Many resource allocation contests have the property that individuals undertake costly actions to appropriate a potentially divisible resource. We design an experiment to compare individuals’ decisions across three resource allocation contests which are isomorphic under risk-neutrality. The...

This paper implements an experimental test of a game-theoretic model of equilibrium profiling. Attackers choose a demographic “type” from which to recruit, and defenders choose which demographic types to search. Some types are more reliable than others in the sense of having a higher...

This paper implements an experimental test of a game-theoretic model of equilibrium profiling. Attackers choose a demographic “type” from which to recruit, and defenders choose which demographic types to search. Some types are more reliable than others in the sense of having a higher...

The stability of International Environmental Agreements (IEA) is analyzed by using game theory. The integrated assessment model FUND provides the cost-bene¯t payo® functions of pollution abatement for sixteen di®erent world regions. The farsighted stability concept of Chwe (1994) is used and...

Non-cooperative game theoretical models of international environmental agreements (IEAs) use the assumption that coalition of signatories maximize their joint welfare. The joint maxi- mization assumption is compared with di®erent sharing pro¯t schemes such as Shapley value, Nash bargaining...

We investigate the stability of International Environmental Agreements (IEA) by applying game theory. The paper extends further our previous research on farsightedly stable coalitions and preferred farsightedly stable coalitions (Osmani & Tol 2007). The integrated assessment model FUND provides...

Game theory is used to analyze the formation and stability of coalitions for environmental protection. The paper extends further our previous research on farsightedly stable coalitions and preferred farsightedly stable coalitions (Osmani & Tol 2007a). The integrated assessment model FUND...