a new project performance measure defined as the probability that a given action belongs to the optimal portfolio finally we provide analytic results to determine which actions should be re evaluated to obtain more accurate value estimates before portfolio selection in particular we show that the optimal targeting of such re evaluations can yield a much higher portfolio value in return for the total resources that are spent on the execution of actions and the acquisition of value estimates

managing risks from climate impacted hazards the value of investment flexibility under uncertainty abstract incomplete knowledge about climate change and the related uncertainty in climate prediction makes adaptation inherently difficult we introduce a real options framework to determine the optimal adaptation to catastrophic risk that takes into account climate change uncertainty the framework can be used to select the optimal adaptation project from a number of alternative projects or to determine the optimal investment sequence of the considered projects in applying the model to the management of bushfire risk at a local government area we find that the framework can significantly increase the value of adaptation investment above the current net present value and also improve upon deterministic dynamic models we also find that it is important to consider sequential investment to preserve investment flexibility under the uncertainty of climate change when decision makers can afford multiple investment projects the loss associated with the use of a simple net present value rule can be substantial and it is important to use a deterministic dynamic model or a real options model

on the sources of technological change assessing the evidence this paper uses a selective review of the economic literature on technological change to support four points that are important for interpreting and incorporating technological change into formal models of energy and the environment the review 1 supports the notion that no single source dominates the process of technological change it supports roles for rd 3 indicates that these spillovers are often indirect requiring own industry activities to utilize and 4 indicates that simple experience curve calibrations often used in formal models likely include a range of sources of technological change in addition to learning by doing some of which might not be induced by the sorts of policies typically considered in the climate context

consumer behaviour with environmental and social externalities implications for analysis and policy in this paper we summarise some of our recent work on consumer behaviour drawing on recent developments in behavioural economics particularly linked to sociol ogy as much as psychology in which consumers are embedded in a social context so their behaviour is shaped by their interactions with other consumers for the purpose of this paper we also allow consumption to cause environmental damage analysing the social context of consumption naturally lends itself to the use of game theoretic tools we shall be con cernedwithtwowaysinwhichsocialinteractionsaffectconsumerpreferencesandbehaviour socially embeddedpreferences wherethebehaviourofotherconsumersaffectanindividual s preferences and hence consumption we consider two examples conspicuous consumption and consumption norms and socially directed preferences where people display altruistic behaviour our aim is to show that building links between sociological and behavioural eco nomic approaches to the study of consumer behaviour can lead to significant and surprising implications for conventional economic analysis and policy prescriptions especially with respect to environmental policy

belief in a just world and redistributive politics international surveys reveal wide differences between the views held in different countries concerning the causes of wealth or poverty and the extent to which people are responsible for their own fate at the same time social ethnographies and experiments by psychologists demonstrate individuals recurrent struggle with cognitive dissonance as they seek to maintain and pass on to their children a view of the world where effort ultimately pays off and everyone gets their just deserts this paper offers a model that helps explain i why most people feel such a need to believe in a just world ii why this need and therefore the prevalence of the belief varies considerably across countries iii the implications of this phenomenon for international differences in political ideology levels of redistribution labor supply aggregate income and popular perceptions of the poor the model shows in particular how complementarities arise endogenously between individuals desired beliefs or ideological choices resulting in two equilibria a first american equilibrium is characterized by a high prevalence of just world beliefs among the population and relatively laissez faire policies the other european equilibrium is characterized by more pessimism about the role of effort in economic outcomes and a more extensive welfare state more generally the paper develops a theory of collective beliefs and motivated cognitions including those concerning money consumption and happiness as well as religion

