nep-evo New Economics Papers
on Evolutionary Economics
Issue of 2005‒07‒18
five papers chosen by
Matthew Baker
US Naval Academy, USA

  1. Denial of Death and Economic Behavior By Wojciech Kopczuk; Joel Slemrod
  2. Conversations between Anthropologists and Economists By Metin Cosgel
  3. Group Cooperation Under Alternative Peer Punishment Technologies: An Experiment By Marco Casari; Luigi Luini
  4. Social Learning in Market Games By Carlo Altavilla; Luigi Luini; Patrizia Sbriglia
  5. Genetic Action Trees A New Concept for Social and Economic Simulation By Thomas Pitz; Thorsten Chmura

  1. By: Wojciech Kopczuk; Joel Slemrod
    Abstract: We model denial of death and its effect on economic behavior. Attempts to reduce death anxiety and the possibility of denial of mortality-relevant information interact with intertemporal choices and may lead to time-inconsistent behavior and other %u201Cbehavioral%u201D phenomena. In the model, repression of signals of mortality leads to underconsumption for unsophisticated individuals, but forward-sophisticated individuals may over-consume in anticipation of future denial and may seek ways to commit to act according to one%u2019s mortality prospects as currently perceived. We show that the mere possibility of engaging in this kind of denial leads to time-inconsistent but efficient behavior. Refusal to face up to the reality of death may help explain a wide range of empirical phenomena, including the underutilization of tax-advanced inter vivos gifts and inadequate purchase of life insurance.
    JEL: D11 D81 D91
    Date: 2005–07
  2. By: Metin Cosgel (University of Connecticut)
    Abstract: Interdisciplinary citation patterns and other indicators of the flow and sharing of academic knowledge suggest that economists and anthropologists do not talk to each other. Previous studies of this puzzling trend have typically attributed the problem to methodological differences between the two disciplines. Although there are significant differences between economics and anthropology in behavioral assumptions and modes of inquiry, similar differences exist between them and other disciplines (some with much heavier volumes of cross-citations with economics or anthropology), suggesting that the source of the problem lies elsewhere. This paper considers the problem at a deeper level by examining systematic differences in the preferences, capabilities, and literary cultures of economists and anthropologists. Adopting a rhetorical perspective, I consider not the firms, households, or tribes as the principal objective of analysis in the two disciplines, but the conversations between these units. These conversations (through non-verbal as well as verbal media) can be grouped into two genres, based on the type of problem they aim to solve. Those in the first genre aim to solve the problem of interest--how to align the incentives of the parties involved. Those in the second genre deal with the problem of knowledge--how to align localized, and dispersed information. Economists are interested and capable of dealing with primarily, if not exclusively, the first genre, and anthropologists focus on the second. This difference has far reaching consequences for how economists and anthropologists conduct their own scholarly conversations with their own colleagues, why they are having difficulty talking to each other across disciplinary boundaries, and what can be done to change the patterns of communication.
    Keywords: anthropology, conversation, interest, incentive, knowledge
    JEL: A12 B4 O5 Z1
    Date: 2005–07
  3. By: Marco Casari; Luigi Luini
    Abstract: This paper experimentally studies peer punishment under three alternative technologies. We find that the choice of peer punishment technology has a substantial impact on group performance. First, under a technology where at least two subjects in the group must agree before another group member can be punished, group cooperation and group net earnings are the highest. Second, outcomes are similar regardless of whether punishment choices are simultaneously or sequential. These results suggest that punishment is not perceived as a second-order public good but is instead an emotional reaction unresponsive to changes in the strategic environment.
    Keywords: decentralized punishment, public goods, other-regarding preferences, team production, experiments.
    JEL: C91 C92 D23
    Date: 2005–05
  4. By: Carlo Altavilla; Luigi Luini; Patrizia Sbriglia
    Abstract: The aim of our experiments is to test the effect of different information settings on firms’ behaviour in duopoly price and quantity games. We find that, when players have full information on their rivals’ choices, the imitation rule prevails and such learning behaviour induces more competitive outcomes in the Cournot market designs. By the same token, when information on the average industrial profit is provided, there is evidence of an increase in cooperation, and the majority of players experiment with new strategies when their payoff falls below the average profit (F. Palomino and F. Vega-Redondo, 1999; H. Dixon, 2000)
    Keywords: Learning, Cournot and Bertrand experiments
    JEL: D83 C91
    Date: 2005–05
  5. By: Thomas Pitz (Laboratory of Experimental Economics University of Bonn); Thorsten Chmura (Laboratory of Experimental Economics University of Bonn)
    Abstract: Multi-Agent Based Simulation is a branch of Distributed Artificial Intelligence that builds the base for computer simulations which connect the micro and macro level of social and economic scenarios. This paper presents a new method of modelling the formation and change of patterns of action in social systems with the help of Multi-Agent Simulations. The approach is based on two scientific concepts: Genetic Algorithms [Goldberg 1989, Holland 1975] and the theory of Action Trees [Goldman 1971]. Genetic Algorithms were developed following the biological mechanisms of evolution. Action Trees are used in analytic philosophy for the structural description of actions. The theory of Action Trees makes use of the observation of linguistic analysis that through the preposition by a semi-order is induced on a set of actions. Through the application of Genetic Algorithms on the attributes of the actions of an Action Tree an intuitively simple algorithm can be developed with which one can describe the learning behaviour of agents and the changes in action spaces. Using the extremely simplified economic action space, in this paper called “SMALLWORLDâ€, it is shown with the aid of this method how simulated agents react to the qualities and changes of their environment. Thus, one manages to endogenously evoke intuitively comprehensible changes in the agents‘ actions. This way, one can observe in these simulations that the agents move from a barter to a monetary economy because of the higher effectiveness or that they change their behaviour towards actions of fraud.
    Keywords: Multi agent system, genetic algorithms, actiontrees, learning, decision making, economic and social behaviour, distributed artificial intelligence
    JEL: C8
    Date: 2005–07–14

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