regulation by simulation the role of production cost models in electricity planning and pricing this paper is a case study on the role of complex computer simulation models in the regulation of the electricity industry the analysis focuses on electricity production cost simulation models as they are used to set prices for certain nonutility generators in california this represents an early part of the trend toward markets for electric power and away from pure monopoly supply the introduction of even limited competition creates conditions both favoring and hindering the reliability of cost estimates and demonstrates the sensitivity of results to problem specification and model implementation attention is focused on the representation of power system operational constraints particularly the unit commitment problem in the modeling process and their effect on the prices which result examples from the litigation history illustrate the problem of managing the strategic use and abuse of modeling techniques for competitive advantage highly structured procedures for using models in such situations offer some constraints on manipulation by competing parties otherwise experts are apt to overwhelm regulators

economic valuation of the threat posed by the establishment of the asian tiger mosquito in australia invasive species policy could be better informed if we understood how much people value reductions in the risks posed by these organisms this study investigates the public s willingness to pay wtp for additional measures to reduce the risk of invasion of the australian mainland by the asian tiger mosquito atm the study contributes to the literature by applying a stated preference method to estimate the public s wtp to reduce the risk of an atm invasion expressed as a change in probability it is the first ex ante invasive species analysis to test over two discrete invasion reduction probabilities based on management effort further to overcome the challenges in valuing changes in probabilities the study presented respondents with a well defined discrete difference in the final probability with one scenario reducing risk from 50 to 25 and the other from 50 to 5 we find a significant difference in the mean wtp values between these two scenarios a 67 vs a 90 the overall conclusion is that estimated benefits of reducing the probability of an atm incursion outweigh the costs

optimal clustering of time periods for electricity demand side management several pure binary integer optimization models are developed for clustering time periods by similarity for electricity utilities seeking assistance with pricing strategies the models include alternative objectives for characterizing various notions of within cluster distances admit as feasible only clusters that are contiguous and allow for circularity where time periods at the beginning and end of the planning cycle may be in the same cluster restrictions upon cluster size may conveniently be included without the need of additional constraints the models are populated with a real world dataset of electricity usage for 93 buildings and solutions and run times attained by conventional optimization software are compared with those by dynamic programming or by a greedy algorithm applicable to one of the models that run in polynomial time the results provide time of use segments that an electricity utility may employ for selective pricing for peak and off peak time periods to influence demand for the purpose of load leveling

anticipated discrimination choices and performance experimental evidence abstract this paper studies experimentally whether potential perceived discrimination affects decisions in a labor market setting with different stereotypes participants are assigned to a seven person group and randomly allocated a role as a firm or worker in each group there are five workers and two firms the only information firms have about each worker is a self selected avatar male female or neutral representing a worker s gender each firm then decides which worker to hire female workers react to potential discrimination when they know the task is math related but not otherwise men choose similar avatar patterns regardless of the task men do perform at much higher levels in the math related task but there is no difference in performance in the emotion recognition task where there is a strong female stereotype

when performance trumps gender bias joint vs separate evaluation gender bias in the evaluation of job candidates has been demonstrated in business government and academia yet little is known about how to overcome it blind evaluation procedures have been proven to significantly increase the likelihood that women musicians are chosen for orchestras and they are employed by a few companies we examine a new intervention to overcome gender bias in hiring promotion and job assignments an evaluation nudge in which people are evaluated jointly rather than separately regarding their future performance evaluators are more likely to base their decisions on individual performance in joint than in separate evaluation and on group stereotypes in separate than in joint evaluation making joint evaluation the profit maximizing evaluation procedure our work is inspired by findings in behavioral decision research suggesting that people make more reasoned choices when examining options jointly rather than separately and is compatible with a behavioral model of information pr

how competitiveness may cause a gender wage gap experimental evidence abstract we show that choices in competitive behavior may entail a gender wage gap in our experiments employees first choose a remuneration scheme competitive tournament vs piece rate and then conduct a real effort task employers know the pie size the employee has generated the remuneration scheme chosen and the employee s gender employers then decide how the pie will be split as in a dictator game whereas employers do not discriminate by gender when tournaments are chosen they take substantially and significantly more from female employees who choose piece rate remuneration a discriminatory wage gap occurs which cannot be attributed to employees performance

optimal economic dispatch and risk management of thermal power plants in deregulated markets this paper presents a methodology for the valuation optimization market margin and credit risk management of gas fired power plants and associated tolling contracts term structure models for the power and gas forward curves are employed to facilitate hedging and risk adjustment and for improved forecasting of short term prices the model for the power forward curve is capable of reproducing the important phenomena often observed in power markets including spot price spikes and spike clustering negative prices and the empirically observed volatility term structures of power and gas forward prices as well as the correlation term structure between these forward curves the method solves the stochastic dynamic optimization problem that arises from the inclusion of the various operational constraints of gas fired power plants including minimum uptime and downtime requirements ramp rate restrictions and costs variable output and efficiency rates and minimum generation levels the model involves the so

