Recommended Materials:
-
Santa Fe Stock Market Demonstration Software
(sourceforge,46K)
-
SimStockExchange (Java)
(homepage)
- * Rob Axtell, "ACE Financial Market Modeling"
(pdf,82K),
presented at the VII Trento Summer School on ACE, July 2006. ON-LINE
- * David F. Batten, Chaper 7: "Coevolving Markets"
(pdf preprint-no figures,247K),
in Discovering Artificial Economics: How Agents Learn and Economies Evolve, Perseus Books, Westview Press, 2000. ON-LINE
- * Blake LeBaron, "Building the Santa Fe Artificial Stock Market"
(pdf,123K),
Working Paper, Brandeis University, June 2002. ON-LINE
- Abstract: This brief summary provides an insider's look at
the construction of the Santa Fe Artificial Stock Market (ASM) model. The
perspective considers the many design questions that went into building the
model from the perspective of a decade of experience with agent-based
financial markets. The model is assessed based on its overall strengths and
weaknesses.
- * Leigh Tesfatsion,
"Detailed Notes on the Santa Fe Artificial Stock Market Model"
(html). ON-LINE
-
Other source materials related to ACE financial modeling
VI. Interaction on Fixed Networks
- Key In-Class Discussion Topics:
- What might be inferred from the observation by Craig Reynolds that
"a flock is not a big bird"?
- Distinguishing between "simple" and "complex" economic systems
- Under what circumstances can robust point predictions of economic
outcomes be obtained from a knowledge of initial economic structure,
ignoring network effects? And when might network
effects be important for the prediction of economic outcomes?
- How can graph theory be used to quantitatively represent and analyze
economic interaction networks?
- What type of systematic phase transition do random graphs undergo as
their connectivity increases?
- Do socioeconomic networks exhibit any kind of systematic phase transition
as their connectivity increases?
- Why all the recent excitement about "small-world networks"
(locally dense networks with global reach)?
Required Readings:
-
** Leigh Tesfatsion, "Introductory Notes on the Structural and Dynamical Analysis of Networks"
(pdf,2.3MB). ON-LINE/CLASS PRESENTATION
- NOTE: These presentation slides summarize and graphically illustrate key points from the
"Introduction to Networks" notes linked below.
-
** Leigh Tesfatsion, "Introduction to Networks"
(html). ON-LINE
- Abstract: These notes provide rigorous definitions for basic structural characterizations of networks (e.g., degree, clustering, shortest path length). Also discussed are phase transitions in random graphs, the concept of a "small world network," and the possible application of small-world networks to the study of trade interactions. The Key references are Batten (Chapter 3, 2000) and Wilhite (2001), both linked below.
-
** Leigh Tesfatsion, "Notes on Wilhite (2001)"
(pdf,236K). ON-LINE/CLASS PRESENTATION
- NOTE: These presentation slides summarize key points from the article by Wilhite (2001), linked below.
- ** Allen Wilhite (2001), "Bilateral Trade and `Small-World' Networks"
(pdf,181K),
Computational Economics, Vol. 18, No. 1, August, pp. 49-64. The published article is also available at
SpringerLink. ON-LINE
- Abstract: Wilhite develops an agent-based
computational model of a bilateral exchange economy in which profit-seeking traders sequentially engage in trade partner search, negotiation, and trading. He uses this model to
explore the consequences of restricting trade to different types of networks,
including a "small-world network" with both local connectivity and global
reach. His key finding is that small-world networks provide most of the
market-efficiency advantages of completely connected networks while retaining
almost all of the transaction cost economies of locally connected networks.
- Recommended Materials:
-
* Wilhite Small-World Trade Network Demo (NetLogo), by Mark McBride
(homepage)
- * David F. Batten, Chapter 3: "Sheeps, Explorers, and Phase Transitions"
(pdf preprint-no figures,203K),
in Discovering Artificial Economics: How Agents Learn and Economies Evolve, Perseus Books, Westview Press, 2000. ON-LINE
- * Steven H. Strogatz, Exploring Complex Networks
(pdf,589K),
Nature, Vol. 410, 8 March 2001, pp. 268-276.
