Agent-Based Computational Economics (ACE)
Research Area: Political Economy

Last Updated: 9 January 2009

Site Maintained By: Leigh Tesfatsion Department of Economics Iowa State University Ames, Iowa 50011-1070 http://www.econ.iastate.edu/tesfatsi/ tesfatsi AT iastate.edu Online ACE Course (Self-Study eBook) ACE Website

Table of Contents: Basic Issues Readings Software, Toolkits, and Demos Resource Sites, Groups, and Individual Researchers

Basic Issues

• Spatial election models;
• Tiebout models (local public goods);
• Voting on multi-dimensional platforms;
• Platform convergence;
• Evolution of voter preferences and party affiliations;
• Fashions, fads, and herd behavior;
• Evolution of political parties;
• Multi-party governments;
• Evolution of political institutions;
• International relations.

Readings

• Robert Axelrod, The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton University Press, Princeton, NJ, 1997.

• A. V. Banerjee, "A Simple Model of Herd Behavior", Quarterly Journal of Economics 107 (1992), 797-817.

• S. Bikhchandani, D. Hirshleifer, and I. Welch, "A Theory of Fads, Custom, and Cultural Change as Information Cascades", Journal of Political Economy 100 (1992), 992-1026.

• Lars-Erik Cederman, Emergent Actors in World Politics: How States and Nations Develop and Dissolve, Princeton University Press, Princeton, NJ, 1997.
  Abstract: The author defines "state" and "nation" in Weberian terms. A state is a territorial organization exercising legimitimate control over its own territory, undisturbed by internal power competition or external intervention. A nation is a "community of sentiment which would adequately manifest itself in a state of its own" and hence "tends to produce a state of its own." Building on concepts from complex adaptive systems modeling, the author presents a series of models that separate the state from the nation and incorporates these as emergent rather than preconceived actors. A review by David Lazer (Kennedy School of Government, Harvard) is available.

  Lars-Erik Cederman, "Modeling the Size of Wars", American Political Science Review, Vol. 97, 2003, pp. 135-150 (pdf preprint) Published article available (in 2007) at JSTOR.

  Abstract: Power-law distributions, scaling laws, and self-organized criticality are features of many frequency distributions, from word usage to avalanches, and from firms to cities. A set of events is said to behave in accordance with a power law distribution if large events are rarer than small events, and specifically if the frequency of an event is inversely proportional to its size. An example is the distribution of the sizes of wars. Cederman uses an agent-based model of war and state formation in the context of technological change to account for this observed regularity. His paper is a good example of how a fairly complicated model and its implications can be clearly presented, with details left to an appendix.

  J. Enelow and M. Hinich (eds.), Advances in the Spatial Theory of Voting, Cambridge University Press, New York, 1990.

  Kenneth L. Judd and Scott E. Page, "Computational Public Economics", pages 195-202 in Journal of Public Economic Theory, Special Issue on Computational Models in Public Economic Theory, Volume 6, Number 2, May 2004.

  Kenneth Kollman and Scott E. Page, "Computational Methods and Models of Politics", in Leigh Tesfatsion and Kenneth L. Judd (editors), Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics, Handbooks in Economics Series, North-Holland/Elsevier, Amsterdam, Spring 2006.

  Abstract: In this chapter, we assess recent contributions of computational models to the study of politics. We focus primarily on agent-based models developed by economists and political scientists. These models address collective action problems, questions related to institutional design and performance, issues in international relations, and electoral competition. In our view, complex systems and computational techniques will have a large and growing impact on research on politics in the near future. This optimism follows from the observation that the concepts used in computational methodology in general and agent-based models in particular resonate deeply within political science because of the domains of study in the discipline and because early findings from agent-based models align with widely known empirical regularities in the political world. In the process of making our arguments, we survey a portion of the growing literature within political science.

  Kenneth Kollman, John H. Miller, and Scott E. Page, "Computational Political Economy", pp. 461-490 in W. Brian Arthur, Steven Durlauf, and David Lane (eds.), The Economy as an Evolving Complex Economy II, SFI Studies in the Sciences of Complexity, Volume XXVII, Addison-Wesley, Reading, MA, 1997.

  Kenneth Kollman, John H. Miller, and Scott E. Page, "Political Institutions and Sorting in a Tiebout Model", American Economic Review, Volume 87, 1997, 977-992. Published article available at JSTOR.

