Insufficient Incentives for Investment in Electricity Generation

In theory, competitive electricity markets can provide incentives for efficient investment in generating capacity. We show that if consumers and investors are risk averse, investment is efficient only if investors in generating capacity can sign long-term contracts with consumers. Otherwise the uncovered price risk increases financing costs, reduces equilibrium investment levels, distorts technology choice towards less capital-intensive generation and reduces consumer utility. We observe insufficient levels of long-term contracts in existing markets, possibly because retail companies are not credible counter-parties if their final customer can switch easily. With consumer franchise, retailers can sign long-term contracts, but this solution comes at the expense of the idea of retail competition. Alternative capacity mechanisms to stimulate investment are discussed

Impact of Variable Renewable Energy on European Cross-Border Electricity Transmission

The estimated growth of Europe’s electricity demand and the policy goals of mitigating climate change result in an expected increase in variable renewable energy. A high penetration of wind and solar energy will bring several new challenges to the European electricity transmission network. The objective of this paper is to understand the effects of a high penetration of variable renewable energy sources (RES) on the demand for cross-border electricity transmission in Europe. EUPowerDispatch, a minimum cost dispatch model is used to compare the impacts of different electricity generation and transmission portfolios on cross-border electricity transmission in 2025. The analysis makes use of the best-estimate scenario developed by the European Network of Transmission System Operators for Electricity (ENTSO-E). Wind and solar energy curtailment needs and variations in load duration curves are analyzed for different scenarios. In addition, the role of hydro energy storage and pumping is analyzed as a complementary technology to transmission in the context of a high penetration of variable RES. The study shows that the planned expansion of the European transmission network is adequate for meeting the expected RES increase and it is needed to maintain the current level of security of supply in the face of the expected demand growth. If RES growth is faster than expected, cross-border transmission capacity will have to increase accordingly if significant RES curtailment is to be avoided.JRC.F.3-Energy securit

The Extent of Internet Auction Markets

Internet auctions attract numerous agents, but only a few become active bidders. A major difficulty in the structural analysis of internet auctions is that the number of potential bidders is unknown. Under the independent private value paradigm (IPVP)the valuations of the active bidders form a specific record sequence. This record sequence implies that if the number n of potential bidders is large, the number of active bidders is approximately 2 log n, explaining the relative inactivity. Empirical evidence for the 2 log n rule is provided. This evidence can also be interpreted as a weak test of the IPVP

Weak & Strong Financial Fragility

The stability of the financial system at higher loss levels is either characterized by asymptotic dependence or asymptotic independence. If asymptotically independent, the dependency, when present, eventually dies out completely at the more extreme quantiles, as in case of the multivariate normal distribution. Given that financial service firms' equity returns depend linearly on the risk drivers, we show that the marginals' distributions maximum domain of attraction determines the type of systemic (in-)stability. A scale for the amount of dependency at high loss lovels is designed. This permits a characterization of systemic risk inherent to different financial network structures. The theory also suggests the functional form of the economically relevant limit copulas

Tail index estimation: quantile driven threshold selection

The selection of upper order statistics in tail estimation is notoriously difficult. Most methods are based on asymptotic arguments, like minimizing the asymptotic mse, that do not perform well in finite samples. Here we advance a data driven method that minimizes the maximum distance between the fitted Pareto type tail and the observed quantile. To analyse the finite sample properties of the metric we organize a horse race between the other methods. In most cases the finite sample based methods perform best. To demonstrate the economic relevance of choosing the proper methodology we use daily equity return data from the CRSP database and find economic relevant variation between the tail index estimates

Using a bootstrap method to choose the sample fraction in tail index estimation

Tail index estimation depends for its accuracy on a precise choice of the sample fraction, i.e. the number of extreme order statistics on which the estimation is based. A complete solution to the sample fraction selection is given by means of a two step subsample bootstrap method. This method adaptively determines the sample fraction that minimizes the asymptotic mean squared error. Unlike previous methods, prior knowledge of the second order parameter is not required. In addition, we are able to dispense with the need for a prior estimate of the tail index which already converges roughly at the optimal rate. The only arbitrary choice of parameters is the number of Monte Carlo replications

Extremal behavior of solutions to a stochastic difference equation, with applications to ARCH processes

AbstractWe consider limit distributions of extremes of a process {Yn} satisfying the stochastic difference equation Yn-AnYn−1+Bn, n⩾1,Y0⩾0, where {An, Bn} are i.i.d. R2+-valued random pairs, A special case of interest is when {Yn} is derived from a first order ARCH process. Parameters of the limit law are exhibited; some are hard to calculate explicitly but easy to simulate

Electricity market design requirements for DC distribution systems

DC distribution systems (DCDS) connect local generators and loads directly. By avoiding unnecessary losses in AC-DC conversion, DCDS offers higher energy efficiency. Since different parties in a DCDS may have conflicting goals, matching between power supply and demand should be done with carefully designed allocation rules and monetary transfers, such that no one prefers to act otherwise than the outcome of the allocation. This paper reveals DCDS' unique operational requirements and indicates the challenges and opportunities they pose to market design. A design framework is introduced into DCDS electricity market, incl. tradable services, design goals, market participants, design options and performance criteria. We review the existing market models for AC and DC distribution systems and point out the direction for future work