We report results from an experiment that examines play in an indefinitely repeated, two-player Prisoner's Dilemma game. Each experimental session involves N subjects and a sequence of indefinitely repeated games. The main treatment consists of whether agents are matched in fixed pairings or matched randomly in each indefinitely repeated game. Within the random matching treatment, we elicit player's strategies and beliefs or vary the information that players have about their opponents. Contrary to a theoretical possibility suggested by Kandori [1992. Social norms and community enforcement. Rev. Econ. Stud. 59, 63-80], a cooperative norm does not emerge in the treatments where players are matched randomly. On the other hand, in the fixed pairings treatment, the evidence suggests that a cooperative norm does emerge as players gain more experience.
Since Griliches (1969), researchers have been intrigued by the idea that physical capital and skilled labor are relatively more complementary than physical capital and unskilled labor. This capital-skill complementarity hypothesis has received renewed attention recently, as researchers have suggested that this phenomenon might account for rising wage inequality between skilled and unskilled workers in several developed countries. In this paper we consider the cross-country evidence for capital-skill complementarity using a time-series, cross-section panel of 73 developed and less developed countries over a 25 year period. In particular, we focus on three empirical issues. First, what is the best specification of the aggregate production technology to address the capital-skill complementarity hypothesis. Second, how should we measure skilled labor? Finally, is there any cross-country evidence in support of the capital-skill complementarity hypothesis? Our main finding is that we are unable to reject the null hypothesis of no capital-skill complementarity using our panel data set.
Abstract.We report results from a laboratory experiment that provides the first direct test of the pivotal voter model. This model predicts that voters will rationally choose to vote only if their expected benefit from voting outweighs the cost. The expected benefit calculation involves the use of the voter's subjective probability that s/he will be pivotal to the election outcome; this probability is typically unobservable. In one of our experimental treatments we elicit these subjective probabilities using a proper scoring rule that induces truthful revelation of beliefs. The cost of voting and the payoff to the election winner are known constants, so the subjective probabilities allow us to directly test the pivotal voter model. We find only weak support for the model. While a higher subjective probability of being pivotal does increase the likelihood that an individual chooses to vote, the decisiveness probability thresholds used by subjects are not as crisp as the theory would predict. We do find that individuals learn over time to adjust their probabilities of being pivotal so that they are more consistent with the historical frequency of decisiveness. In a second treatment, we eliminate the elicitation of decisiveness probabilities and find little change in the voting behavior of subjects; we conclude from this second treatment that our belief elicitation procedure does not alter the manner in which individuals make voting decisions and therefore provides a reasonable direct test of the pivotal voter model.
We examine whether a simple agent-based model can generate asset price bubbles and crashes of the type observed in a series of laboratory asset market experiments beginning with the work of Smith, Suchanek and Williams (1988). We follow the methodology of Gode and Sunder (1993, 1997) and examine the outcomes that obtain when populations of zero-intelligence (ZI) budget constrained, artificial agents are placed in the various laboratory market environments that have given rise to price bubbles. We have to put more structure on the behavior of the ZI-agents in order to address features of the laboratory asset bubble environment. We show that our model of “near-zero-intelligence” traders, operating in the same double auction environments used in several different laboratory studies, generates asset price bubbles and crashes comparable to those observed in laboratory experiments and can also match other, more subtle features of the experimental data. Copyright Springer-Verlag Berlin/Heidelberg 2006Bubbles, Zero-intelligence traders, Double auction, Agent-based models, Experimental economics.,
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