  Abstract: The authors develop an agent-based model to explore how social outcomes are affected by the political institutions used to aggregate individual choices on local public goods issues, such as whether or not to finance a community swimming pool. Examples of such political institutions are referenda, two-party competition, and proportional representation. For each tested political institution, assumed to be commonly in use across all jurisdictions, citizens "vote with their feet" in each time period regarding which jurisdiction they wish to inhabit. The policy positions resulting in any given jurisdiction depend on the preferences of the citizens located within that jurisdiction, in a manner determined by the political institution in force. Citizens can continue to relocate in response to changing local policy positions, and local policy positions can continue to change in response to citizen relocations. The authors find that social efficiency is highest under political institutions such as two-party competition or proportional representation that initially induce citizens to undertake a suitable degree of experimentation among alternative jurisdictions.

  R. H. Sander, D. Schreiber, and J. Doherty, "Empirically Testing a Computational Model: The Example of Housing Segregation" (pdf,53K), UCLA working paper, 2000.

  Abstract: Using the Swarm simulation environment, this paper constructs a computational model of racial housing segregation that extends the Schelling Segregation Model. Preference functions are derived from empirical data on neighborhood racial composition and from a variety of other factors conjectured to be important in housing decisions. The model is used to examine the contemporary debate about the nature and causes of housing segregation.

  Thomas Schelling, Micromotives and Macrobehavior, W. W. Norton, New York, 1978.

  Paul M. Torrens, "New Tools for Simulated Housing Choices" (pdf,943K), presented at the Special Fannie Mae Foundation Session: Housing and the New Economy, Washington, D.C., May 2001.

  Abstract: This paper presents a framework for urban geographic simulation that infuses approaches derived from geocomputation and complexity (e.g, Schelling-type cellular automata multi-agent models) with standard techniques that have been tried and tested in operational land-use and transport simulation.

Software, Toolkits, and Demos

• Annotated list of pointers to ACE/CAS General Software and Toolkits

• Annotated list of pointers to ACE/CAS Computational Laboratories and Demonstration Software for ACE in particular and complex adaptive systems in general. Included are several spatial demos (e.g., the Schelling Segregation Model and demos for cellular automata) of possible use for voting and Tiebout (local public goods) modeling.

Resource Sites, Groups, and Individual Researchers

• ACE/CAS Research Sites and Groups

• Individual Researchers using ACE/CAS Tools

• A website on Agent-Based Models of Conflict and Collaboration is maintained by Robert Axelrod of the University of Michigan.

• The Association for Evolutionary Economics (AFEE) is an international organization of economists and other social scientists devoted to the analysis of economies as evolving, socially constructed, and politically governed systems. The intellectual heritage of AFEE is that of the original institutional economics created and developed by early twentieth-century economists such as Thorstein Veblen, John R. Commons, and Wesley Mitchell. The AFEE sponsors the Journal of Economic Issues, published quarterly, whose primary mission is to present articles that use and develop the core ideas of institutional economics in discussions of current economic problems and policy alternatives.

• The European Association for Evolutionary Political Economy, founded in London in 1988, promotes evolutionary, dynamic, and realistic approaches to economic theory and policy.

• Robert Axelrod (School of Public Policy Studies, University of Michigan, Ann Arbor): Complexity of cooperation; Evolution of cooperation.

• Lars-Erik Cederman (Swiss Federal Institute of Technology (ETH), Zurich): Agent-based computational modeling; International relations theory; Nationalism, integration, and disintegration processes; Historical sociology; RePast (Java-based toolkit for agent-based simulation).

• Joshua M. Epstein (Economic Studies and Governance Studies, Brookings Institution, Washington, D.C.): Sugarscape; Growing societies from the bottom up; Modelling of complex social systems, with application to international security, environmental, and policy areas.

• Joe Harrington (Department of Economics, Johns Hopkins University, Baltimore): Industrial organization; Political economy; Evolutionary economics; Game theory.

• Ken Kollman (Department of Political Science, University of Michigan, Ann Arbor): Computational political economy; Political parties and electoral landscapes; Interest groups, ideological bias, and Congressional committees; Development of national political parties; Effects of multi-layered electoral competition in federal political systems.

• John H. Miller (Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania): Computational economic modelling; Complex adaptive behavior in social and political systems; Artificial adaptive agent models.

• Scott Page (Department of Political Science and Center for Complex Systems, University of Michigan, Ann Arbor, U.S.A.): Problem solving by heterogeneous agents; On the emergence of cities; Diversity and optimality; Political institutions and sorting in a Tiebout model.

• Margaret M. Polski (Institute for Development Strategies, Indiana University, Bloomington, and A. T. Kearney, New York): Agent-based modelling; Economic development and institutional change; Innovation and growth in the new economy; Institutional evolution and change in U.S. commercial banking; Legislative games.

• Darren Schreiber (Political Science, UCLA, Los Angeles): Agent-based computational modelling of the formation of political parties, housing segregation, and political cognition; Swarm modelling.

Copyright © 2009 Leigh Tesfatsion. All Rights Reserved.