-
Visualcomplexity.com
maintains an intriguing site devoted to the visual exploration of real-world complex networks. ON-LINE
-
Other source materials related to ACE network research
VII. Formation of Interaction Networks
- Key In-Class Discussion Topics:
- In what economic situations are interactions determined randomly over time?
- In what economic situations are interactions determined preferentially over time by choice
and refusal of trade partners based on past experiences?
- What difference might it make if econonomic interactions are randomly versus preferentially determined?
- A labor market study illustrating preferential network formation among workers and employers with learning capabilities
- Representation and visualization of network formation: How should it be done?
- Required Readings:
- ** Leigh Tesfatsion, "Notes on Network Formation"
(pdf,246K). ON-LINE/CLASS PRESENTATION
- Recommended Materials:
-
* The Trade Network Game (TNG) Laboratory (C++/VB, open source), includes run-time visualization of trader network formation, by McFadzean, Stewart, and Tesfatsion
(homepage)
- * Albert-László Barabási, "Network Overview"
(pdf,70M),
2006 Keynote Address. (Caution: Large download)
- Professor Albert-László Barabási (Department of
Physics, Notre Dame, Indiana) directs a research group focusing on the
emergence and evolution of networks in various contexts (e.g., metabolic and
genetic networks, actor networks, collaborative networks). This fun slide
presentation provides a vivid visual summary of some of their key findings to date.
- * David F. Batten, Chapter 4:"The Ancient Art of Learning by Circulating"
(pdf preprint - no figures, 167K),
in Discovering Artificial Economics: How Agents Learn and
Economies Evolve, Westview Press, Boulder, Colorado, 2000, plus
Leigh Tesfatsion, "Notes on Batten Chapter 4, Plus Glossary of Terms"
(html). ON-LINE
-
Other source materials related to ACE labor research
-
General resource site on network formation
VIII. Empirical Validation of ACE Models
- Key In-Class Discussion Topics:
- Verification for ACE models: How to verify an ACE model is carrying out operations in the way the modeler intends?
- [G.E.P. Box (1979)]: "All models are wrong, but some are useful." Must the intended purpose of a model be known before meaningful empirical validation can proceed?
- Empirical validation for ACE models: input validation (operational validity), descriptive output validation, and predictive output validation
- What is iterative participatory modeling (companion modeling)?
- Required Readings:
- ** Leigh Tesfatsion, "Notes on the Empirical Validation of ACE Models"
(pdf,176K). ON-LINE/CLASS PRESENTATION
- Recommended Materials:
- *
Paul Windrum,
Giorgio Fagiolo, and
Alessio Moneta,
Empirical Validation of Agent-Based Models: Alternatives and Prospects
(html),
Journal of Arificial Societies and Social Simulation, Vol. 10, no. 2,8, March 31, 2007.
- Abstract: This paper addresses the problem of finding the appropriate method for conducting empirical validation in ACE models. The paper has two primary objectives: (1) to identify key issues facing ACE economists engaged in empirical validation; and (2) to critically appraise the extent to which alternative approaches deal with these issues.
-
Other source materials on the empirical validation of ACE models
Appendix: General Course Project Information
Students are strongly encouraged to begin consideration of possible course project
topics as soon as possible.
Please visit the
Course Project Information Site
for detailed information regarding course projects, including a list of
course projects selected by Econ 308 students in previous years.
I am available during office hours, by appointment, and anytime by email to
provide guidance if desired.
Preliminary outlines for student project proposals must be turned in to the instructor during the first week following Spring break and must receive go-ahead instructor approval by the end of March.
Final write-ups for student project reports are due the last day of
class.
Copyright © Leigh Tesfatsion. All Rights Reserved.
tesfatsi AT iastate.edu 
Course Overview