nep-evo New Economics Papers
on Evolutionary Economics
Issue of 2005‒11‒19
six papers chosen by
Matthew Baker
US Naval Academy, USA

  1. Rage Against the Machines: By Dürsch, Peter; Kolb, Albert; Oechssler, Jörg; Schipper, Burkhard
  2. The Economics of Fairness, Reciprocity and Altruism ? Experimental Evidence and New Theories By Fehr, Ernst; Schmidt, Klaus M.
  3. Evolution with Individual and Social Learning in an Agent-Based Stock Market By Ryuichi YAMAMOTO
  4. Revealed Altruism By Jim C. Cox; Daniel Friedman; Vjollca Sadiraj
  5. Social norms and social choice By Anabela Botelho; Glenn W. Harrison; Lígia Pinto; Elisabet E. Rutstrom
  6. The Emergence of Local Norms in Networks By Mary Burke; Gary Fournier

  1. By: Dürsch, Peter (Department of Economics, University of Heidelberg); Kolb, Albert (Department of Economics, University of Bonn); Oechssler, Jörg (Department of Economics, University of Heidelberg); Schipper, Burkhard (University of California, Davis Department of Economics)
    Abstract: We use an experiment to explore how subjects learn to play against computers which are programmed to follow one of a number of standard learning algorithms. The learning theories are (unbeknown to subjects) a best response process, fictitious play, imitation, reinforcement learning, and a trial & error process. We test whether subjects try to influence those algorithms to their advantage in a forward-looking way (strategic teaching). We find that strategic teaching occurs frequently and that all learning algorithms are subject to exploitation with the notable exception of imitation. The experiment was conducted, both, on the internet and in the usual laboratory setting. We find some systematic differences, which however can be traced to the different incentives structures rather than the experimental environment.
    Date: 2005–10–24
  2. By: Fehr, Ernst; Schmidt, Klaus M.
    Abstract: This paper surveys recent experimental and field evidence on the impact of concerns for fairness, reciprocity and altruism on economic decision making. It also reviews some new theoretical attempts to model the observed behavior.
    JEL: J3 D0 C9 C7
    Date: 2005–06
  3. By: Ryuichi YAMAMOTO (International Business School Brandeis University)
    Abstract: Recent research has shown a variety of computational techniques to describe evolution in an artificial stock market. One can distinguish the techniques based on at which level the learning of agents is modeled. The previous literature describes learning at either individual or social level. The level of learning is exogenously given, and agents involve only a particular level of learning when they update their rules. But such a setting doesn’t say anything about why agents choose a particular level of learning to update their trading rules. This paper introduces a learning mechanism which allows agents to choose one rule at each period among a set of ideas updated through both individual and social learning. A trading strategy performed well in the past is more likely to be selected by agents regardless it is created at individual or social level. This framework allows agents to choose a decision rule endogenously among a wider set of ideas. With such evolution, the following two questions are examined. First, since agents who have a wider set of ideas to choose are more intelligent, a question would arise if the time series from an economy with intelligent agents would converge to a rational expectation equilibrium (REE). Previous literature like LeBaron (2000) and Arthur et al. (1996) investigates the convergence property to the REE by looking at different time-horizons. It finds that the more information from the market agents get before updating their rules, the market is more likely to converge to the REE. But this paper investigates the convergence property by looking at different degrees of intelligence given a time horizon. The second investigates which level of learning is likely to dominate in the market. This is analyzed by investigating who chooses which level of learning and what proportion of the agents often uses individual or social learning. We analyze a hypothesis that wealthy agents often choose an idea from a set of her private ideas (from individual learning) while some with less wealth frequently imitate ideas from others (from social learning). The result eventually indicates that the agent-based stock market in this paper would possibly explain the mechanism of herding behavior which is often observed in financial markets
    Keywords: Individual learning; Social learning; Evolution; Asset pricing; Financial time series
    JEL: G12 G14 D83
    Date: 2005–11–11
  4. By: Jim C. Cox; Daniel Friedman; Vjollca Sadiraj
    Date: 2005–11–16
  5. By: Anabela Botelho (NIMA, Universidade do Minho); Glenn W. Harrison; Lígia Pinto (NIMA, Universidade do Minho); Elisabet E. Rutstrom (University of South Carolina)
    Abstract: Experiments can provide rich information on behavior conditional on the institutional rules of the game being imposed by the experimenter. We consider what happens when the subjects are allowed to choose the institution through a simple social choice procedure. Our case study is a setting in which sanctions may or may not be allowed to encourage "righteous behavior". Laboratory experiments show that some subjects in public goods environments employ costly sanctions against other subjects in order to enforce what appears to be a social norm of contribution. We show that this artificial society is not an attractive place to live, by any of the standard social choice criteria. If it came about because of evolutionary forces, as speculated, then The Blind Watchmaker was having one of his many bad days at the workbench. In fact, none of our laboratory societies with perfect strangers matching ever chose to live in such a world. Our findings suggest that the conditions under which a group or a society would choose a constitution that is based on voluntary costly sanctions are very special.
    Date: 2005–11
  6. By: Mary Burke; Gary Fournier
    Abstract: We develop an explanation of the emergence of local norms, and the associated phenom- enon of geographical variation in behavior. Individuals are assumed to interact locally with neighbors in an environment with a network externality. Although many patterns of behavior are possible, the dispersed interactive choices of agents are shown to select behavior that is locally uniform but globally diverse. The range of applications of the theory includes regional variation in the practice of medicine, technology choice, and corruption. The framework is also useful for further developing our understanding of important phenomena like lock-in, critical thresholds, and contagion
    Keywords: Social norms, networks, geographical variation
    JEL: C73
    Date: 2005–11–11

This nep-evo issue is ©2005 by Matthew Baker. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.