Affirmative Action Policy and Effort Levels. Sequential-Move Contest Game Argument

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.

When Do We Learn to Cooperate? The Role of Social Learning in Social Dilemmas

In this paper, I look at the interaction between social learning and cooperative behavior. I model this using a social dilemma game with publicly observed sequential actions and asymmetric information about pay offs. I find that some informed agents in this model act, individually and without collusion, to conceal the privately optimal action. Because the privately optimal action is socially costly the behavior of informed agents can lead to a Pareto improvement in a social dilemma. In my model I show that it is possible to get cooperative behavior if information is restricted to a small but non-zero proportion of the population. Moreover, such cooperative behavior occurs in a finite setting where it is public knowledge which agent will act last. The proportion of cooperative agents within the population can be made arbitrarily close to 1 by increasing the finite number of agents playing the game. Finally, I show that under a broad set of conditions that it is a Pareto improvement on a corner value, in the ex-ante welfare sense, for an interior proportion of the population to be informed.

The Impact of Information Provision on Agglomeration Bonus Performance: An Experimental Study on Local Networks

The Agglomeration Bonus (AB) is a mechanism to induce adjacent landowners to spatially coordinate their land use for the delivery of ecosystem services from farmland. This paper uses laboratory experiments to explore the performance of the AB in achieving the socially optimal land management configuration in a local network environment where the information available to subjects varies. The AB poses a coordination problem between two Nash equilibria: a Pareto dominant and a risk dominant equilibrium. The experiments indicate that if subjects are informed about both their direct and indirect neighbors’ actions, they are more likely to coordinate on the Pareto dominant equilibrium relative to the case where subjects have information about their direct neighbors’ action only. However, the extra information can only delay – and not prevent – the transition to the socially inferior risk dominant Nash equilibrium. In the long run, the AB mechanism may only be partially effective in enhancing delivery of ecosystem services on farming landscapes featuring local networks.