The role of natural language communication in economic exchange has been the focus of substantial experimental analysis. Recently, scholars have taken the important step of investigating whether certain types of communication (e.g., promises) might affect decisions differently than other types of communication. This requires classifying natural language messages. Unfortunately, no broadly-accepted method is available for this purpose. We here describe a coordination game for classification of natural language messages. The game is similar in spirit to the “ESP” game that has proven successful for the classification of tens of millions of internet images. We compare our approach to self-classification as well as to classifications based on a standard content analysis. We argue that our classification game has advantages over those alternative approaches, and that these advantages might stem from the salient rewards earned by our game's participants.

In this paper we use experimental data from rural Cameroon to quantify the effect of social distance on trust and altruism. Our measure of social distance is relevant to everyday economic interactions: subjects in a Trust Game play with fellow villagers or with someone from a different village. We find that significantly more money is sent when the players are from the same village. Other factors that influence transfers at least as much as the same-village effect are gender, education and membership of rotating credit groups. To test whether Senders are motivated by altruism, they also play a Triple Dictator Game. Senders transfer significantly more money on average in the Trust Game than in the Triple Dictator Game. However, there is also a social distance effect in the Triple Dictator Game. Results from a Risk Game suggest that Trust Game transfers are uncorrelated with attitudes to risk.

We report on an experiment conducted to evaluate the effects of varying the way in which market information is presented to participants in laboratory Cournot duopolies. We find that the most standard variations, which are the use of a profit table or a profit calculator, yield indistinguishable performance. However, the addition of a best-response option to the profit calculator tends to increase aggregate output to the Cournot level and decrease the incidence of tacit collusion.

I survey the literature post Ledyard (Handbook of Experimental Economics, ed. by J. Kagel, A. Roth, Chap. 2, Princeton, Princeton University Press, 1995) on three related issues in linear public goods experiments: (1) conditional cooperation; (2) the role of costly monetary punishments in sustaining cooperation and (3) the sustenance of cooperation via means other than such punishments. Many participants in laboratory public goods experiments are “conditional cooperators” whose contributions to the public good are positively correlated with their beliefs about the average group contribution. Conditional cooperators are often able to sustain high contributions to the public good through costly monetary punishment of free-riders but also by other mechanisms such as expressions of disapproval, advice giving and assortative matching.

Agent-based simulations and human-subject experiments explore the emergence of respect for property in a specialization and exchange economy with costless theft. Software agents, driven by reciprocity and hill-climbing heuristics and parameterized to replicate humans when property is exogenously protected, are employed to predict human behavior when property can be freely appropriated. Agents do not predict human behavior in a new set of experiments because subjects innovate, constructing a property convention of “mutual taking” in 5 out of the 6 experimental sessions that allows exchange to crowd out theft. When the same convention is made available to agents, they adopt it and again replicate human behavior. Property emerges as a social convention that exploits the capacity for reciprocity to sustain trade.

We study the effects of closing price manipulation in an experimental market to evaluate the social harm caused by manipulation. We find that manipulators, given incentives similar to many actual manipulation cases, decrease price accuracy and liquidity. The mere possibility of manipulation alters market participants’ behavior, leading to reduced liquidity. We find evidence that ordinary traders attempt to profitably counteract manipulation. This study provides examples of the strategies employed by manipulators, illustrates how these strategies change in the presence of detection penalties and assesses the ability of market participants to identify manipulation.