balancing solar pv deployment and rd d a comprehensive framework for managing innovation uncertainty in electricity technology investment planning abstract we present a new framework for studying the socially optimal level of generating capacity and public rd d investments for the electric power sector under decision dependent technical change uncertainty we construct a bottom up stochastic electricity generation capacity expansion model with uncertain endogenous rd d based technical change focusing on solar pv rd d investment planning for its current prominent role in sustainable energy and climate policy deliberations we characterize the decision dependent process of technical change uncertainty as unknown outcomes of rd d investments that increase the likelihood of success with increasing amounts of rd d and calibrate to a novel expert elicitation dataset that accounts for this decision dependence the problem is framed as a multi stage decision under uncertainty where the decision maker learns and adapts to new information between decision periods specifically our application considers four decision stages with the decision maker choosing investment levels for new capacity and solar pv rd d while learning about rd d outcomes that can reduce solar pv costs between each stage the problem is thus formulated to match the manner in which real world decisions about rd d investments in renewable energy are made and avoids common assumptions of perfect foresight or uncertainty but no learning that are often used in practice numerical results show that when uncertainty and learning features are both included the optimal solar pv rd d investment strategy changes from solutions using other methods considering uncertainty and learning results in solar rd d investment differences as high as 20 percent lower in the first stage and 300 percent higher in later stages we also show that when uncertainty is considered without learning the fraction of new solar pv capacity investments can be depressed overall this paper shows that it is possible to unify several realistic features of the deployment and development problem for the electricity sector to meet sustainability goals into one framework

investment in risky r d programs in the face of climate uncertainty we analyze how the socially optimal technology rd and that uncertainty in damages interacts with uncertainty in the returns to rd and r d that reduces the emissions to output ratio and argue that this is a good representation of r d into fossil fuel technologies for r d programs into non carbon technologies optimal investment is higher in riskier programs our empirical model indicates that the optimal investment in a risky program is about 3 1 2 times larger than in a program with certain returns for r d programs aimed at reducing emissions in fossil fuel based technologies our results show that qualitatively investment is higher in less risky programs under most uncertain damage scenarios our empirical model shows however that the risk profile of fossil fuel based r d programs generally has little quantitative impact on optimal investment the exception is that when the probability of a catastrophe inducing full abatement is very high investment is about twice as high in risky programs compared to programs with certain returns

stochastic dominance and expected utility survey and analysis while stochastic dominance has been employed in various forms as early as 1932 it has only been since 1969 1970 that the notion has been developed and extensively employed in the area of economics finance agriculture statistics marketing and operations research in this survey the first second and third order stochastic dominance rules are discussed with an emphasis on the development in the area since the 1980s

an optimal middleman firm price adjustment policy the short run inventory based pricing policy this paper examines the optimum pricing policies of middleman firms who carry an inventory of goods bought for resale each period the firm in the theoretical model is required to post a price before it observes its realized demand in disequilibrium situations the firm s profit maximizing pricing policy is shown to be a short run inventory based pricing policy which requires the firm to post a price below the long run equilibrium price upon observing its actual beginning inventory level above its optimum level and to post a price above the long run equilibrium price upon observing its actual inventory level below its optimum level the final section suggests that the use of such policies by middleman firms will lead to market price adjustments which are both consistent with the law of supply and demand and which are based on explicit maximizing behavor

a portfolio decision analysis approach to support energy research and development resource allocation abstract research sponsored by the us department of energy doe aims to facilitate a clean and independent energy future for the nation strategic planning for energy research and development r d can be complex and dynamic in part due to federal budgetary constraints and volatility managing r d funding to advance energy technologies in spite of these challenges is a crucial component of the nation s long term energy policy this study demonstrates a portfolio decision analysis pda approach to support r d resource allocation decisions for the doe office of fossil energy s carbon capture and storage r d program a multi attribute value model uses technology readiness levels trls and other metrics to represent the overall objectives of the r d program in order to evaluate alternative research portfolios given limited funding mathematical optimization identifies efficient funding allocations for each technology program area to maximize the multi attribute value generated from the total budget this is especially useful for responding to externally imposed budget changes as the case study demonstrates explicitly funding the most value generating options leads to greater expected r d programmatic value than typical strategies of equal or proportional distributions of a budget change among technology program areas

strategic wind power investment this paper considers the problem of identifying the optimal investment of a strategic wind power investor that participates in both the day ahead da and the balancing markets this investor owns a number of wind power units that jointly with the newly built ones allow it to have a dominant position and to exercise market power in the da market behaving as a deviator in the balancing market in which the investor buys sells its production deviations the model is formulated as a stochastic complementarity model that can be recast as a mixed integer linear programming milp model a static approach is proposed focusing on a future target year whose uncertainties pertaining to demands wind power productions and balancing market prices are precisely described the proposed model is illustrated using a simple example and two case studies

