Handbook of Computational Economics
Volume 2, 2006, Pages 831-880
Chapter 16 Agent-Based Computational Economics: A Constructive Approach to Economic Theory⁎
Abstract
Economies are complicated systems encompassing micro behaviors, interaction patterns, and global regularities. Whether partial or general in scope, studies of economic systems must consider how to handle difficult real-world aspects such as asymmetric information, imperfect competition, strategic interaction, collective learning, and the possibility of multiple equilibria. Recent advances in analytical and computational tools are permitting new approaches to the quantitative study of these aspects. One such approach is Agent-based Computational Economics (ACE), the computational study of economic processes modeled as dynamic systems of interacting agents. This chapter explores the potential advantages and disadvantages of ACE for the study of economic systems. General points are concretely illustrated using an ACE model of a two-sector decentralized market economy. Six issues are highlighted: Constructive understanding of production, pricing, and trade processes; the essential primacy of survival; strategic rivalry and market power; behavioral uncertainty and learning; the role of conventions and organizations; and the complex interactions among structural attributes, institutional arrangements, and behavioral dispositions.
Introduction
Economies are complex dynamic systems. Large numbers of micro agents engage repeatedly in local interactions, giving rise to global regularities such as employment and growth rates, income distributions, market institutions, and social conventions. These global regularities in turn feed back into the determination of local interactions. The result is an intricate system of interdependent feedback loops connecting micro behaviors, interaction patterns, and global regularities.
Economists have grappled with the modeling of economic systems for hundreds of years. Nevertheless, the Walrasian equilibrium model devised by the nineteenth-century French economist Leon Walras (1834–1910) still remains the fundamental paradigm that frames the way many economists think about this issue. Competitive models directly adopt the paradigm. Imperfectly competitive models typically adopt the paradigm as a benchmark of coordination success. Although often critiqued for its excessive abstraction and lack of empirical salience, the paradigm has persisted.
As detailed by Katzner (1989) and Takayama (1985), Walrasian equilibrium in modern-day form is a precisely formulated set of conditions under which feasible allocations of goods and services can be price-supported in an economic system organized on the basis of decentralized markets with private ownership of productive resources. These conditions postulate the existence of a finite number of price-taking profit-maximizing firms who produce goods and services of known type and quality, a finite number of consumers with exogenously determined preferences who maximize their utility of consumption taking prices and dividend payments as given, and a Walrasian Auctioneer (or equivalent clearinghouse construct) that determines prices to ensure each market clears.1 Assuming consumer nonsatiation, the First Welfare Theorem guarantees that every Walrasian equilibrium allocation is Pareto efficient.
The most salient structural characteristic of Walrasian equilibrium is its strong dependence on the Walrasian Auctioneer pricing mechanism, a coordination device that eliminates the possibility of strategic behavior. All agent interactions are passively mediated through payment systems; face-to-face personal interactions are not permitted. Prices and dividend payments constitute the only links among consumers and firms prior to actual trades. Since consumers take prices and dividend payments as given aspects of their decision problems, outside of their control, their decision problems reduce to simple optimization problems with no perceived dependence on the actions of other agents. A similar observation holds for the decision problems faced by the price-taking firms. The equilibrium values for the linking price and dividend variables are determined by market clearing conditions imposed through the Walrasian Auctioneer pricing mechanism; they are not determined by the actions of consumers, firms, or any other agency supposed to actually reside within the economy.
Walrasian equilibrium is an elegant affirmative answer to a logically posed issue: can efficient allocations be supported through decentralized market prices? It does not address, and was not meant to address, how production, pricing, and trade actually take place in real-world economies through various forms of procurement processes.
What, specifically, is standardly meant by "procurement processes" in the business world? As discussed at length by Mackie-Mason and Wellman (2006), customers and suppliers must identify what goods and services they wish to buy and sell, in what volume, and at what prices. Potential trade partners must be identified, offers to buy and sell must be prepared and transmitted, and received offers must be compared and evaluated. Specific trade partners must be selected, possibly with further negotiation to determine contract provisions, and transactions and payment processing must be carried out. Finally, customer and supplier relationships involving longer-term commitments must be managed.
Theories always simplify, and substituting equilibrium assumptions for procurement processes is one way to achieve an immensely simplified representation of an economic system. For economic systems known to have a globally stable equilibrium, this simplification might be considered reasonable since procurement processes do not affect the system's long-run behavior. Even in this case, however, the path of adjustment could be of considerable practical concern as a determinant of the speed of convergence. For economic systems without a globally stable equilibrium, procurement processes determine how the dynamics of the system play out over time from any initial starting point.
