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Auctions have emerged as the primary means of assigning spectrum licenses to companies wishing to provide wireless communication services. Since July 1994, the Federal Communications Commission (FCC) has conducted 33 spectrum auctions, assigning thousands of licenses to hundreds of firms. Countries throughout the world are conducting similar auctions. I review the current state of spectrum auctions. Both the design and performance of these auctions are addressed.

Abstract: Agent-based computational economics (ACE) is the computational study of economies modeled as evolving systems of autonomous interacting agents. Thus, ACE is a specialization to economics of the basic complex adaptive systems paradigm. This study outlines the main objectives and defining characteristics of the ACE methodology, and discusses similarities and distinctions between ACE and artificial life research. Eight ACE research areas are identified, and a number of publications in each area are highlighted for concrete illustration. Open questions and directions for future ACE research are also considered. The study concludes with a discussion of the potential benefits associated with ACE modeling, as well some potential difficulties. Keywords: Agent-based computational economics; artificial life; learning; evolution of norms; markets; networks; parallel experiments with humans and computational agents; computational laboratories. 1

Economists have long been ambivalent about whether the discipline should focus on the analysis of markets or should be concerned with social interactions more generally. Recently the discipline has sought to broaden its scope while maintaining the rigor of modern economic analysis. Major theoretical developments in game theory, the economics of the family, and endogenous growth theory have taken place. Economists have also performed new empirical research on social interactions, but the empirical literature does not show progress comparable to that achieved in economic theory. This paper examines why and discusses how economists might make sustained contributions to the empirical analysis of social interactions.

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This report describes simple mechanisms that allow autonomous software agents to engage in bargaining behaviors in market-based environments. Groups of agents with such mechanisms could be used in applications including market-based control, internet commerce, and economic modelling. After an introductory discussion of the rationale for this work, and a brief overview of key concepts from economics, work in market-based control is reviewed to highlight the need for bargaining agents. Following this, the early experimental economics work of Smith (1962) and the recent results of Gode and Sunder (1993) are described.

William Vickrey's predicted equivalences between first-price sealed-bid and Dutch auctions, and between second-price sealed-bid and English auctions, are tested using field experiments that auctioned off collectible trading cards over the Internet. The results indicate that the Dutch auction produces 30 percent higher revenues than the first-price auction format, a violation of the theoretical prediction and a reversal of previous laboratory results, and that the English and second -price formats produce roughly equivalent revenues. (JEL C93, D44) Forthcoming, American Economic Review Department of Economics, 415 Calhoun Hall, Vanderbilt University., Nashville, TN 37235 (Email: reiley@vanderbilt.edu) Although I financed the actual experiments myself while a graduate student, I very gratefully acknowledge the financial support of the National Science Foundation, grant SBR-9811273, for subsequent work on this paper. I wish to thank Marius Hauser and Mary Lucking-Reiley for their research assistance, and Skaff Elias for product information about Magic: the Gathering. I am grateful to an anonymous referee, Orley Ashenfelter, Ann Bell, Jim Cox, Rachel Croson, Ron Harstad, Elton Hinshaw, John List, Preston McAfee, Jennifer Reinganum, Bill Sethares, Vernon Smith, David Wildasin, participants at the Economic Science Association annual meetings, and especially Glenn Ellison, for their advice and constructive criticism.

This paper describes a new multi-player computer game, Colored Trails (CT), which may be played by people, computers and heterogeneous groups. CT was designed to enable investigation of properties of decision-making strategies in multi-agent situations of varying complexity. The paper presents the results of an initial series of experiments of CT games in which agents ’ choices affected not only their own outcomes but also the outcomes of other agents. It compares the behavior of people with that of computer agents deploying a variety of decision-making strategies. The results align with behavioral economics studies in showing that people cooperate when they play and that factors of social dependency influence their levels of cooperation. Preliminary results indicate that people design agents to play strategies closer to game-theory predictions, yielding lower utility. Additional experiments show that such agents perform worse than agents designed to make choices that resemble human cooperative behavior. The paper describes challenges raised by these results for designers of agents, especially agents that need to operate in heterogeneous groups that include people. 1.

Dissatisfaction with previous assignment mechanisms and the desire to raise revenue induced Congress to grant the FCC authority to auction radio licenses. The debate over an appropriate auction design produced a variety of innovative proposals. One point that could not be unambiguously resolved [in the PCS debate] was whether the auction rules should permit combinatorial bids (i.e., bids on packages of licenses). In the end, the FCC chose not to do so because of perceived complexities with permitting such bids and concerns over the performance properties of a combinatorial auction. This paper presents an analysis of the proper role of combinatorial auctions as a mechanism for assigning spectrum licenses. In general, synergies across license valuations complicate the auction design process. Theory suggests that a simple (i.e., non-combinatorial) auction will have difficulty in assigning licenses efficiently in such an environment. This difficulty increases with increases in fitting complexity. In some environments, bidding may become mutually destructive. Experiments indicate that a combinatorial auction is superior to a simple auction in terms of economic efficiency and revenue generation in bidding environments with a low amount of fitting complexity. Concerns that a combinatorial auction will cause a threshold problem are not borne out when bidders for small packages can communicate.

This article argues that the agent-based computational model permits a distinctive approach to social science for which the term “generative ” is suitable. In defending this terminology, features distinguishing the approach from both “inductive ” and “deductive ” science are given. Then, the following specific contributions to social science are discussed: The agent-based computational model is a new tool for empirical research. It offers a natural environment for the study of connectionist phenomena in social science. Agent-based modeling provides a powerful way to address certain enduring—and especially interdisciplinary—questions. It allows one to subject certain core theories—such as neoclassical microeconomics—to important types of stress (e.g., the effect of evolving preferences). It permits one to study how rules of individual behavior give rise—or “map up”—to macroscopic regularities and organizations. In turn, one can employ laboratory behavioral research findings to select among competing agent-based (“bottom up”) models. The agent-based approach may well have the important effect of decoupling individual rationality from macroscopic equilibrium and of separating decision science from social science more generally. Agent-based modeling offers powerful new forms of hybrid theoretical-computational work; these are particularly relevant to the study of non-equilibrium systems. The agentbased approach invites the interpretation of society as a distributed computational device, and in turn the interpretation of social dynamics as a type of computation. This interpretation raises important foundational issues in social science—some related to intractability, and some to undecidability proper. Finally, since “emergence” figures prominently in this literature, I take up the connection between agent-based modeling and classical emergentism, criticizing the latter and arguing that the two are incompatible. � 1999 John Wiley &