Market Design: Auctions and Matching

Auctions, market design

Comments on the RGGI Market Design

Auctions, carbon auctions, greenhouse gas auctions

Market design

Europe is liberalising electricity in accordance with the European Commission’s Electricity Directives. Different countries have responded differently, notably in the extent of restructuring, treatment of mergers, market power, and vertical unbundling. While Britain and Norway have achieved effective competition, others like Germany, Spain and France are still struggling to deal with dominant and sometimes vertically integrated companies. The Netherlands offers an interesting intermediate case, where good economic analysis has sometimes been thwarted by legalistic interpretations. Investment under the new Emissions Trading system could further transform the electricity industry but may be hampered by slow progress in liberalising European gas markets

Dynamic Matching Market Design

We introduce a simple benchmark model of dynamic matching in networked markets, where agents arrive and depart stochastically and the network of acceptable transactions among agents forms a random graph. We analyze our model from three perspectives: waiting, optimization, and information. The main insight of our analysis is that waiting to thicken the market can be substantially more important than increasing the speed of transactions, and this is quite robust to the presence of waiting costs. From an optimization perspective, naive local algorithms, that choose the right time to match agents but do not exploit global network structure, can perform very close to optimal algorithms. From an information perspective, algorithms that employ even partial information on agents' departure times perform substantially better than those that lack such information. To elicit agents' departure times, we design an incentive-compatible continuous-time dynamic mechanism without transfers

The Convergence of Market Designs for Adequate Generating Capacity

This paper compares market designs intended to solve the resource adequacy (RA) problem, and finds that, in spite of rivalrous claims, the most advanced designs have nearly converged. The original dichotomy between approaches based on long-term energy contracts and those based on short-term capacity markets spawned two design tracks. Long-term contracts led to call-option obligations which provide market-power control and the ability to strengthen performance incentives, but this approach fails to replace the missing money at the root of the adequacy problem. Hogan’s energy-only market fills this gap. On the other track, the short-term capacity markets (ICAP) spawned long-term capacity market designs. In 2004, ISO New England proposed a short-term market with hedged performance incentives essentially based on high spot prices. In 2005 we developed for New England a forward capacity market with load obligated to purchase a target level of capacity covered by an energy call option. The two tracks have now converged on two conclusions: (1) High real-time energy prices should provide performance incentives. (2) High energy prices should be hedged with call options. We argue that two more conclusions are needed: (3) Capacity targets rather than high and volatile spot prices should guide investment, and (4) long-term physically based options should be purchased in a forward market for capacity. The result will be that adequacy is maintained, performance incentives are restored, market power and risks are reduced from present levels, and prices are hedged down to a level below the present price cap.Auctions, electricity auctions, uniform-price auctions

Downtown Providence Farmers Market Design

This market essentially combines a marketplace with an existing or new industrial building. The hybrid created results in space that has daily retail sales and hours, as well as other goods available at other times. The industrial aspect typically acts as the anchor, as the market’s activities help attract a different group of consumers at other business times. An example of this would be a seafood supply warehouse that also provides dining and entertainment as a nightlife destination

An Agent Based Market Design Methodology for Combinatorial Auctions

Auction mechanisms have attracted a great deal of interest and have been used in diverse e-marketplaces. In particular, combinatorial auctions have the potential to play an important role in electronic transactions. Therefore, diverse combinatorial auction market types have been proposed to satisfy market needs. These combinatorial auction types have diverse market characteristics, which require an effective market design approach. This study proposes a comprehensive and systematic market design methodology for combinatorial auctions based on three phases: market architecture design, auction rule design, and winner determination design. A market architecture design is for designing market architecture types by Backward Chain Reasoning. Auction rules design is to design transaction rules for auctions. The specific auction process type is identified by the Backward Chain Reasoning process. Winner determination design is about determining the decision model for selecting optimal bids and auctioneers. Optimization models are identified by Forward Chain Reasoning. Also, we propose an agent based combinatorial auction market design system using Backward and Forward Chain Reasoning. Then we illustrate a design process for the general n-bilateral combinatorial auction market. This study serves as a guideline for practical implementation of combinatorial auction markets design.Combinatorial Auction, Market Design Methodology, Market Architecture Design, Auction Rule Design, Winner Determination Design, Agent-Based System

Investment Incentives and Electricity Spot Market Design

In liberalized electricity markets strategic firms compete in an environment characterized by fluctuating demand and non-storability of electricity. While spot market design under those conditions by now is well understood, a rigorous analysis of investment incentives is still missing. Existing models, as the peak-load-pricing approach, analyze welfare optimal investment and find that optimal investment is higher with more competitive spot markets. In this article we want to extend the analysis to investment decisions of strategic firms that anticipate competition on many consecutive spot markets with fluctuating (and possibly uncertain) demand. We study how the degree of spot market competition affects investment incentives and welfare and provide an application of the model to electricity market data. Our results show that more competitive spot market prices strictly decrease investment incentives of strategic firms. The reduction of investment incentives can be so intense to even offset the beneficial impact of more competitive spot market design. Those results obtain with and without free entry. Our analysis thus demonstrates that investment incentives necessarily have to be taken into account for a meaningful assessment of proper electricity spot market design

The Complexity Dilemma in Policy Market Design

Regulators are increasingly pursuing their policy objectives by creating markets. To create a policy market, regulators require firms to procure a product that is socially useful but that confers little direct private benefit to the acquiring party. Examples of policy markets include pollutant emissions trading programs, renewable energy credit markets, and electricity capacity markets. Existing scholarship has tended to analyze policy markets simply as market-based regulation. Although not inaccurate, such inquiries are necessarily incomplete because they do not focus on the distinctive traits of policy markets. Policy markets are neither typical regulations nor typical markets. Concentrating on policy markets as a distinctive type of market brings to light common characteristics of such markets, which in turn generates insights into how they can be used more effectively to implement policy. In particular, this Article focuses on a recurring fundamental challenge in policy market design: managing complexity. Typical markets manage complexity through market forces. As a regulatory creation, however, policy markets require regulators to manage their complexity. This poses what we call the complexity dilemma, which requires regulators to balance strong pressures both toward and away from complexity. The central argument of this Article is that although policy markets are an important part of a regulator’s toolkit, they are also subject to complexity that limits their usefulness. Understanding the complexity dilemma and its crucial role in policy market design forms an essential step toward progress in improving the design and function of these markets