Download Artificial Economics and Self Organization: Agent-Based by Matteo Richiardi (auth.), Stephan Leitner, Friederike Wall PDF

By Matteo Richiardi (auth.), Stephan Leitner, Friederike Wall (eds.)

This quantity provides contemporary advances within the dynamic box of synthetic Economics and its quite a few functions. synthetic Economics offers a dependent method of version and examine fiscal and social structures. specifically, this process relies at the use of agent-based simulations and additional computational suggestions. the most goal is to investigate the results on the total structures’ point as effects from the brokers’ habit on the micro-level. those emergent features of advanced monetary and social structures can neither be foreseen nor are they meant. The emergence fairly makes those structures functionality. man made Economics in particular enables the research of this emergent structures’ habit. ​

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Extra resources for Artificial Economics and Self Organization: Agent-Based Approaches to Economics and Social Systems

Sample text

Therefore, we emphasize in this work the distinction of matchable versus non-matchable income, as done in [5] where it is empirically shown that the non-matchable component notably increased in recent years for US taxpayers, with visible repercussions on aggregate compliance. Take, for instance, two taxpayers with the same gross income: the first earns 90 % of his revenues from matchable wage, whereas the second gets 90 % of income from non-matchable sources. Clearly, it is materially possible for the latter to strategically conceal a vast amount of her income and devise profitable tax evasion.

However, our results equally show that any source of randomness can also (and perhaps more easily, since still in the absence of any centralization and deliberation) compensate for the inequality self-reinforcing 40 H. Bersini and N. van Zeebroeck tendency coming along with competition. Such irrational intrusions are already at work to soften the effect of free market since competing agents have limited time and cognitive resources to explore all possible offers and many apparently unexplained motivations undermine a lot of trading decisions, to the benefit of all.

Reidel, Dordrecht 3. Epstein JM, Axtell R (1996) Growing artificial societies – social science from the bottom up. MIT, Cambridge MA 4. Ihrig M, Troitzsch KG (2013) An extended research framework for the simulation era. In: Diaz R, Longo F (eds) 2013 Spring simulation multiconference on emerging M&S applications in industry and academia symposium and the modeling and humanities (EAIA and MathH 2013) (SpringSim ’13). Simulation Series, vol 45(5). Curran Associates, Red Hook, pp 99–106 5. Jazayeri P, Tohum MH (2012) Auswirkung der Einf¨uhrung eines Mindestlohns auf den Arbeitsmarkt, anhand eines Simulationsmodells.

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