on backstops and boomerangs environmental r d under technological uncertainty abstract in areas such as climate change the recent economic literature has been emphasizing and addressing the pervasive presence of uncertainty this paper considers a new and salient form of uncertainty namely uncertainty regarding the environmental characteristics of green innovations here rd ii a decreasing probability of finding a backstop leads to the toleration of higher pollution levels slower rd iii learning about the probability of a backstop is driven by failures only and leads to decreasing research incentives and iv small to moderate delays in the resolution of technological uncertainty do not affect the optimal policy

contingent portfolio programming for the management of risky projects methods for selecting a research and development r d project portfolio have attracted considerable interest among practitioners and academics this notwithstanding the industrial uptake of these methods has remained limited partly because of the difficulties of capturing relevant concerns in r d portfolio management motivated by these difficulties we develop contingent portfolio programming cpp which extends earlier approaches in that it i uses states of nature to capture exogenous uncertainties ii models resources through dynamic state variables and iii provides guidance for the selection of an optimal project portfolio that is compatible with the decision maker s risk attitude although cpp is presented here in the context of r d project portfolios it is applicable to a variety of investment problems where the dynamics and interactions of investment opportunities must be accounted for

emission path planning based on dynamic abatement cost curve abstract global climate change is one of the most serious environmental problems that has attracted an unprecedented global attention the scientific community has recognized that human activity is mostly responsible for global climate warming therefore states participating in the united nations framework convention on climate change unfccc have initiated a series of negotiations on how to develop their own emission reduction targets however the realization of these targets is at the expense of economic development to a great extent therefore an abatement plan is necessary to decide how and when to implement emission reduction targets a marginal abatement cost curve macc often used as an important quantitative tool to estimate abatement burden or evaluate abatement performance should be considered carefully in this paper we enrich the traditional macc by introducing the concept of an immediate unit marginal abatement cost to describe its intrinsic incremental abatement difficulty this cost is proved to be agreed with the actual situation in many ways and is therefore very suitable for practical use two factor learning curve are considered in the model which can go some way in improving the performance of the revised macc using a parameterization method the original problem can be converted into a tractable nonlinear programming problem we use an algorithm to search for the approximate global optimal solution the effectiveness and the efficiency of the algorithm are discussed respectively in the results we find that the abatement path distinguishes largely under different abatement targets some plausible reasons and policy advices are given

wind farm portfolio optimization under network capacity constraints in this article we provide a new methodology for optimizing a portfolio of wind farms within a market environment for two market designs exogenous prices and endogenous prices our model is built on an agent based representation of suppliers and generators interacting in a certain number of geographic demand markets organized as two tiered systems assuming rational expectation of the agents with respect to the outcome of the real time market suppliers take forward positions which act as signals in the day ahead market to compensate for the uncertainty associated with supply and demand then generators optimize their bilateral trades with the generators in the other markets the nash equilibria resulting from this signaling game are characterized using game theory the markowitz frontier containing the set of efficient wind farm portfolios is derived theoretically as a function of the number of wind farms and of their concentration finally using a case study of france germany and belgium we simulate the markowitz frontier contour in the expected cost risk plane

is certainty in carbon policy better than uncertainty abstract uncertainty in the strictness of carbon policy can have significant impacts on power generating firms capacity investment decisions and market outcomes we investigate the effects of this policy uncertainty on firms expected profits consumers surplus and firms cost for reaching a co 2 emission target our results derived from a game theoretical model and applied to realistic data indicate that uncertainty in the carbon policy induces more capacity investments in fossil and renewable technologies we find that it is optimal for firms with higher risk aversion to invest more in renewable technologies than their less risk averse rivals for policy makers our results suggest counter intuitively that retaining the flexibility to update emission targets whilst causing uncertainty in the carbon policy is beneficial this is because it provides higher expected consumer surplus and lower expected electricity price power generating firms are also better off under the policy uncertainty by having lower expected costs for reaching the emission goal and higher expected profits when firms risk aversions are low these results support the approach employed in european power markets to periodically update the co 2 emission cap depending on the prevailing circumstances rather than having certainty in the decrements of the caps over a longer time horizon our insights can help policy makers and firms to make better decisions by understanding how carbon policy uncertainty impacts the optimal capacity investments and how these investments might depend on the firms heterogeneity in risk aversion

