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Learning in public goods game: alternative model performance
Grohmannová, Klára ; Červinka, Michal (advisor) ; Gregor, Martin (referee)
Over the last fifty years the research field of the public goods game experi- ment became increasingly more convoluted. Especially in the area of learning models, which attempted to explain the experimental data, many models with different mechanisms were proposed and studied. However, when it comes to assessing the performance of the models in relation to each other, few conclu- sions were reached. This thesis attempts to further the comparative analysis conducted in Cotla (2015). Using R software simulations, three directional learning models are assessed on their ability to accurately predict experimental data. Among the considered models, K-strong equilibrium model is found to be the best predicting model for all of public goods game experiments considered in this thesis. JEL Classification C71, C73, C87, C92, D64, D90 Keywords public goods game, behavioral game theory, learning Title Learning in public goods game: alternative model performance
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