the value of nonindigenous species risk assessment in international trade abstract managing the introduction of nonindigenous species is becoming a major goal of policy makers at regional national and international scales here we investigate at the national level the ideal design and expected net benefits of a risk assessment program for evaluating the desirability of nonindigenous species imports we show how to enhance the statistical rigor of such a system by correcting a common non random sampling problem encountered in the data this correction enables model output to be interpreted in an economically relevant way and facilitates a theoretically rigorous characterization of the balance between trade and nonindigenous species establishment risk using reptiles and amphibians imported to the u s as a case study we characterize economic outcomes over a range of cases and demonstrate substantial expected returns to such a screening program relative to the current effectively open door policy our results are informative for the current debate in the u s about whether to require federal agencies to apply risk assessment before allowing a species for import the framework presented decomposes a complex argument about risk management into component economic and statistical parts allowing for debate and improved understanding over each element to inform the overall program in a transparent fashion

uncertainty management in the unit commitment problem uncertainty in power systems operations has been traditionally managed by multistage decision making and operating reserve requirements a familiar example of multistage decisions is day ahead unit commitment and real time economic dispatch an alternate approach for managing uncertainty is a stochastic formulation which allows the explicit modeling of the sources of uncertainty this paper compares stochastic and reserve methods and evaluates the benefits of a combined approach for the efficient management of uncertainty in the unit commitment problem numerical studies show that unit commitment solutions obtained for the combined approach are robust and superior with respect to the traditional approach in terms of both economics and reliability metrics

the econometrics of damage control why specification matters the contribution of damage control agents to production differs fundamentally from that of standard inputs lands labor capital this paper develops an econometric model based on the key characteristics of damage control agents and examines its properties it demonstrates that standard production function specifications overestimate damage control agent productivity and have erroneous implications for the evolution of damage control agent productivity and use in response to changing environments e g the spread of pest resistance it also proposes several alternative specifications and discusses methods for estimating them

the control of invasive species on private property with neighbor to neighbor spillovers invasive pests cross property boundaries property managers may have private incentives to control invasive species despite not having sufficient incentive to fully internalize the external costs of their role in spreading the invasion each property manager has a right to future use of his own property but his property may abut others properties enabling spread of an invasive species the incentives for a foresighted property manager to control invasive species have received little attention we consider the efforts of a foresighted property manager who has rights to future use of a property and has the ability to engage in repeated discrete control activities we find that higher rates of dispersal associated with proximity to neighboring properties reduce the private incentives for control controlling species at one location provides incentives to control at a neighboring location control at neighboring locations are strategic complements and coupled with spatial heterogeneity lead to a weaker link public good problem in which each property owner is unable to fully appropriate the benefits of his own control activity future use rights and private costs suggest that there is scope for a series of coase like exchanges to internalize much of the costs associated with species invasion pigouvian taxes on invasive species potentially have qualitatively perverse behavioral effects a tax with a strong income effect e g failure of effective revenue recycling can reduce the value of property assets and diminish the incentive to manage insects on one s own property

incorporating fuel constraints and electricity spot prices into the stochastic unit commitment problem the electric power industry is going through deregulation as a result the load on the generating units of a utility is becoming increasingly unpredictable furthermore electric utilities may need to buy power or sell their production to a power pool that serves as a spot market for electricity these trading activities expose utilities to volatile electricity prices in this paper we present a stochastic model for the unit commitment that incorporates power trading into the picture our model also accounts for fuel constraints and prices that may vary with electricity prices and demand the resulting model is a mixed integer program that is solved using lagrangian relaxation and bender s decomposition using this solution approach we solve problems with 729 demand scenarios on a single processor to within 0 1 of the optimal solution in less than 10 minutes our numerical results indicate that significant savings can be achieved when the spot market is entered into the problem and when stochastic policy is adopted instead of a deterministic one

the influence of distributed generation penetration levels on energy markets planning of national energy policies brings new dilemmas with the introduction of distributed generators dg economic theory suggests that a perfectly competitive market would lead to efficient pricing in the absence of competition regulators play a fundamental role in attracting reasonably priced finance in order to maintain refurbish and increase the infrastructure and provide services at a reasonable cost energy market price equilibrium is mainly dependent on suppliers generators energy sources and demand represented by conventional utility grid users its behavior is similar to that of other commodities as generation becomes less centralized with the increasing economic viability of renewable energy sources new suppliers are being connected to the grid such evolution means the transition from a monopolistic market to a broader and more open environment with an increasing number of competitors we make use of variational inequalities to model a hypothetical dg market in different scenarios from monopoly to oligopoly to open market such an approach enables different equilibrium outcomes due to different dg penetration levels based on these findings we argue that energy policies for such markets must be developed according to each specific stage of the grid s lifecycle we show how energy policies and market regulations may affect such a transition which may be catastrophic if not managed properly and which is dependent on the energy mix