selecting a portfolio of solar energy projects using multiattribute preference theory this article reports a procedure developed to assist the u s department of energy in selecting a portfolio of solar energy applications experiments the procedure has also been used in other government procurements and appears to be applicable in a variety of project funding processes the technical quality of each proposed applications experiment was summarized through the use of multiple evaluation measures or attributes these were combined into a single index of the overall technical quality of an experiment through the use of a multiattribute utility function recently derived results in measurable value theory were applied to derive an index of the overall technical quality of a portfolio of experiments budgetary and programmatic issues were handled through the use of constraints this approach allowed the portfolio selection problem to be formulated as an integer linear program details of the application are presented including a discussion of the data requirements and assessment procedure used the portfolio selection procedure was successfully applied and variations of it have been successfully used in four other solar energy procurements

no man is an island social coordination and the environment humans are fundamentally social social activities require coordination possibly leading to multiple equilibria in the form of self reinforcing patterns of herd behavior when alternative equilibria differ substantially with respect to environmental damage they represent virtuous and vicious cycles from an environmental perspective such cycles can be sustained by network effects social pressure to conform or other mechanisms directly or indirectly yielding coordination benefits breaking the vicious cycles can be an important task for environmental policies i present a stylized model of social coordination with environmental externalities using it to discuss how environmental policies may help agents coordinate in more environment friendly ways

r d investment strategy for climate change abstract the economic costs of stabilizing greenhouse gas concentrations over the coming century depend critically on the development of new technologies in the energy sector our research and development r d investment strategy is the control variable for technology availability this paper proposes an analytic framework for determining optimal r d investment allocation and presents some numerical results to demonstrate the implementation of the methodology the value of technological advance in three targeted areas fossil based generation renewables and carbon capture and storage is represented by the increase in expected welfare in the presence of an emissions policy constraint of initially uncertain stringency r d expenditure increases the probability of advance optimal investment is determined by its relationship with success probability which is assumed to exhibit decreasing returns to scale relative to the value of success while the numerical results are speculative the paper offers insights into the nature of an optimal technology strategy for addressing climate change

network effects and environmental externalities do clean technologies suffer from excess inertia abstract we study the diffusion of a clean substitute to a dirty durable in a dynamic model consumer utility of both durables increases in their respective market shares due to network effects first we characterize the optimal dirty good tax the tax should achieve a long run optimal division of the market between the two goods along the transition path to this steady state the optimal tax depends on the current and future market shares of the clean durable thus even if the marginal environmental damage from an additional dirty durable is constant the optimal tax should not be constant second we study whether excess inertia can occur if the emission tax is not optimally set we then find that a constant tax that only accounts for the environmental damage caused by the dirty good may lead to excess inertia excess inertia could happen even if the clean technology is proprietary and the technology owner has incentives to sponsor the initial market diffusion of the technology

multistage decision making fuzzy methodology for optimal investments based on experts evaluations abstract a new methodology of making a decision on an optimal investment in several projects is proposed the methodology is based on experts evaluations and consists of three stages in the first stage kaufmann s expertons method is used to reduce a possibly large number of applicants for credit using the combined expert data the credit risk level is determined for each project only the projects with low risks are selected in the second stage the model of refined decisions is constructed using the new modification of the previously proposed possibilistic discrimination analysis method sirbiladze khutsisvili dvalishvili 2010 this stage is based on expert knowledge and experience the projects selected in the first stage are compared in order to identify high quality ones among them the possibility levels of experts preferences are calculated and the projects are ranked finally the third stage deals with the bicriteria discrete optimization problem whose solution makes it possible to arrange the most advantageous investment in several projects simultaneously the decision on funding the selected projects is made and an optimal distribution of the allocated investment amount among them is provided the efficiency of the proposed methodology is illustrated by an example

on the theory of the firm underlying empirical models of aggregate price behavior recent empirical work on aggregate and industrial price behavior has been conducted within the framework of a static neo classical theory of price formation 2 the purpose of this paper is to propose a more general theoretical framework for analyzing price behavior the proposed framework is neo classical in its basic characteristics but unlike the recent literature it is based on a dynamic theory of firm behavior in which decisions on price inventories and the capital stock are integrated to serve as a basis for comparison with the model developed here it is useful to state briefly the main propositions of the static neo classical model the model presumes that the typical firm behaves as if it were a simple monopolist that faces competitive factor input markets and sets its price so as to maximize current profits assuming a log linear demand function and production function the model yields the result that the firm s long run optimal price policy in general is

