2 resultados para Programmazione video-giochi, iOS, Game Engine, Cocos2D

em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom


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In this paper we analyse a simple two-person sequential-move contest game with heterogeneous players. Assuming that the heterogeneity could be the consequence of past discrimination, we study the effects of implementation of affirmative action policy, which tackles this heterogeneity by compensating discriminated players, and compare them with the situation in which the heterogeneity is ignored and the contestants are treated equally. In our analysis we consider different orders of moves. We show that the order of moves of contestants is a very important factor in determination of the effects of the implementation of the affirmative action policy. We also prove that in such cases a significant role is played by the level of the heterogeneity of individuals. In particular, in contrast to the present-in-the-literature predictions, we demonstrate that as a consequence of the interplay of these two factors, the response to the implementation of the affirmative action policy option may be the decrease in the total equilibrium effort level of the contestants in comparison to the unbiased contest game.

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We provide experimental evidence on the ability to detect deceit in a buyer-seller game with asymmetric information. Sellers have private information about the buyer's valuation of a good and sometimes have incentives to mislead buyers. We examine if buyers can spot deception in face-to-face encounters. We vary (1) whether or not the buyer can interrogate the seller, and (2) the contextual richness of the situation. We find that the buyers' prediction accuracy is above chance levels, and that interrogation and contextual richness are important factors determining the accuracy. These results show that there are circumstances in which part of the information asymmetry is eliminated by people's ability to spot deception.