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This chapter discusses some things we have learned about markets, in the process of designing marketplaces to fix market failures. To work well, marketplaces have to provide thickness, i.e. they need to attract a large enough proportion of the potential participants in the market; they have to overcome the congestion that thickness can bring, by making it possible to consider enough alternative transactions to arrive at good ones; and they need to make it safe and sufficiently simple to participate in the market, as opposed to transacting outside of the market, or having to engage in costly and risky strategic behavior. The chapter draws on recent examples of market design ranging from labor markets for doctors and new economists, to kidney exchange, and school choice in New York City and Boston. The first part of this chapter was prepared to accompany the Hahn Lecture delivered at the Royal Economic Society meetings, on April 11, 2007, and was published as Roth (2008). The present chapter extends the 2008 paper with a Postscript to bring it up to date, and to include some details appropriate to this book.

This chapter attempts to explain under which circumstances political embeddedness (PE) leads to the emergence of sustainable markets. The question is of more than academic interest: after all, if PE does result in functioning markets, then we can expect it to become entrenched in the institutional architecture of the business system of China. The analytical tool ‘imported’ into the concept of PE is Market Design, the findings of which allow us to specify criteria for the development of functioning markets. Using these criteria, three cases are analysed. The first case is the well-known example of Township and Village Enterprises (TVEs), in which the political embeddedness of TVEs resulted in the emergence of a competitive sustainable market. The second case takes the public utility sector as an example in which PE resulted in ill-functioning markets because private investment could not be mobilized. The third case, which takes Enterprise Bankruptcy Law (EBL) as its example, deals with the question of whether attempting to embed firms within the law is actually a move away from PE, or whether PE and the law supplement each other. The example of the insolvency law (EBL) is also used to enquire whether a ‘marketplace’ for legal services such as court-mediated arbitration and litigation is emerging, and whether it can be expected to function within PE. The findings suggest that PE contributes to the development of functioning markets only in certain conditions: when the use of informal norms aligns the interests of all parties involved, and when decision-making rights are uncontested, and when there is equivalence between the spatial dimension of the market and the spatial dimension of political embeddedness.

Experience of the past twenty years suggests that potential benefits from electricity industry restructuring are small relative to those from introducing competition into other network industries. Also, the probability of costly market failure in the electricity supply industry, often due to the exercise of unilateral market power, seems higher than in other network industries. This chapter shows that electricity industry restructuring is an evolving process that requires market designers to choose between an imperfectly competitive market and an imperfect regulatory process to provide incentives for least-cost supply at all stages of the production process. A goal of that process is to limit suppliers’ ability to exercise unilateral market power in wholesale generation markets, explicitly through market price-setting mechanisms, or implicitly through the regulatory price-setting process. Regulators can limit suppliers’ ability to exercise unilateral market power by altering the market structure, changing market rules, imposing penalties and sanctions on market participants, and explicitly setting the prices that market participants receive for their production. This chapter provides a theoretical framework for understanding how to make these choices in designing a wholesale electricity generation market that provides consumers with greater benefits relative to those under the former vertically-integrated regulated monopoly regime.

This chapter examines design issues associated with markets for ideas. It considers how the nature of ideas themselves impacts upon the effectiveness of markets for ideas. It then looks at the impact of repugnance and how specific real-world institutions and norms (such as those associated with open science) can be understood as attempts to facilitate multilateral idea exchange while managing the repugnance associated with idea trading. The chapter highlights three main findings. First, the nature of ideas undermines the spontaneous and uncoordinated evolution of a corresponding market for ideas. Secondly, specific institutions, most notably formal intellectual property rights such as patents, play a crucial role in addressing the challenges raised by market design. Thirdly, the most robust markets for ideas are those where ideas are free.

Organisations and individuals trading in electronic markets are increasingly using automated agents. Agents are particularly useful in markets where trade might not otherwise have been possible, for example because a lot of information must be processed quickly, or because employing human traders in 24-hour, small transaction markets is not cost-effective. Markets for communication bandwidth, where organisations trade the rights to transmit data over a network, are one such application. Because demand fluctuates considerably every few seconds, agent-based spot markets provide extra liquidity. In order for such markets to work effectively, it is necessary to provide users with agents that can represent and maximise the goals of the organisations using them. This is a hard problem. This chapter provides general principles and examples of good algorithms, based on our research in this area and on our work on designing agents and markets for trading communication bandwidth — some of which on behalf of HP labs. The contribution of our approach is threefold: First, the chapter provides a definition for what a ‘good’ trading agent is. Second, the chapter discusses how to design an interface where users can easily and effectively communicate their preferences to the agents. Clearly, if users can not do that, then this will limit both their incentives to use such technologies and the benefits of what they can achieve when they so. Third, the chapter shows how to design adaptive agents based on ideas from statistical decision theory. In particular our agents are designed to differentiate stable from unstable market conditions and to best respond to these changes. The chapter describes simulation results which show that our design performs well in a large number of trading environments which tries to capture what real markets trading is like.