electricity market clearing with improved scheduling of stochastic production abstract in this paper we consider an electricity market that consists of a day ahead and a balancing settlement and includes a number of stochastic producers we first introduce two reference procedures for scheduling and pricing energy in the day ahead market on the one hand a conventional network constrained auction purely based on the least cost merit order where stochastic generation enters with its expected production and a low marginal cost on the other a counterfactual auction that also accounts for the projected balancing costs using stochastic programming although the stochastic clearing procedure attains higher market efficiency in expectation than the conventional day ahead auction it suffers from fundamental drawbacks with a view to its practical implementation in particular it requires flexible producers those that make up for the lack or surplus of stochastic generation to accept losses in some scenarios using a bilevel programming framework we then show that the conventional auction if combined with a suitable day ahead dispatch of stochastic producers generally different from their expected production can substantially increase market efficiency and emulate the advantageous features of the stochastic optimization ideal while avoiding its major pitfalls a two node power system serves as both an illustrative example and a proof of concept finally a more realistic case study highlights the main advantages of a smart day ahead dispatch of stochastic producers

the economics of convention c onventions regulate much of economic and social life yet they have received surprisingly little attention from economists by a convention we mean a pattern of behavior that is customary expected and self enforcing everyone conforms everyone expects others to conform and everyone has good reason to conform because conforming is in each person s best interest when everyone else plans to conform lewis 1969 familiar examples include following rules of the road adhering to conventional codes of dress and using words with their conventional meanings conventions with direct economic implications include species of money and credit industrial and technological standards accounting rules and forms of economic contracts indeed it would scarcely be an exaggeration to say that almost all economic and social institutions are governed to some extent by convention the main feature of a convention is that out of a host of conceivable choices only one is actually used this fact also explains why conventions are needed they resolve problems of indeterminacy in interactions that have multiple equilibria indeed from a formal point of view we may define a convention as an equilibrium that everyone expects in interactions that have more than one equilibrium the economic significance of conventions is that they reduce transaction costs imagine the inconvenience if whenever two vehicles approached one another the important exceptions are sugden 1986 and ullman margalit 1977 the interested reader might also refer to the symposium on social norms that appeared in the fall 1989 issue of this journal with articles by sugden 1989 and elster 1989

advanced solar r d combining economic analysis with expert elicitations to inform climate policy the relationship between r d investments and technical change is inherently uncertain in this paper we combine economics and decision analysis to incorporate the uncertainty of technical change into climate change policy analysis we present the results of an expert elicitation on the prospects for technical change in advanced solar photovoltaics we then use the results of the expert elicitations as inputs to the minicam integrated assessment model to derive probabilistic information about the impacts of r d investments on the costs of emissions abatement

social norms morals and self interest as determinants of pro environment behaviours the case of household recycling this paper considers the role which selfish moral and social incentives and pressures play in explaining the extent to which stated choices over pro environment behaviours vary across individuals the empirical context is choices over household waste contracts and recycling actions in poland a theoretical model is used to show how cost based motives and the desire for a positive self and social image combine to determine the utility from alternative choices of recycling behaviour we then describe a discrete choice experiment designed to empirically investigate the effects such drivers have on stated choices a hybrid logit model is used to link statements over attitudes to recycling to choices dealing with a potential endogeneity problem caused by the joint effects of un observables on attitudes and choices we find that a substantial share of our respondents prefer to sort their waste at home rather than in a central sorting facility this preference is associated with a moral intrinsic motivation involving a belief that sorting at home is more thorough than central sorting

the damage costs of climate change toward more comprehensive calculations it is argued that estimating the damage costs of a certain benchmark climate change is not sufficient what is needed are cost functions and confidence intervals although these are contained in the integrated models and their technical manuals this paper brings them into the open in order to stimulate discussion after briefly reviewing the benchmark climate change damage costs region specific cost functions are presented which distinguish tangible from intangible losses and the losses due to a changing climate from those due to a changed climate furthermore cost functions are assumed to be quadratic as an approximation of the unknown but presumably convex functions results from the damage module of the integrated climate economy model fund are presented next uncertainties are incorporated and expected damages are calculated it is shown that because of convex loss functions and right skewed uncertain ties the risk premium is substantial calling for more action than analysis based on best guess estimates the final section explores some needs for further scientific research

