Colasante, Annarita (2016): Evolution of Cooperation in Public Good Game.
Preview |
PDF
MPRA_paper_72577.pdf Download (1MB) | Preview |
Abstract
This paper presents an investigation about cooperation in a Public Good Game using an Agent Based Model calibrated on experimental data. Starting from the experiment proposed in Colasante and Russo (2016), we analyze the dynamic of cooperation in a Public Good Game where agents receive an heterogeneous income and choose both the level of contribution and the distribution rule. The starting point is the calibration and the output validation of the model using the experimental results. Once tested the goodness of fit of the Agent Based Model, we run some policy experiment in order to verify how each distribution rule, i.e. equidistribution, proportional to contribution and progressive, affects the level of contribution in the simulated model. We find out that the share of cooperators decreases over time if we exogenously set the equidistribution rule. On the contrary, the share of cooperators converges to 100% if we impose the progressive rule. Finally, the most interesting result refers to the effect of the progressive rule. We observe that, in the case of high inequality, this rule is not able to reduce the heterogeneity of income.
Item Type: | MPRA Paper |
---|---|
Original Title: | Evolution of Cooperation in Public Good Game |
English Title: | Evolution of Cooperation in Public Good Game |
Language: | English |
Keywords: | Public Good Game, Cooperation, Social Influence |
Subjects: | C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling D - Microeconomics > D7 - Analysis of Collective Decision-Making > D71 - Social Choice ; Clubs ; Committees ; Associations H - Public Economics > H4 - Publicly Provided Goods > H41 - Public Goods |
Item ID: | 72577 |
Depositing User: | Dr Annarita Colasante |
Date Deposited: | 17 Jul 2016 14:34 |
Last Modified: | 07 Oct 2019 07:51 |
References: | Alfarano, S., Lux, T., and Wagner, F. (2007). Empirical validation of stochastic models of interacting agents. The European Physical Journal B, 55(2), 183-187. Andreoni, J., Croson, R., et al. (2008). Partners versus strangers: Random rematching in public goods experiments. Handbook of experimental economics results, 1, 776-783. Chaudhuri, A. (2011). Sustaining cooperation in laboratory public goods experiments: a selective survey of the literature. Experimental Economics, 14(1), 47-83. Colasante, A. and Russo, A. (2016). Voting for the distribution rule in a public good game with heterogeneous endowments. Journal of Economic Interaction and Coordination, pages 1-25. Fehr, E. and Gachter, S. (1998). Reciprocity and economics: The economic implications of homo reciprocans. European economic review, 42(3), 845-859. Fischbacher, U. and Gachter, S. (2010). Social preferences, beliefs, and the dynamics of free riding in public goods experiments. American Economic Review, 100(1), 541-556. Garcia, R., Rummel, P., and Hauser, J. (2007). Validating agent-based marketing models through conjoint analysis. Journal of Business Research, 60(8), 848-857. Helbing, D., Yu, W., and Rauhut, H. (2011). Self-organization and emergence in social systems: Modeling the coevolution of social environments and cooperative behavior. The Journal of Mathematical Sociology, 35(1-3), 177-208. Janssen, M. A. and Ostrom, E. (2006). Empirically based, agent-based models. Ecology and Society, 11(2), 37. Kolm, S.-C. and Ythier, J. M. (2006). Handbook of the economics of giving, altruism and reciprocity: Foundations, volume 1. Elsevier. Nikiforakis, N. and Normann, H.-T. (2008). A comparative statics analysis of punishment in public-good experiments. Experimental Economics, 11(4), 358-369. Recchioni, M. C., Tedeschi, G., and Gallegati, M. (2015). A calibration procedure for analyzing stock price dynamics in an agent-based framework. Journal of Economic Dynamics and Control, 60, 1-25. Roth, A. E. and Erev, I. (1995). Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term. Games and economic behavior, 8(1),64-212. Sargent, R. G. (2013). Verification and validation of simulation models. Journal of Simulation, 7(1), 12-24. Szolnoki, A. and Perc, M. (2010). Reward and cooperation in the spatial public goods game. EPL (Europhysics Letters), 92(3), 38003. Tedeschi, G., Gallegati, M., Mignot, S., and Vignes, A. (2012). Lost in transactions: The case of the boulogne s/mer fish market. Physica A: Statistical Mechanics and its Applications, 391(4),1400-1407. Tedeschi, G., Vitali, S., and Gallegati, M. (2014). The dynamic of innovation networks: a switching model on technological change. Journal of Evolutionary Economics, 24(4), 817-834. Vitali, S., Tedeschi, G., and Gallegati, M. (2013). The impact of classes of innovators on technology,financial fragility, and economic growth. Industrial and Corporate Change, 22(4), 1069-1091. Windrum, P., Fagiolo, G., and Moneta, A. (2007). Empirical validation of agent-based models: Alternatives and prospects. Journal of Artificial Societies and Social Simulation, 10(2), 8. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/72577 |