valuation and optimal operation of electric power plants in competitive markets we present an algorithm for the valuation and optimal operation of hydroelectric and thermal power generators in deregulated electricity markets real options theory is used to derive nonlinear partial integro differential equations pides for the valuation and optimal operating strategies of both types of facilities the equations are designed to incorporate a wide class of spot price models that can exhibit the same time dependent mean reverting dynamics and price spikes as those observed in most electricity markets particular attention is paid to the operational characteristics of real power generators for thermal power plants these characteristics include variable start up times and costs control response time lags minimum generating levels nonlinear output functions and structural limitations on ramp rates for hydroelectric units head effects and environmental constraints are addressed we illustrate the models with numerical examples of a pump storage facility and a thermal power plant this pide framework can achieve high levels of computational speed and accuracy while incorporating a wide range of spot price dynamics and operational characteristics

deregulated power prices comparison of volatility abstract we examine electrical power price variability for 14 deregulated markets power price volatility is measured by price velocity the daily average of the absolute value of price change per hour deregulated markets show a wide variability in price velocity some price velocity is expected and arises from the daily diurnal price pattern which differs significantly between markets even when the expected daily variability in price is removed the residual unexpected variability differs between markets some deregulated markets most notably britain and spain show patterns that are predictable and consistent and have low values of unexpected price velocity these markets create a climate conducive to consumers facing the market through real time pricing and shaping consumption behaviors in response to price changes other markets for example south australia and alberta have patterns that are inconsistent and irregular and hence are hard for a customer to interpret a customer in such a market will have a higher incentive to avoid demand side management and escape risk through hedging mechanisms

deregulated power prices comparison of diurnal patterns we examine electrical power price and in particular its daily and average weekday vs weekend pattern of change for 14 deregulated markets power price in deregulated markets shows fundamentally different patterns north american markets show a monotonic diurnal weekday price pattern while all other markets studied show more than one price peak deregulated power markets differ in maximum vs minimum daily average price and in average weekday to weekend price in turn creating a different incentive for a consumer to time shift power consuming activities markets differ in the extent to which a small fraction of the days shapes the average diurnal pattern and value of price deregulated markets show a wide variation in the correlation between load and price some deregulated markets most notably britain and spain show patterns that are predictable and consistent and hence that can encourage a customer to shape consumption behaviors other markets for example south australia have patterns that are inconsistent and irregular and hence are hard for a customer to interpret a customer in such a market will have a higher incentive to escape risk through hedging mechanisms

a stochastic programming approach to power portfolio optimization we consider a power portfolio optimization model that is intended as a decision aid for scheduling and hedging dash in the wholesale power market our multiscale model integrates the unit commitment model with financial decision making by including the forwards and spot market activity within the scheduling decision model the methodology is based on a multiscale stochastic programming model that selects portfolio positions that perform well on a variety of scenarios generated through statistical modeling and optimization when compared with several commonly used fixed mix policies our experiments demonstrate that the dash model provides significant advantages

risk constrained generation asset arbitrage in power systems a competitive generating company genco can maximize its payoff by optimizing its generation assets this paper considers the genco s arbitrage problem using stochastic price based unit commitment while considering the associated risks the genco may consider arbitrage opportunities in purchases from qualifying facilities qfs as well as simultaneous trades with spot markets for energy ancillary services fuel and emission allowance the tradeoff between maximizing expected payoffs and minimizing risks due to market price uncertainties is modeled explicitly by including the expected downside risk as a constraint the downside risk is defined as the unfulfilled profit the monte carlo simulation is applied to generate scenarios and scenario reduction techniques are applied to reduce the number of scenarios while maintaining a good approximation of the exact solution the proposed case studies illustrate the significance of arbitrage in multi commodity markets and the importance of considering the uncertainty of market prices

hourly electricity prices in day ahead markets this paper focuses on the characteristics of hourly electricity prices in day ahead markets in these markets quotes for day ahead delivery of electricity are submitted simultaneously for all hours in the next day the same information set is used for quoting all hours of the day the dynamics of hourly electricity prices does not behave as a time series process instead these prices should be treated as a panel in which the prices of 24 cross sectional hours vary from day to day this paper introduces a panel model for hourly electricity prices in day ahead markets and examines their characteristics the results show that hourly electricity prices exhibit hourly specific mean reversion and that they oscillate around an hourly specific mean price level furthermore a block structured cross sectional correlation pattern between the hours is apparent

value of an option to purchase electric power the case of uncertain consumption abstract large manufacturers and corporations often purchase options on power to protect themselves against unanticipated price increases this paper analyzes the impact of uncertainty in power consumption by a corporation on the value of an option to purchase electric power because there is no economically viable method to store power these options are exercised to satisfy immediate consumption needs only the amount exercised may differ from the maximum amount contracted which in turn alters the payoffs that accrue to the option contract we apply a monte carlo methodology to show that consumption uncertainty may substantively lower the price of an option contract under different conditions

