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on Evolutionary Economics |
| By: | Jon Anderson (University of Minnesota, Morris); Stephen V. Burks (University of Minnesota, Morris); Jeffrey Carpenter (Middlebury College); Lorenz Goette (University of Lausanne); Karsten Maurer (Iowa State University); Daniele Nosenzo (University of Nottingham); Ruth Potter (University of Minnesota, Morris); Kim Rocha (University of Minnesota, Morris); Aldo Rustichini (University of Minnesota, Twin Cities) |
| Abstract: | We measure the other-regarding behavior in samples from three related populations in the upper Midwest of the United States: college students, non-student adults from the community surrounding the college, and adult trainee truckers in a residential training program. The first two groups were recruited according to procedures commonly used in experimental economics and therefore subjects self-selected into the experiment. Because the structure of their training program reduced the opportunity cost of participating dramatically, 91% of the solicited trainees participated in the third group, so there was little scope for self-selection in this sample. We find no differences in the elicited other-regarding preferences between the self-selected adults and the adult trainees, suggesting that selection into this type of experiment is unlikely to bias inferences with respect to non-student adult subjects. At the same time, we find a large difference between self-selected students and self-selected adults: the students appear considerably less pro-social. |
| Keywords: | methodology; selection bias; laboratory experiment; field experiment; other-regarding behavior, social preferences, truckload, trucker |
| JEL: | C90 |
| Date: | 2010–12 |
| URL: | http://d.repec.org/n?u=RePEc:cdx:dpaper:2010-22&r=evo |
| By: | Novarese, Marco; Lanteri, Alessandro; Tibaldeschi, Cesare |
| Abstract: | This article experimentally explores the way in which human agents learn how to process and manage new information. In an abstract setting, players should perform an everyday task: selecting information, making generalizations, distinguishing contexts. The tendency to generalize is common to all participants, but in a different way. Best players have a stringer tendency to generalise rules. A high score is, in fact, associated with low entropy for mistakes, that is with a tendency to repeat the same mistakes over and over. Though the repetition of mistakes might be considered a failure to properly employ feedback or a bias, it may instead turn out as a viable and successful procedure. This result is connected to the literature on learning. |
| Keywords: | behavioural entropy; cognitive economics; complexity; experiments; feedback; heuristics; learning |
| JEL: | A12 D83 C91 |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:28007&r=evo |
| By: | M. Cristelli; L. Pietronero; A. Zaccaria |
| Abstract: | We present an overview of some representative Agent-Based Models in Economics. We discuss why and how agent-based models represent an important step in order to explain the dynamics and the statistical properties of financial markets beyond the Classical Theory of Economics. We perform a schematic analysis of several models with respect to some specific key categories such as agents' strategies, price evolution, number of agents, etc. In the conclusive part of this review we address some open questions and future perspectives and highlight the conceptual importance of some usually neglected topics, such as non-stationarity and the self-organization of financial markets. |
| Date: | 2011–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1101.1847&r=evo |