Large scale and information effects on cooperation in public good games.

The problem of public good provision is central in economics and touches upon many challenging societal issues, ranging from climate change mitigation to vaccination schemes. However, results which are supposed to be applied to a societal scale have only been obtained with small groups of people, with a maximum group size of 100 being reported in the literature. This work takes this research to a new level by carrying out and analysing experiments on public good games with up to 1000 simultaneous players. The experiments are carried out via an online protocol involving daily decisions for extended periods. Our results show that within those limits, participants' behaviour and collective outcomes in very large groups are qualitatively like those in smaller ones. On the other hand, large groups imply the difficulty of conveying information on others' choices to the participants. We thus consider different information conditions and show that they have a drastic effect on subjects' contributions. We also classify the individual decisions and find that they can be described by a moderate number of types. Our findings allow to extend the conclusions of smaller experiments to larger settings and are therefore a relevant step forward towards the understanding of human behaviour and the organisation of our society.