evaluation of different hedging strategies for commodity price risks of industrial cogeneration plants abstract in this paper we design and evaluate eight different strategies for hedging commodity price risks of industrial cogeneration plants price developments are parameterized based on eex data from 2008 to 2011 the probability distributions derived are used to determine the value at risk var of the individual strategies which are in a final step combined in a mean variance portfolio analysis for determining the most efficient hedging strategy we find that the strategy adopted can have a marked influence on the remaining price risk quarter futures are found to be particularly well suited for reducing market price risk in contrast spot trading of co 2 certificates is found to be preferable compared to forward market trading finally portfolio optimization shows that a mix of various hedging strategies can further improve the profitability of a heat based cogeneration plant

do women shy away from competition do men compete too much we examine whether men and women of the same ability differ in their selection into a competitive environment participants in a laboratory experiment solve a real task first under a noncompetitive piece rate and then a competitive tournament incentive scheme although there are no gender differences in performance men select the tournament twice as much as women when choosing their compensation scheme for the next performance while 73 percent of the men select the tournament only 35 percent of the women make this choice this gender gap in tournament entry is not explained by performance and factors such as risk and feedback aversion only playa negligible role instead the tournament entry gap is driven by men being more overconfident and by gender differences in preferences for performing in a competition the result is that women shy away from competition and men embrace it

risk constrained self scheduling of a thermal power producer this paper addresses the self scheduling problem of a price taker power producer it focuses on risk modeling emphasizing the tradeoff existing between maximum profit and minimum risk the paper analyzes a self scheduling model that considers simultaneously profit and risk this model is formulated as a mixed integer quadratic programming problem which is solved using commercially available software relevant results from a realistic case study are discussed

stochastic programming based bounding of expected production costs for multiarea electric power system a bounding based method is developed for estimating the expected operation cost of a multiarea electric power system in which transmission capacity limits interarea flows costs include the expense of power generation and losses suffered by consumers because of supply shortfalls averaged over random generator outage states and varying demand levels the calculation of this expectation termed the distribution problem is a large scale stochastic programming problem rather than solving this problem directly lower and upper bounds to the expected cost are created using two more easily solved models the lower bound is from a deterministic model based on the expected value of the uncertain inputs the upper bound results from a linear program with recourse whose structure permits relatively quick solution by benders decomposition the benders subproblems use probabilistic production costing which can be viewed as a stochastic greedy algorithm to consider random outages and demands these bounds are iteratively tightened by partitioning realizations of the random variables into subsets based on the status of larger generators and a cluster analysis of demands computational examples are described and application issues addressed

women in economics moving up or falling off the academic career ladder copyright 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 by the american economic association

efficient modeling and forecasting of electricity spot prices abstract the increasing importance of renewable energy especially solar and wind power has led to new forces in the formation of electricity prices hence this paper introduces an econometric model for the hourly time series of electricity prices of the european power exchange epex which incorporates specific features like renewable energy the model consists of several sophisticated and established approaches and can be regarded as a periodic var tarch with wind power solar power and load as influences on the time series it is able to map the distinct and well known features of electricity prices in germany an efficient iteratively reweighted lasso approach is used for the estimation moreover it is shown that several existing models are outperformed by the procedure developed in this paper

commitment of electric power generators under stochastic market prices a formulation for the commitment of electric power generators under a deregulated electricity market is proposed the problem is expressed as a stochastic optimization problem in which expected profits are maximized while meeting demand and standard operating constraints under an assumption of perfect competition when an electric power producer has the option of trading electricity at market prices a unit commitment schedule can be obtained by optimizing the self commitment of each unit separately subject to stochastic prices three certainty equivalent formulations of the stochastic self commitment problem are provided the procedures involve application of dynamic programming statistical analysis and asymptotic probability computations the price of electricity is represented by a stochastic model depending on demand generating unit reliabilities and temperature fluctuations we use several approximation methods normal edgeworth series expansion and monte carlo simulation for computing the required probability distributions numerical examples are provided for a market consisting of 150 generating units

why do electricity prices jump empirical evidence from the nordic electricity market the paper empirically explores the possible causes behind electricity price jumps in the nordic electricity market nord pool a time series model a mixed garch earji jump model capturing the com

optimization of electricity retailer s contract portfolio subject to risk preferences when an electricity retailer faces volume risk in meeting load and spot price risk in purchasing from the wholesale market conventional risk management optimization methods can be quite inefficient for the management of an electricity contract portfolio in this context we develop a multistage stochastic optimization approach which accounts for the uncertainties of both electricity prices and loads and which permits the specification of conditional value at risk requirements to optimize hedging across intermediate stages in the planning horizons our experimental results based on real data from nordpool suggest that the modeling of price and load correlations is particularly important the sensitivity analysis is extended to characterize the behavior of retailers with different risk attitudes thus we observe that a risk neutral retailer is more susceptible to price related than load related uncertainties in terms of the expected cost of satisfying the load and that a risk averse retailer is especially sensitive to the drivers of the forward risk premium