In recent years most financial exchanges introduced parallel trading mechanisms: Block or over the counter trading which is largely bilateral; and limit order books where at any given point in time the price is the same for all traders and is determined by supply and demand. This chapter presents three case studies which look at detailed data from various financial exchanges and tries to relate that to the various theoretical explanations that has been proposed to explain traders' short and long term choice of which mechanism to use. In particular we look for long term trend related to strategic choice as proposed by a number of theories including our own (Neeman and Vulkan 2010). While costs (direct and indirect, via bid ask spreads) provide the most direct explanation of short term choices, the chapter finds that strategic theories do fit most of the medium to long term data. Understanding the incentives of traders to choose between competing designs in clearly of great importance for market designers. It is hoped that the evidence presented here can contribute to future successful designs.

“Americanization” in marketing did not simply entail out-right imports, but rather a careful and selective adaptation of specific elements. Such transnational corporate learning processes negotiating differences between American and European consumption and marketing cultures, opened new career opportunities for the émigré consumer engineers. This chapter traces their “return” to Europe after the war as well as their impact on the transformation of Western European consumer marketing between the late 1940s and the early 1960s. The focus will be on West Germany, which had a special role in this transatlantic exchange. The returning émigrés did not simply act as cheerleaders of American consumer modernity, however. Through their cultural translations they were able to engage skeptical colleagues and consumers in Europe and, in some instances, to “Europeanize” modern marketing practice.

Friedman (1962) suggested that unfettered markets generally ensure efficient provision of goods and services. Applying this logic to education, he recommended that students be provided vouchers to purchase schooling in a free market. Hoxby (2002) agrees, and suggests that more choice increases school productivity. This chapter discusses the evidence in this area, concluding that competition has more mixed and modest impact than expected. This should not be surprising, since economic theory on incentives and incomplete contracts (beginning with contributions from the 1950s) leads to more nuanced expectations. An examination of the incentives faced by schools, parents, and students yields predictions that are broadly consistent with the evidence, and suggests little reason to expect that school choice will dramatically improve test scores. The chapter describes a simple model that illustrates this point and implies that elements of market design might be necessary to ensure that competition enhances educational performance.

This chapter analyzes the possible causes of the electricity crisis in California in 2000. It argues against the belief that the crisis was caused by a combination of rising input costs, poor market design, and the exercise of market power and failed market oversight by state and federal regulators, and suggests that the crisis fundamentally a regulatory crisis rather than an economic crisis. This chapter suggests that the most important lesson from the California crisis relates to how the Federal Energy Regulatory Commission (FERC) carries out its statutory mandate to set just and reasonable wholesale prices in a market regime.

It has long been recognized that individuals' preferences adapt to the social, economic and legal environment in which they take part, in addition to reacting to incentives and constraints given these preferences. Therefore, the design of such incentives via legislation or regulation should better take into account also its own effect on preferences, in order to avoid endogenous preference adaptation curtailing the designer's aims. Furthermore, the endogeneity of preferences poses a dilemma to the social planner whether to maximize welfare having in mind the original preferences of individuals, or rather the preferences that emerge endogenously with the intervention mechanism. This chapter outlines a general formulation of the design problem with endogenous preferences, and demonstrates its use with a prominent example — the design of incentives for bilateral trade under asymmetric information. The chapter shows how different timings of the intervention ex post, interim or ex ante have different effects on the endogenous preferences that emerge, and on the extent of divergence between the original and the adapted preferences.

Sourcing is the process by which companies acquire goods and services for their operations. Drawing from personal experiences of designing and fielding over 800 sourcing auctions worth over $60 billion, this chapter examines issues that arise in very-large-scale generalized combinatorial auctions. It discusses how combinatorial and multi-attribute auctions can be hybridized. It addresses preference and constraint expression languages for the bidders and the bid taker, as well as techniques for effectively using them. It presents scalable optimization techniques for the market clearing (a.k.a. winner determination) problem. It also considers other issues that this study uncovered as well as the significant efficiency gains and other benefits that followed.

This chapter reports the results of an experimental test of alternative auction designs suitable for pricing and removing troubled assets from banks' balance sheets as part of the financial rescue planned by the U.S. Department of Treasury in the fall of 2008. All auction mechanisms tested here are structured so that many individual securities or pools of securities are auctioned simultaneously. Securities that are widely held are purchased in auctions for individual securities; securities with concentrated ownership are purchased as pools of related securities. Each experimental subject represents a bank which has private information about its liquidity need and the true common value of each security. The chapter studies bidding behavior and performance of sealed-bid uniform-price auctions and dynamic clock auctions. The clock and sealed-bid auctions resulted in similar prices. However, the clock auctions resulted in substantially higher bank payoffs, since the dynamic auction enabled the banks to better manage their liquidity needs. The clock auctions also reduced bidder error. The experiments demonstrated the feasibility of quickly implementing simple and effective auction designs to help resolve the crisis.