dynamic portfolio selection of npd programs using marginal returns selecting program portfolios within a budget constraint is an important challenge in the management of new product development npd optimal portfolios are difficult to define because of the combinatorial complexity of project combinations however at the aggregate level of the strategic allocation of resources across product lines investment in a program is not an all or nothing decision but can beadjusted resulting in a higher or lower program benefit e g higher or lower quality in some cases resources can be adjusted even for individual projects with this insight one can usemarginal analysis to optimally allocate the scarce budget this article develops a dynamic model of resource allocation taking into account multiple interacting factors such as independent or correlated uncertain market payoffs that change over time increasing or decreasing returns from the npd investment carry over of the investment benefit over multiple periods and interactions across market segments we characterize optimal policies in closed form and derive qualitative decision rules for managers

stochastic carbon sinks for combating carbon dioxide emissions in the eu abstract this paper carries out numerical calculations on the potential of carbon sinks in the eu emissions trading scheme ets and national commitments under conditions of stochastic carbon dioxide emissions from fossil fuels and carbon sequestration by forests chance constraint programming is used to analyze the role of stochastic carbon sinks for national and eu wide compliance costs the analytical results show that the inclusion of the carbon sink option can reduce costs for low enough marginal cost and risk discount but also that costless carbon sinks as by products from forestry are not part of a cost effective solution under a high reliability concern cost savings are reduced due to risk discounting under a reliability concern in particular when assigning chebyshev s inequality as compared with a normal probability distribution it is also shown that the supply of forest sinks on the market depends on the differences in marginal abatement cost between the trading and the non trading sectors and in risk discounting between achievements of the ets cap and the national commitment relatively low marginal abatement cost in the non trading sector and high risk discounting of national commitment achievements increase the supply of sinks in the market and hence reduces the equilibrium price the empirical application illustrates the importance of risk discounting for the magnitude of cost savings obtained from introducing forest carbon sinks in the eu ets and national commitments

joining the ccs club the economics of co2 pipeline projects this paper examines the conditions for a widespread adoption of carbon capture transport and storage ccs by a group of emitters that can be connected to a common co2 pipeline it details a modeling framework aimed at assessing the critical value in the charge for the co2 emissions required for each of the emitters to decide to implement capture capabilities this model can be used to analyze how the tariff structure imposed on the co2 pipeline operator modifies the overall cost of co2 abatement via ccs this framework is applied to the case of a real european co2 pipeline project we find that the obligation to use cross subsidy free pipeline tariffs has a minor impact on the minimum co2 price required to adopt the ccs in contrast the obligation to charge non discriminatory prices can either impede the adoption of ccs or significantly raise that price besides which we compared two alternative regulatory frameworks for co2 pipelines a common european organization as opposed to a collection of national regulations the results indicate that the institutional scope of that regulation has a limited impact on the adoption of ccs compared to the detailed design of the tariff structure imposed on pipeline operators

inventories and sticky prices more on the microfoundations of macroeconomics the role of inventories in making prices sticky is studied by analyzing a dynamic linear quadratic model of a monopoly firm facing stochastic demand but able to store its finished goods in inventory it is shown that in contrast to the usual presumption firms that exhibit the smallest output responses to demand fluctuations may also exhibit the smallest price fluctuations specifically firms which have very flexible inventory storage facilities or are subjected to very transitory demand shocks will rely on inventories as buffers and will change neither production nor price very much on the other hand firms which have very inflexible storage facilities or whose demand shocks are quite permanent will display large swings in both price and output the standard assumption about inventory carrying costs that has been used in the literature that they are linear is shown to imply that production is impervious to fluctuations in demand it is also established that prices may respond more strongly to positive demand shocks than to negative ones if it is impossible to hold negative inventories i e to have unfilled orders the model offers an explanation for stickiness in relative prices however under certain circumstances it may help explain the persistence of inflation this abstract was borrowed from another version of this item

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 c 2006 elsevier b v all rights reserved