can gender parity break the glass ceiling evidence from a repeated randomized experiment this paper studies whether the gender composition of recruiting committees matters we make use of the unique evidence provided by spanish public examinations where the allocation of candidates to evaluating committees is random we analyse how the chances of success of 150 000 female and male candidates for positions in the four main corps of the spanish judiciary from 1987 to 2007 were affected by the gender composition of their evaluation committee we find that a female male candidate is significantly less likely to be hired whenever she he is randomly assigned to a committee where the share of female male evaluators is relatively greater evidence from multiple choice tests suggests that this is due to the fact that female majority committees overestimate the quality of male candidates

the extent of the market examines the classical theory of the market in this paper authors consider the role of price market determination price movement in competitive and monopolistic markets extension of commodity markets

short term generation asset valuation a real options approach this paper discusses using real options to value power plants with unit commitment constraints over a short term period we formulate the problem as a multistage stochastic problem and propose a solution procedure that integrates forward moving monte carlo simulation with backward moving dynamic programming we assume that the power plant operator maximizes expected profit by deciding in each hour whether or not to run the unit that a certain lead time for commitment and decommitment decisions is necessary to start up and shut down a unit and that these commitment decisions once made are subject to physical constraints such as minimum uptime and downtime we also account for the costs associated with starting up and shutting down a unit last we assume that there are hourly markets for both electricity and the fuel used by the generator and that their prices follow ito processes using numerical simulation we show that failure to consider physical constraints may significantly overvalue a power plant

merit order effects of renewable energy and price divergence in california s day ahead and real time electricity markets abstract we answer two policy questions 1 what are the estimated merit order effects of renewable energy in the california independent system operator s caiso s day ahead market dam and real time market rtm and 2 what causes the hourly dam and rtm prices to systematically diverge the first question is timely and relevant because if the merit order effect estimates are small california s renewable energy development is of limited help in cutting electricity consumers bills but also has a lesser adverse impact on the state s investment incentive for natural gas fired generation the second question is related to the efficient market hypothesis under which the hourly rtm and dam prices tend to converge using a sample of about 21 000 hourly observations of caiso market prices and their fundamental drivers during 12 12 2012 04 30 2015 we document statistically significant estimates p value 0 01 for the dam and rtm merit order effects this finding lends support to california s adopted procurement process to provide sufficient investment incentives for natural gas fired generation we document that the rtm dam price divergence partly depends on the casio s day ahead forecast errors for system loads and renewable energy this finding suggests that improving the performance of the caiso s day ahead forecasts can enhance trading efficiency in california s dam and rtm electricity markets

choosing between adaptation and prevention with an increasing probability of a pandemic abstract the risk of pandemics is increasing driven by changes in human behavior and climate both of which are difficult for policymakers to control there are two main strategies available for reacting to these changes this paper considers the decision to invest in either adaptation domestic capital or prevention foreign capital before a pandemic in an interval of time when pandemic risk is increasing this paper demonstrates how relatively small investments in the two strategies can provide large savings through smaller expected future damages the technical relationships between adaptation prevention and risk also determine the optimal mixture of investment over time as risk increases the technical relationships between these three stocks causes the optimal mixture of strategies to change over time

sex discrimination in restaurant hiring an audit study in an audit study of sex discrimination in hiring comparably matched pairs of men and women applied for jobs as waiters and waitresses at restaurants in philadelphia in high price restaurants where earnings are higher job applications from women had an estimated probability of receiving a job offer that was lower by about 0 4 and an estimated probability of receiving an interview that was lower by about 0 35 both estimated differentials are statistically significant additional evidence suggests that customer discrimination partly underlies the hiring discrimination

orchestrating impartiality the impact of blind auditions on female musicians a change in the audition procedures of symphony orchestras adoption of blind auditions with a screen to conceal the candidate s identity from the jury provides a test for sex biased hiring using data from actual auditions in an individual fixed effects framework we find that the screen increases the probability a woman will be advanced and hired although some of our estimates have large standard errors and there is one persistent effect in the opposite direction the weight of the evidence suggests that the blind audition procedure fostered impartiality in hiring and increased the proportion women in symphony orchestras

field experiments of discrimination in the market place controlled experiments using matched pairs of bogus transactors to test for discrimination in the marketplace have been conducted for over 30 years and have extended across 10 countries significant persistent and pervasive levels of discrimination have been found against non whites and women in labour housing and product markets rates of employment discrimination against non whites in excess of 25 have been measured in australia europe and north america a small number of experiments have also investigated employment discrimination against the disabled in britain and the netherlands and against older applicants in the united states

