Predicting Efficiency in Threshold Public Good Games: A Learning Direction Theory Approach

Federica Alberti, Anna Cartwright and Edward Cartwright

No 2021-01, Working Papers in Economics & Finance from University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group

Abstract: In this paper we propose a tractable model of behavior in threshold public good games. The model is based on learning direction theory. We find that individual behavior is consistent with the predictions of the model. Moreover, the model is able to accurately predict the success rate of groups in providing the public good. We apply this to give novel insight on the assurance problem by showing that the problem (of coordinating on the inefficient equilibrium of no contributions) is only likely with a relatively low endowment. In developing the model we compare and contrast best reply learning and impulse balance theory. Our results suggest that best reply learning provides a marginally better fit with the data.

Keywords: public good; threshold; learning direction theory; impulse balance theory; counterfactual thinking (search for similar items in EconPapers)
JEL-codes: C72 C92 H41 (search for similar items in EconPapers)
Pages: 46
Date: 2021-01-27
New Economics Papers: this item is included in nep-gth
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