In complex environments, it can be difficult to understand the underlying characteristics of transactions, and it is challenging to learn enough about them so as to design the best institutions to efficiently generate gains from trade. In recent years, artificial intelligence has emerged as an important tool that allows market designers to uncover important market fundamentals, and to better predict fluctuations that can cause friction in markets. Examples include retailers and marketplaces who mine vast amounts of data to identify patterns that help them increase the efficiency of their markets, and auction designers who train learning models to simplify auctions with complex sets of constraints. With better prediction tools, companies can better anticipate consumer demand and producer supply as well as identify risks to the integrity of transactions. This chapter offers some recent developments of how artificial intelligence helps market designers improve the operations of markets, and outlines directions in which it will continue to shape and influence market design.

This chapter describes how markets that use a combination of automated and human agents can work. It presents a system AutONA (Automated One-to-one Negotiation Agent), for conducting multiple simultaneous negotiations over price and quantity. The use of competition between sellers to guide negotiation tactics is key. This system was implemented and human trials were conducted to evaluate it based on its ability to negotiate ‘reasonably’, and on its performance with respect to a trading game that was designed independently of the system itself. AutONA passed a limited version of the Turing test: The experiments did not reveal any obvious exploitation that a human trader can use against AutONA.

Cooperation within larger groups is often endangered by incentives to free ride. One goal of market and institutional design is to create environments in which socially efficient cooperation can be achieved. The main point in this chapter is that only considering first-order incentives to cooperate within a larger group may not be sufficient, as subcoalitions display reciprocal behavior despite the incentives to renege. Three related complications are discussed: (a) exploitative behavior is often coordinated in subgroup coalitions, (b) natural within-group resistance to exploitation already exists, and (c) the actions of group members can often only be imperfectly monitored. Given these realities, implications of current research for applied market and institutional design are outlined.

Microcredit, the practice of making small uncollateralized loans to the poor, is a potential solution to credit market imperfections. This chapter examines the design of uncollateralized lending programs in light of recent field evidence. It shows that efficient design of microcredit is impossible without an understanding of informal side-contracting. If side-contracting is perfect, the design problem is not very interesting. If side-contracting is impossible, the theoretical welfare comparison between joint and individual liability is ambiguous. Joint liability encourages the borrowers to help each other in hard times, which mitigates insurance market imperfections and enhances efficiency, but a large (perhaps infeasible) cost of default is required for this help to be incentive compatible.

Over the last three decades, rapid progress in market design had brought the subject to an engineering-like state, where a large number of well understood mechanisms can be prescribed for a given situation. Electronic markets — whether direct negotiations, auction or exchanges — are a particularly good place to apply this theory, because the interactions between participants are regulated by the communication protocol. Since there are already rules in place, it seems wise to ensure that they are the right rules the ones that will lead to efficient outcomes. In another chapter in this book (Vulkan and Preist) we looked at market design issues for markets where all participants are automated agents. Elsewhere in this book there are plenty of examples for market design for human agents, be it individuals or firms. In this chapter we look at the hybrid case where some of the organisations involved are using a software agent to directly aid them in their negotiations with other organisations where agents are not used. The context for this is procurement negotiations: Very large firms can force their suppliers to participate in an auction, but small and middle size firms cannot. To these firms, the technology described in this chapter can be used to ensure almost the same efficiency of outcome without changing the way they negotiate. The system uses multiple one-to-one negotiations to try and mimic the process and hopefully outcome of an auction (in this case a reverse, price lowering auction). The AutONA (Automated One-to-one Negotiation Agent) system was conceived as a means of reducing these operational procurement costs enabling procurement departments to automate as much price negotiation as possible thus creating the option of reducing direct costs and/or redeployment of operational effort into strategic procurement requiring high human involvement. The chapter presents based on Byde et al [1] the design of the core reasoning system and preliminary results obtained from a number of experiments conducted in HPs Experimental Economics Lab. The main conclusion is that AutONA could reasonably be deployed for automated negotiation having shown no evidence for being identified as an automated system by suppliers.

Curiously, early neoclassical economics was a theory of agents, not markets as such. But changes in markets in the late twentieth century began to highlight this lacuna. How information was incorporated into the theory began to suggest that economists could not just describe The Market, but could also design boutique markets for clients. We trace the resulting narrative trajectory of this epoch-making departure using an abstract Information Space graphic showing combinations of types of agent epistemology, with different types of models of information.

The chapter describes a new approach for selling rough diamonds through competitive auctions. The classical approach of De Beers — giving each customer a bag of stones and a take-it-or-leave-it price — worked well in near monopoly circumstances, but is ill-suited for competitive producers. Competitive producers, like BHP Billiton, benefit from getting the diamonds to those who value them the most. Beginning in 2008, BHP Billiton introduced a simple auction process to assign its Ekati diamonds to the highest bidders at competitive market prices. A Spot auction, ten times per year, is used to establish prices for each of nineteen deals of diamonds grouped by size, color, and quality. A Term auction allows customers to lock in a long-term supply commitment at prices indexed to future Spot auctions. A Specials auction, two or three times per year, prices large stones. The auctions use an ascending-clock format in which prices increase for each product until there is no excess demand. This approach allows customers to discover market prices, while managing portfolio and budget constraints. The approach has proven remarkably successful in pricing and allocating the mine's output even in the face of the global financial crisis.