self commitment of combined cycle units under electricity price uncertainty day ahead energy market clearing relies on a deterministic equivalent model with a limited time horizon which may lead to inefficient scheduling of generating units from the point of view of generators for this reason generators may wish to assume the risk of self committing their units with the hope of securing greater profits this phenomenon may reduce the room for economic signals in the day ahead market in this paper we investigate the influence of risk aversion and price volatility on the decision of generators to self commit units we present a stochastic programming model for self committing combined cycle units under price uncertainty with a conditional value at risk criterion we use benders decomposition to solve the problem and present results on a case study to draw conclusions

take a risk preferring prevention over control of biological invaders abstract scientists have argued that invasive species can be managed most cost effectively with greater investments in prevention further under ideas like the precautionary principle it is reasonable to expect that a cautious manager would use more prevention relative to control because it keeps more invaders out yet this is not typically done in many cases private and public resources are invested primarily to control existing invaders rather than to prevent new invasions managers frequently wait until after invaders have arrived and then scramble to limit the damages we believe these paradoxical decisions can be understood by recognizing the link between typical human preferences for risk bearing and the technology of risk reduction we demonstrate quantitatively how managers perceived to be cautious or averse to risk tend to shy away from prevention relative to control this counterintuitive result arises because control is a safer choice than prevention because its productivity is relatively less risky it works to remove existing invaders from the system in contrast the productivity of prevention is more uncertain because prevention only reduces the chance of invasion it does not eliminate it and invasion may not occur even in the absence of prevention managers averse to risk will inherently avoid as much uncertainty as possible whether the source of uncertainty regards ecological outcomes or economic productivity implications for environmental decision making are clear in invasive species management if managers act as though they are risk averse their caution can backfire when it leads to more control rather than prevention the social consequences of this choice are a greater probability of future invasions and lower social welfare our results suggest that social welfare is highest when managers were willing to take a risk with prevention

a portfolio balancing approach to natural capital and liabilities managing livestock and wildlife diseases with cross species transmission researchers often refer to stocks of desirable natural resources as natural capital and stocks of undesirable species as natural liabilities the logical extension is that when these natural resources interact then the ecosystem is a collection or portfolio of natural capital and liabilities however natural capital and liabilities held in an ecosystem portfolio are more complex to manage than financial asset portfolios the key problem in a financial asset portfolio is adjusting the rates of return on assets for risk and correlation of risk in contrast the returns on natural assets and liabilities require many other adjustments arising from stock related returns and depreciation that endogenously depend on both stocks and controls including interactions among these variables this means ecosystem portfolio analysis extends beyond the consideration of uncertainty and involves understanding complex economic ecological tradeoffs even in a deterministic setting we use capital theory in the context of a deterministic bioeconomic model of valuable wildlife livestock and a pathogen that can be passed between them to develop a portfolio balancing approach to understanding the tradeoffs associated with ecosystem management this specific ecosystem is highly relevant to conservation health and livestock agriculture within the context of this example we also explore issues of mitigation and adaptation to disease risks and the management implications of cross species transmission a final contribution is to examine how exports and infection risks influence the ecological thresholds that epidemiologists often focus on to guide disease management

offer stack optimization in electricity pool markets we consider a generator making offers of energy into an electricity pool market for a given time period it must submit an offer stack consisting of a fixed number of quantities of energy and prices at which it wants these quantities dispatched we assume that the generator cannot offer enough power to substantially affect the market price so the optimal response would be to offer energy at marginal cost however the market rules do not permit an arbitrary function so the problem is to find an offer stack approximating marginal cost in a way that maximizes its profit we give optimality conditions for this problem and derive an optimization procedure based on dynamic programming this procedure is illustrated by applying it to several examples with different costs of production

a profit based unit commitment ga for the competitive environment as the electrical industry restructures many of the traditional algorithms for controlling generating units need modification or replacement previously utilized to schedule generation units in a manner that minimizes costs while meeting all demand the unit commitment uc algorithm must be updated a uc algorithm that maximizes profit will play an essential role in developing successful bidding strategies for the competitive generator simply bidding to win contracts is insufficient bidding strategies must result in contracts that on average cover the total generation costs no longer guaranteed to be the only electricity supplier a generation company s share of the demand will be more difficult to predict than in the past removing the obligation to serve softens the demand constraint in this paper the authors provide a price profit based uc formulation which considers the softer demand constraint and allocates fixed and transitional costs to the scheduled hours the authors describe a genetic algorithm solution to this new uc problem and present results for an illustrative example

how costly is diversity affirmative action in light of gender differences in competitiveness affirmative action is often criticized for causing reverse discrimination and lowering the qualifications of those hired under the policy however the magnitude of such adverse effects depends on whether the best suited candidate is hired absent the policy indeed affirmative action may compensate for the distortion discrimination imposes on the selection of candidates this paper asks whether affirmative action can have a similar corrective impact when qualified individuals fail to apply for a job we evaluate the effect of introducing a gender quota in an environment where high performing women fail to enter competitions they can win we show that guaranteeing women equal representation among winners increases their entry the response exceeds that predicted by the change in probability of winning and is in part driven by women being more willing to compete against other women the consequences are substantial as the boost in supply essentially eliminates the anticipated costs of the policy this paper was accepted by uri gneezy behavioral economics

