Download Agent-Based Approaches in Economic and Social Complex by Yuhsuke Koyama, Ko Ishiyama, Hiroyuki Kaneko, Isao Ono, PDF

By Yuhsuke Koyama, Ko Ishiyama, Hiroyuki Kaneko, Isao Ono, Hiroyuki Matsui (auth.), Takao Terano Ph.D., Hajime Kita Dr. Eng., Hiroshi Deguchi Ph.D., Kyoichi Kijima Dr. Eng. (eds.)

ISBN-10: 4431713069

ISBN-13: 9784431713067

Agent-Based Modeling/Simulation (ABM/ABS) is an rising box that permits bottom-up and experimental research in social sciences similar to economics, administration, sociology and politics. The chapters of this booklet are the chosen papers from these provided the 3rd foreign Workshop on Agent-Based techniques in financial and Social complicated structures held in Tokyo, Japan in 2005. Articles during this e-book covers methodological concerns, computational model/software, mix with gaming simulation, and real-world purposes to fiscal, management/organizational and social issues.

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Additional info for Agent-Based Approaches in Economic and Social Complex Systems IV: Post-Proceedings of The AESCS International Workshop 2005

Sample text

Journal of Monetary Economics 27: 39-71. 15. Lucas D (1994) Asset Pricing with Undiversifiable Risk and Short Sales Constraints: Deepening the Equity Premium Puzzle. Journal of Monetary Economics 34: 325-341. 16. Mankiw G-N, Rotemberg J-J, Summers L-H (1985) Intertemporal Substitution in Macroeconomics. Quarterly Journal of Economics 100: 225-251. 17. Obstfeld M (1994) Risk Taking, Global Diversification, and Growth. American Economic Review 84: 1310-1329. 18. Sandroni A (2000) Do Markets Favor Agents Able to Make Accurate Predictions?

He simulates a learning process and compares his results to a game theoretic prediction under the assumption of rational agents. In our paper, we find a learning process involving a convergence toward a stable state to which, in turn, we compare to the empirical facts. Our main results are consistent with the empirical market' dynamics: the sellers' negotiating power is always superior to the buyers and tends to decrease. The loyalty of buyers does not influence the transactions prices, and the frequency of each "nature of contact" is similar to the observed ones.

The third set of simulations shows the influence of the time buyers can spend on the market. The simulation which results are nearest to the empirical data is the one where the sellers stay longest on the market: the frequency of the different nature of contacts is well reproduced; the bargaining power index decreases. The value to a buyer for 4 visits to sellers each day is in line with the qualitative survey conducted on the market. Hence, given the values of parameters, the learning process gives results close to the empirical observations.

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