Experimental Games on Networks: Underpinnings of Behavior and Equilibrium Selection

Charness, Gary; Feri, Francesco; Meléndez-Jímenez, Miguel A.; Sutter, Matthias

doi:10.2139/ssrn.2426858

Cited by 8 publications

(11 citation statements)

References 45 publications

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“…In the laboratory, the researcher can exogenously vary the information people receive about others to evaluate the effect of information on outcomes and whether people use the information in a naive or sophisticated way. The experimental literature consistently finds that network information does matter for outcomes in a variety of domains, like expectation formation (Grimm and Mengel, 2020), cooperation behavior (Gallo and Yan, 2015), equilibrium selection (Charness et al, 2014), and coordination (Kearns et al, 2006).…”

Section: Related Literaturementioning

confidence: 97%

Statistical inference in social networks: how sampling bias and uncertainty shape decisions

Bjerre-Nielsen¹,

Busch²

2022

Preprint

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We investigate how individuals form expectations about population behavior using statistical inference based on observations of their social relations. Misperceptions about others' connectedness and behavior arise from sampling bias stemming from the friendship paradox and uncertainty from small samples. In a game where actions are strategic complements, we characterize the equilibrium and analyze equilibrium behavior. We allow for agent sophistication to account for the sampling bias and demonstrate how sophistication affects the equilibrium. We show how population behavior depends on both sources of misperceptions and illustrate when sampling uncertainty plays a critical role compared to sampling bias.

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Section: Related Literaturementioning

confidence: 97%

Statistical inference in social networks: how sampling bias and uncertainty shape decisions

Bjerre-Nielsen¹,

Busch²

2022

Preprint

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“…Models by Eshel et al (1998), Assenza et al (2008), Vega-Redondo et al (2005, and Vega-Redondo (2006) all predict that a higher degree of clustering will lead to better cooperation. Experimental work by Berninghaus et al (2002), Keser et al (1998), Cassar (2007), Charness et al (2014), and Melamed et al (2018) all find that higher clustering leads to more efficient outcomes. Yet, none of these experiments has network-member communication, and we are not aware of any paper that has considered how clustering in networks interacts with different forms of communication in terms of the rate of cooperative play induced.…”

Section: Previous Work Has Almost Completely Ignored the Effects Of C...mentioning

confidence: 98%

An Experimental Study on the Effects of Communication, Credibility, and Clustering in Network Games

Charness

Feri

Meléndez-Jímenez

et al. 2023

Review of Economics and Statistics

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We examine how pre-play communication and clustering affect play in a challenging hybrid experimental game on networks. Free-form chat is impressively effective in achieving the non-equilibrium efficient outcome, but restricted communication has little effect. We support this result with a model about the credibility of cheap-talk messages. We also offer a model of message diffusion that correctly predicts more rapid diffusion without clustering. We show an interaction effect of network structure and communication technologies. A remarkable result is that restricted communication is quite effective in a network Stag Hunt, but not in our extended game.

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“…Moreover, the equilibrium selection is also affected by the duration of the repeated game, as the coordination to the efficient equilibrium usually increases with the number of rounds of the myopic play [19,165]. In this respect, recent experiments argue that in most cases the efficient equilibrium is played with low effects due to the network structure [36,38,61]. Finally, degree heterogeneity seems to promote coordination with a crucial role played by well-connected individuals which trigger the adoption cascades [88,145].…”

Section: Appendix B: Related Literature On Dynamical Equilibrium Sele...mentioning

confidence: 99%

Coordination problems on networks revisited: statics and dynamics

Dall'Asta

2021

Preprint

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Simple binary-state coordination models are widely used to study collective socio-economic phenomena such as the spread of innovations or the adoption of products on social networks. The common trait of these systems is the occurrence of large-scale coordination events taking place abruptly, in the form of a cascade process, as a consequence of small perturbations of an apparently stable state. The conditions for the occurrence of cascade instabilities have been largely analysed in the literature, however for the same coordination models no sufficient attention was given to the relation between structural properties of (Nash) equilibria and possible outcomes of dynamical equilibrium selection. Using methods from the statistical physics of disordered systems, the present work investigates both analytically and numerically, the statistical properties of such Nash equilibria on networks, focusing mostly on random graphs. We provide an accurate description of these properties, which is then exploited to shed light on the mechanisms behind the onset of coordination/miscoordination on large networks. This is done studying the most common processes of dynamical equilibrium selection, such as best response, bounded-rational dynamics and learning processes. In particular, we show that well beyond the instability region, full coordination is still globally stochastically stable, however equilibrium selection processes with low stochasticity (e.g. best response) or strong memory effects (e.g. reinforcement learning) can be prevented from achieving full coordination by being trapped into a large (exponentially in number of agents) set of locally stable Nash equilibria at low/medium coordination (inefficient equilibria). These results should be useful to allow a better understanding of general coordination problems on complex networks. CONTENTS I. IntroductionII. A coordination model with heterogeneous payoffs III. Monotone decision processes A. Message-passing equations for minimal equilibria and global cascade condition B. Properties of the maximal equilibria IV. The equilibrium landscape A. Cavity method for Nash equilibria B. Results for random regular graphs C. Results on non-regular random graphs V. Dynamical equilibrium selection A. Best-response dynamics B. Stochastic stability C. Learning dynamics D. Comparative Statics: emergence of coordination on general random networks E. Payoff dominance vs. risk dominance VI. Conclusions

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Experimental Games on Networks: Underpinnings of Behavior and Equilibrium Selection

Cited by 8 publications

References 45 publications

Statistical inference in social networks: how sampling bias and uncertainty shape decisions

Statistical inference in social networks: how sampling bias and uncertainty shape decisions

An Experimental Study on the Effects of Communication, Credibility, and Clustering in Network Games

Coordination problems on networks revisited: statics and dynamics

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