Curty, Philippe; Marsili, Matteo Phase coexistence in a forecasting game. (English) Zbl 1456.91070 J. Stat. Mech. Theory Exp. 2006, No. 3, Paper No. P03013, 8 p. (2006). Summary: Individual choices are either based on personal experience or on information provided by peers. The latter case causes individuals to conform to the majority in their neighbourhood. Such herding behaviour may be very efficient in aggregating disperse private information, thereby revealing the optimal choice. However if the majority relies on herding, this mechanism may dramatically fail to aggregate the information correctly, causing the majority to adopt the wrong choice. We address these issues in a simple model of interacting agents who aim at giving a correct forecast of a public variable, either seeking private information or resorting to herding. As the fraction of herders increases, the model features a phase transition beyond which a state where most agents make the correct forecast coexists with one where most of them are wrong. Simple strategic considerations suggest that indeed such a system of agents self-organizes deep in the coexistence region. There, agents tend to agree much more among themselves than with what they aim at forecasting, as found in recent empirical studies. Cited in 4 Documents MSC: 91B80 Applications of statistical and quantum mechanics to economics (econophysics) 91A90 Experimental studies 82B26 Phase transitions (general) in equilibrium statistical mechanics Keywords:applications to game theory and mathematical economics; critical phenomena of socio-economic systems; interacting agent models PDFBibTeX XMLCite \textit{P. Curty} and \textit{M. Marsili}, J. Stat. Mech. Theory Exp. 2006, No. 3, Paper No. P03013, 8 p. (2006; Zbl 1456.91070) Full Text: DOI arXiv References: [1] Bikhchandani S, Hirshleifer D and Welch I 1992 J. Pol. Econ.100 992 · doi:10.1086/261849 [2] Cont R and Bouchaud J 2000 Macroecon. Dyn.4 170 · Zbl 1060.91506 · doi:10.1017/S1365100500015029 [3] Stauffer D 2001 Adv. Complex Syst.4 19 · Zbl 1090.82508 · doi:10.1142/S0219525901000061 [4] Weisbuch G et al 2002 Complexity7 55 · doi:10.1002/cplx.10031 [5] Eguíluz V and Zimmermann M 2003 Phys. Rev. Lett.85 5659 · doi:10.1103/PhysRevLett.85.5659 [6] Zhou W-X and Sornette D 2005 Preprint physics/0503230 [7] Michard Q and Bouchaud J-P 2005 Preprint cond-mat/0504079 [8] Guedj O and Bouchaud J-P 2004 Preprint cond-mat/0410079 [9] Vega-Redondo F 2004 Economics and the Theory of Games (Cambridge: Cambridge University Press) [10] Challet D, Marsili M and Zhang Y-C 2004 The Minority Game (Oxford: Oxford University Press) [11] Borgers T and Sarin R 1997 J. Econ. Theory77 1 · Zbl 0892.90198 · doi:10.1006/jeth.1997.2319 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.