the impact of heat waves on electricity spot markets abstract thermoelectric power plants depend on cooling water drawn from water bodies low river run off and or high water temperatures limit a plant s production capacity this problem may intensify with climate change our study quantifies the impact of forced capacity reductions on market prices production costs consumer and producer surplus as well as emissions by means of a bottom up power generation system model first we simulate the german electricity spot market during the heat wave of 2006 then we conduct a sensitivity study that accounts for future climatic and technological conditions we find an average price increase of 11 during the heat wave 2006 which is even more pronounced during times of peak demand production costs accumulate to an additional but moderate 16 m due to the price increase producers gain from the heat wave whereas consumers disproportionately bear the costs carbon emissions in the german electricity sector increase during the heat wave the price and cost effects are more pronounced and increase significantly if assumptions on heat sensitive demand hydropower capacity net exports and capacity reductions are tightened these are potential additional effects of climate change hence if mitigation fails or is postponed globally the impacts on the current energy system are very likely to rise increases in feed in from renewable resources and demand side management can counter the effects to a considerable degree countries with a shift toward a renewable energy supply can be expected to be much less susceptible to cooling water scarcity than those with a high share of nuclear and coal fired power plants

a fuzzy optimization approach to dynamic economic dispatch considering uncertainties in this paper the authors propose a fuzzy optimization approach to dynamic economic dispatch considering the uncertainties in deregulated energy and reserve markets the methodology was developed from the viewpoint of a generation company wishing to maximize its own profit and to hedge its risks as a participant in the energy market and 10 min spinning reserve market the uncertainties in the current paper were represented with fuzzy numbers and consist of the demand and reserves required in each market prices cleared in each market and the probability that reserves are called upon in actual operation the energy and reserve markets were coordinated by the generator ramp rate limits the optimal amounts of power and reserve were determined by solving the optimization problem two reserve payment methods payment for power delivered and payment for reserve allocated were investigated in this paper

choice under uncertainty problems solved and unsolved ffifteen years ago the theory of choice under uncertainty could be considered one of the success stories of economic analysis it rested on solid axiomatic foundations it had seen important breakthroughs in the analytics of risk risk aversion and their applications to economic issues and it stood ready to provide the theoretical underpinnings for the newly emerging information revolution in economics 1 today choice under uncertainty is a field in flux the standard theory is being challenged on several grounds from both within and outside economics the nature of these challenges and of our profession s responses to them is the topic of this paper

a stochastic programming model for a day ahead electricity market with real time reserve shortage pricing we present a multi period stochastic mixed integer programming model for power generation scheduling in a day ahead electricity market the model considers various scenarios and integrates the idea of reserve shortage pricing in real time instead of including all the possible scenarios we parsimoniously select a certain number of scenarios to limit the size of the model as realistic size models are still intractable for exact methods we propose a heuristic solution methodology based on scenario rolling that is capable of finding good quality feasible solutions within reasonable computation time

coordination between medium term generation planning and short term operation in electricity markets this paper analyzes the coordination between medium term generation planning and short term operation in electricity markets this coordination is particularly important from a practical point of view in order to guarantee that certain aspects of the operation that arise in the medium term level are explicitly taken into account limited energy resources and obligatory use resources three different approaches are proposed in order to guarantee that short term decisions made by a generation company are consistent with its operation objectives formulated from a medium term perspective these approaches make use of technical and economic signals to coordinate both time scopes primal information dual information and resource valuation functions this paper presents the main advantages and drawbacks of the three approaches and applies them to a case study that uses a conjectural variation based representation of the market

wind storage interconnection and the cost of electricity generation abstract we evaluate how increasing wind generation affects wholesale electricity prices balancing payments and the cost of subsidies using the irish single electricity market sem as a test system with hourly data from 1 january 2008 to 28 august 2012 we model the spot market using a system of seemingly unrelated regressions sur where the regressions are the 24 hours of the day wind has a negative impact on the system marginal price with every mwh increase in wind generation equal to about 0 2 of the average wind generation in our sample leading to a decrease of the system marginal price of 0 018 mwh or about 0 3 of its average value we use time series models to analyse the balancing market and show that wind generation increases balancing payments as do the forecast errors of demand and wind every mwh of additional wind generation is associated with an increase in constraint payments of 3 2 or about 0 01 lack of storage increases the impact of wind on balancing payments whereas the lack of interconnection has no effect overall wind decreases costs through its effect on the electricity price more than it increases constraint payments even when storage is on outage the effect of wind remains positive after including the cost of subsidies given to wind generation

