Agent-based markets

Speaker Winslow Farrell Leigh Tesfatsion
Affiliation Emergent Solutions Group, PricewaterhouseCoopers Department of Economics, Iowa State University
Seminar title Consumer demand modeling using CAS The Trade Network Game: A Computational Laboratory for the Study of Agent-Based Markets
Links
Readings
  • How hits happen - Forecasting Predictability in a Chaotic Marketplace. What makes a hit a hit? How does a movie like Titanic captivate the public eye-and break box office records worldwide? What set Hootie and the Blowfish apart from countless other bands struggling to make it big-enabling them to sell more than 13 million copies of their debut album? What forces thrust Tickle Me Elmo to the top of every child's Christmas list last year, creating a feeding frenzy and waiting lists several months long? Just how do hits happen? Managers and marketing gurus alike have struggled to find the answers for years. Using outdated strategies and theories, they make foggy predictions based on past performance. Yet no matter how much research and marketing money you pour into a product, the biggest hits always seem to come out of the blue. But do they really? In How Hits Happen, Winslow Farrell offers a breakthrough approach to uncovering the hidden patterns behind hits. Applying complexity theory-the science that examines the interactions of various factors in complex systems-to modern business problems, How Hits Happen reveals how the actions of synthetic customers shed light on consumer behavior in the natural world. These computer-generated "consumers" embody quirks and contradictions, motivations and behaviors that uncannily resemble our own. They shop, go to movies, listen to music, and form cliques-in turn making or breaking the virtual products they're confronted with. Motivated by popularity, product placement, advertising, and simple preferences, their purchases are a powerful predictor of the next giant hit or the next huge flop. How Hits Happen turns the findings of this technology into a practical, accessible guide to consumer behavior for businesspeople everywhere, from marketing managers to management consultants, strategic planners to small-business owners. Fascinating, compelling, and truly revolutionary, it reveals invaluable lessons for managers in any real-life industry.
  • "Hysteresis in an Evolutionary Labor Market with Adaptive Search" (ps,307K), ISU Economic Report 50, October 1999. Real-world labor markets are characterized by highly heterogeneous earnings relative to observable heterogeneity in worker and employer attributes. This study uses an agent-based computational economics model of a labor market to undertake a systematic experimental study of how capacity asymmetries between workers and employers can induce persistent heterogeneity in average earnings and employment histories across workers with initially identical observable structural attributes, and similarly for employers. This persistent heterogeneity arises because workers and employers repeatedly engage in a costly adaptive search for worksite partners and evolve their worksite behaviors over time, which can result in path dependency (hysteresis) effects. Particular attention is focused on the experimental determination of correlations between capacity asymmetries and the formation of contractual networks among workers and employers, and between contractual network formation and the types of worksite interactions and earnings outcomes that these contractual networks support.
  • "A C++ Platform for the Evolution of Trade Networks" (ps,244K) (with D. McFadzean), Economic Report No. 39, Iowa State University, Revised: June 1999. To appear in Computational Economics.
    This study provides a detailed discussion of the C++ implementation of the Trade Network Game (TNG), a computational framework for studying the formation and evolution of trade networks in buyer-seller markets modelled as decentralized systems of autonomous interacting agents.
  • "A Trade Network Game with Endogenous Partner Selection" (ps,151K), Economic Report No. 36, Revised: June 1996. Final version appears as pp. 249--269 in H. M. Amman, B. Rustem, and A. B. Whinston (eds.), Computational Approaches to Economic Problems, Kluwer Academic Publishers, 1997.
    This study develops a Trade Network Game (TNG) framework for studying the interplay between evolutionary game dynamics and preferential partner selection in buyer-seller markets. The TNG consists of successive generations of resource-constrained traders who choose and refuse trade partners on the basis of continually updated expected payoffs, engage in risky trades modelled as two-person games, and evolve their trade strategies over time. Preliminary computer experiments are reported which suggest that the standard optimality properties used to judge the desirability of matching mechanisms in static market contexts may be inadequate measures of optimality from an evolutionary perspective.
  • "How Economists Can Get Alife" (ps,226K), Economic Report No. 37, Revised: March 1997. Final version appears as pp. 533--564 in W. Brian Arthur, Steven Durlauf, and David Lane (eds.), The Economy as an Evolving Complex System, II, Santa Fe Institute Studies in the Sciences of Complexity, Volume XXVII, Addison-Wesley, 1997.
    This study presents a summary overview of the basic artificial life (alife) paradigm, stressing aspects especially relevant for the study of decentralized market economies. In particular, recent work on a "Trade Network Game (TNG)" framework combining evolutionary game play with endogenous partner selection is used to illustrate how the alife paradigm might be specialized to economics. Analytical and simulation work is reported to show how the TNG is currently being used to study the evolutionary implications of alternative market structures at three different levels: individual trade behavior; trade network formation; and social welfare.