As carefully detailed by Fisher (1983) and Takayama (1985, Chapters 2–3), economists have not been able to find empirically compelling sufficient conditions guaranteeing existence of Walrasian equilibria, let alone uniqueness, stability, and rapid speed of convergence, even for relatively simple modelings of market economies. For extensions of the Walrasian framework to dynamic open-ended economies, such as overlapping generations economies, multiple equilibria commonly occur and the Pareto efficiency of these equilibria is no longer guaranteed.2 The explicit consideration of procurement processes would therefore appear to be critically important for understanding how numerous market economies have managed in practice to exhibit reasonably coordinated behavior over time. As eloquently expressed by Fisher (1983, p. 16):
"The theory of value is not satisfactory without a description of the adjustment processes that are applicable to the economy and of the way in which individual agents adjust to disequilibrium. In this sense, stability analysis is of far more than merely technical interest. It is the first step in the reformulation of the theory of value."
A natural way to proceed is to examine what happens in a standard Walrasian model if the Walrasian Auctioneer pricing mechanism is removed and if prices and quantities are instead required to be set entirely through the procurement actions of the firms and consumers themselves. Not surprisingly, this "small" perturbation of the Walrasian model turns out to be anything but small. Even a minimalist attempt to complete the resulting model leads to analytical difficulty or even intractability. As elaborated by numerous commentators, the modeler must now come to grips with challenging issues such as asymmetric information, strategic interaction, expectation formation on the basis of limited information, mutual learning, social norms, transaction costs, externalities, market power, predation, collusion, and the possibility of coordination failure (convergence to a Pareto-dominated equilibrium).3 The prevalence of market protocols, rationing rules, antitrust legislation, and other types of institutions in real-world economies is now better understood as a potentially critical aspect of procurement, the scaffolding needed to ensure orderly economic process.
Over time, increasingly sophisticated tools are permitting economic modelers to incorporate procurement processes in increasingly compelling ways. Some of these tools involve advances in logical deduction and some involve advances in computational power.4
This chapter provides an introductory discussion of a potentially fruitful computational development, Agent-based Computational Economics (ACE). Exploiting the growing capabilities of computers, ACE is the computational study of economic processes modeled as dynamic systems of interacting agents.5 Here "agent" refers broadly to bundled data and behavioral methods representing an entity constituting part of a computationally constructed world. Examples of possible agents include individuals (e.g., consumers, workers), social groupings (e.g., families, firms, government agencies), institutions (e.g., markets, regulatory systems), biological entities (e.g., crops, livestock, forests), and physical entities (e.g., infrastructure, weather, and geographical regions). Thus, agents can range from active data-gathering decision-makers with sophisticated learning capabilities to passive world features with no cognitive functioning. Moreover, agents can be composed of other agents, thus permitting hierarchical constructions. For example, a firm might be composed of workers and managers.6
Section 2 explains more fully the basic ACE methodology and discusses the potential advantages and disadvantages of ACE for the study of economic systems. An illustrative ACE model of a relatively simple two-sector decentralized market economy, referred to as the "ACE Trading World," is outlined in Section 3. This model is used in Section 4 to discuss in concrete terms several important but difficult issues associated with procurement processes in real-world economies that ACE is able to address. Concluding remarks are given in Section 5. A detailed discussion of the ACE Trading World is presented in an Appendix A.
Section snippets
ACE study of economic systems
A system is typically defined to be complex if it exhibits the following two properties [see, e.g., Flake (1998)]:
- •The system is composed of interacting units;
- •The system exhibits emergent properties, that is, properties arising from the interactions of the units that are not properties of the individual units themselves.
From Walrasian equilibrium to ACE trading
For concrete illustration, this section first presents in summary form a Walrasian equilibrium modeling of a simple two-sector economy with price-taking firms and consumers. The Walrasian Auctioneer pricing mechanism is then removed, resulting in a dynamically incomplete economy. Specifically, the resulting economy has no processes for determining how production and price levels are set, how buyers are to be matched with sellers, and how goods are to be distributed from sellers to buyers in
ACE modeling of procurement processes
In real-world economies, rival firms must actively compete for customers in order to survive and prosper. This section focuses on six important issues entailed by this procurement process that ACE frameworks are able to address: namely, constructive understanding; the essential primacy of survival; strategic rivalry and market power; behavioral uncertainty and learning; the role of conventions and organizations; and the complex interactions among structural attributes, institutional
Concluding remarks
The defining characteristic of ACE models is their constructive grounding in the interactions of agents, broadly defined to include economic, social, biological, and physical entities. The state of a modeled system at each point in time is given by the internal data and methods of the agents that currently constitute the system. Starting from an initially specified system state, the motion of the state through time is determined by endogenously generated agent interactions.
This agent-based
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- ⁎
- Earlier versions of this study have been presented in the Computations in Science Distinguished Lecture Series (University of Chicago, October 2003), at the Post Walrasian Macroeconomics Conference (Middlebury College, May 2004), at the ACE Workshop (University of Michigan, May 2004), and in a Fall 2004 faculty seminar at ISU. For helpful conversations on the topics covered in this paper, thanks in particular to Bob Axelrod, Dave Batten, Facundo Bromberg, Myong-Hun Chang, Dave Colander, Chris Cook, Catherine Dibble, Josh Epstein, Charlie Gieseler, Joe Harrington, Kevin Hoover, Ken Judd, Deddy Koesrindartoto, Blake LeBaron, Abishek Somani, and Nick Vriend.
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