a probability model for the electricity price duration curve under an oligopoly market in this paper we propose a new formulation for the price duration curve pdc using probability considerations and provide a procedure for constructing it this curve is expected to be useful in the long term prediction of market prices and is similar in spirit to the load duration curve it shows the proportion of time over a given time horizon during which the real time market price of electricity is expected to exceed specified dollar amounts the price over a long term is a stochastic quantity that depends on physical factors such as production cost load generation availability unit commitment and transmission constraints it also depends on economic factors such as strategic bidding and load elasticity we illustrate a procedure for constructing a stochastic system based model for the pdc taking into account the randomness associated with load and generator outages the effects of unit commitment transmission congestion and transmission outages are not considered we use two economic models one is due to bertrand and represents perfect competition the other model is due to rudkevich et al who have given a closed form expression for the market clearing price in an oligopoly consisting of several identical firms

coordinating fuel inventory and electric power generation under uncertainty the authors discuss the problem of hedging between the natural gas and electric power markets based on multiple forecasts for natural gas prices natural gas demand and electricity prices a stochastic optimization model advises a decision maker on when to buy or sell natural gas and when to transform gas into electricity for relatively small models branch and bound solves the problem to optimality larger models are solved using benders decomposition and lagrangian relaxation they apply their approach to the system of an electric utility and succeed in solving problems with 50000 binary variables in less than 4 min to within 1 16 of the optimal value

experimental methods for the general economist five lessons from the lab i review five primary results from experimental economics that impact the economics profession as a whole these results regard the relative un importance of subject sophistication in laboratory markets the importance of gender on economic outcomes the propensity for humans to behave in less than fully rational ways the importance of trading institutions on economic performance and the behavioral relevance of economic theory i find that economics as a profession has benefited from the use of experimental methods by fostering a dialogue between theorists and empiricists better informing policy and improving data collection techniques

economic incentives for managing filterable biological pollution risks from trade infectious livestock disease problems are biological pollution problems prior work on biological pollution problems generally examines the efficient allocation of prevention and control efforts but does not identify the specific externalities underpinning the design of efficiency enhancing policy instruments prior analyses also focus on problems where those being damaged do not contribute to externalities we examine a problem where the initial biological introduction harms the importer and then others are harmed by spread from this importer here the externality is the spread of infection beyond the initial importer this externality is influenced by the importer s private risk management choices which provide impure public goods that reduce disease spillovers to others making disease spread a filterable externality we derive efficient policy incentives to internalize filterable disease externalities given uncertainties about introduction and spread we find efficiency requires incentivizing an importer s trade choices along with self protection and abatement efforts in contrast to prior work that targets trade alone perhaps surprisingly we find these incentives increase with importers private risk management incentives and with their ability to directly protect others in cases where importers can spread infection to each other we find filterable externalities may lead to multiple nash equilibria

risk constrained bidding strategy with stochastic unit commitment this paper develops optimal bidding strategies based on hourly unit commitment in a generation company genco that participates in energy and ancillary services markets the price based unit commitment problem with uncertain market prices is modeled as a stochastic mixed integer linear program the market price uncertainty is modeled using the scenario approach monte carlo simulation is applied to generate scenarios scenario reduction techniques are applied to reduce the size of the stochastic price based unit commitment problem and postprocessing is applied based on marginal cost of committed units to refine bidding curves the financial risk associated with market price uncertainty is modeled using expected downside risk which is incorporated explicitly as a constraint in the problem accordingly the proposed method provides a closed loop solution to devising specific strategies for risk based bidding in a genco illustrative examples show the impact of market price uncertainty on genco s hourly commitment schedule and discuss the way gencos could decrease financial risks by managing expected payoffs

multimarket optimal bidding for a power producer this paper considers a profit maximizing thermal producer that participates in a sequence of spot markets namely day ahead automatic generation control agc and balancing markets the producer behaves as a price taker in both the day ahead market and the agc market but as a potential price maker in the volatile balancing market the paper provides a stochastic programming methodology to determine the optimal bidding strategies for the day ahead market uncertainty sources include prices for the day ahead and agc markets and balancing market linear price variations with the production of the thermal producer results from a realistic case study are reported and analyzed conclusions are duly drawn

electricity spot price dynamics beyond financial models we reveal properties of electricity spot prices that cannot be captured by the statistical models commonly used to model financial asset prices that are increasingly used to model electricity prices using more than eight years of half hourly spot price data from the new zealand electricity market we find that the half hourly trading periods fall naturally into five groups corresponding to the overnight off peak the morning peak daytime off peak evening peak and evening off peak the prices in different trading periods within each group are highly correlated with each other yet the correlations between prices in different groups are lower models adopted from the modeling of security prices that are currently applied to electricity spot prices are incapable of capturing this behavior we use a periodic autoregression to model prices instead showing that shocks in the peak periods are larger and less persistent than those in off peak periods and that they often reappear in the following peak period in contrast shocks in the off peak periods are smaller more persistent and die out perhaps temporarily during the peak periods current approaches to modeling spot prices cannot capture this behavior either