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Elias Fernández (VUB)

November 21, 2019 @ 13:00 - 14:00

Title: Uncertain times promote polarisation and reciprocation in a public goods game with risky commons

Abstract: Anthropogenic climate change, public health measures or even group hunting, are some of the many collective endeavors characterized by uncertain, long-term and non-linear returns. We operationalize these scenarios in a collective-risk dilemma, where players can invest into a public good over a number of rounds, and will only observe their payoff when the game ends. The risk of crossing a dangerous threshold is able to transform a traditional public goods game, where players incur in the well-known tragedy of commons, into a coordination game, where success depends on surpassing a coordination barrier. Behavioral experiments indicate that, when the risk of collective loss is high, slightly more than half of the experimental groups are able to coordinate and avoid the dangerous threshold. However, uncertainties over environmental variables, such as the placement of the threshold, revert the game back into a prisoner’s dilemma, decreasing group success. Here we show experimentally the effect of uncertainty about the number of rounds the game will take, i.e., how much time the players have to avoid the consequences of surpassing a dangerous threshold. Surprisingly, our results indicate that, for low levels of this timing uncertainty, not only collective success does not decrease significantly, but we observe a behavioral shift. Contrarily to what happens when there is no uncertainty, participants invest earlier and in a more polarized manner. Also, a behavioural analysis of the experimental data reveals that, under timing uncertainty, participants of successful groups tend to reciprocate in a similar fashion to the group analogous of the Tit-for-Tat strategy, where players only increase their investments if the group does the same. Such a result indicate that certain behavioral ecosystems are more successful than others in achieving the equilibrium that is socially optimum.


November 21, 2019
13:00 - 14:00
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