Altruism, equity, and reciprocity in a gift-exchange experiment: an encompassing approach

Considerable experimental evidence suggests that non-pecuniary motives must be addressed when modeling behavior in economic contexts. Recent theories of non-pecuniary motives can be classified as altruism-, equity-, or reciprocity-based. We outline the qualitative differences in prediction these alternative explanations yield in a gift-exchange game. We estimate and compare leading approaches in these categories, using experimental data. We then offer a flexible approach that nests the above three approaches, thereby allowing for nested hypothesis testing and for determining the relative strength of each of the competing theories. In addition, the encompassing approach provides a functional form for utility in different settings without the restrictive nature of the approaches nested within it. Using this flexible form for nested tests, we find that intentional reciprocity, distributive concerns, and altruistic considerations all play a significant role in players' decisions.     

A Psychological Reexamination of the Bertrand Paradox

The Bertrand paradox describes a situation in which two competing firms reach an outcome where both price at marginal cost. In laboratory experiments, this equilibrium is not generally observed. Existing empirical works on Bertrand competition have found evidence for boundedly rational models. We find that such models are useful in organizing behavior in early stages of the game, but less so in later stages. We show that a new model, coarse grid Nash equilibrium, based on the assumption that subjects discretize the strategy space, explains the data better.     

Subgame perfection in ultimatum bargaining trees

In typical experiments on ultimatum bargaining, the game is described verbally and the majority of subjects deviate from subgame-perfect behavior. Proposers typically offer significantly more than the minimum possible and Responders reject “unfair” offers. In this work, we show that when the ultimatum bargaining game is presented as an abstract game tree, the vast majority of behavior is consistent with individualistic preferences and subgame-perfection. This finding raises doubts about theories that ignore the potential influence of social context and experiments that do not control for social context.     

Bargaining under a deadline: evidence from the reverse ultimatum game

We study a “reverse” ultimatum game, in which proposers have multiple chances to offer responders a division of some fixed pie. The game ends if the responder accepts an offer, or if, following a rejection, the proposer decides not to make a better offer. The unique subgame perfect equilibrium gives the proposer the minimum possible payoff. Nevertheless, the experimental results are not too different from those of the standard ultimatum game, although proposers generally receive slightly less than half of the surplus.We use the reverse ultimatum game to study deadlines experimentally. With a deadline, the subgame perfect equilibrium prediction is that the proposer gets the entire surplus.Deadlines are used strategically to influence the outcome, and agreements are reached near the deadline. Strategic considerations are evident in the differences in observed behavior between the deadline and no deadline conditions, even though agreements are substantially less extreme than predicted by perfect equilibrium.     

Optimal product strategies in the presence of network externalities

A network externality exists when a user’s benefit from a product increases with the number of other users in the same network. We examine the possibility that a software firm may exploit network externalities by introducing a limited feature version of its commercially available software into the market. The two versions need not be perfectly compatible and network externalities are allowed to decline as the difference between the versions increases. We obtain conditions under which introducing a limited feature version is optimal.     

Competition between auctions

Even though auctions are capturing an increasing share of commerce, they are typically treated in the theoretical economics literature as isolated. That is, an auction is typically treated as a single seller facing multiple buyers or as a single buyer facing multiple sellers. In this paper, we review the state of the art of competition between auctions. We consider three different types of competition: competition between auctions, competition between formats, and competition between auctioneers vying for auction traffic. We highlight the newest experimental, statistical, and analytical methods in the analysis of competition between auctions.     

Two-stage lotteries and the value of unresolved uncertainty

We study two-stage lotteries wherein, in the first stage, the consumer may be awarded a lottery ticket for some choices and, in the second stage, some of the lottery tickets win prizes. In a series of Internet experiments, we examine store choice and repeat visits in response to immediate and two-stage lottery incentives. We show that a delayed resolution of uncertainty may dramatically increase the desired response over immediate resolution. However, this effect is due to an interaction of several potentially contradictory effects. When prizes are frequent, the effectiveness of the two-stage lottery is expected to decline.     

Between-game rule learning in dissimilar symmetric normal-form games

Rule learning posits that decision makers, rather than choosing over actions, choose over behavioral rules with different levels of sophistication. Rules are reinforced over time based on their historically observed payoffs in a given game. Past works on rule learning have shown that when playing a single game over a number of rounds, players can learn to form sophisticated beliefs about others. Here we are interested in learning that occurs between games where the set of actions is not directly comparable from one game to the next. We study a sequence of ten thrice-played dissimilar games. Using experimental data, we find that our rule learning model captures the ability of players to learn to reason across games. However, this learning appears different from within-game rule learning as previously documented. The main adjustment in sophistication occurs by switching from non-belief-based strategies to belief-based strategies. The sophistication of the beliefs themselves increases only slightly over time.     

Are You Risk Averse over Other People's Money?

Decisions with uncertain outcomes are often made by one party in settings where another party bears the consequences. Whenever an individual is delegated to make decisions that affect others, such as in the typical corporate structure, does the individual make decisions that reflect the risk preferences of the party bearing the consequences? We examine this question in two simple settings, lottery choices and sealed‐bid auctions, using controlled laboratory experiments. We find that when an individual makes a decision for an anonymous stranger, there is a tendency to exhibit less risk aversion. This reduction in risk aversion is relative to his or her own preferences, and it is also relative to his or her belief about the preferences of others. This result has significant implications for the design of contracts between principals and agents.     

Optimal freeware quality in the presence of network externalities: an evolutionary game theoretical approach

New software products often face difficulty in achieving market penetration. A potential remedy is to offer a freeware version of the software to encourage initial adoption and establish a larger user base for the software, thereby increasing the commercial version's value to adopters in future periods. However, to avoid complete cannibalization of the commercial version, the freeware version's quality must be sufficiently low and the price of the commercial version must not be too high. We model the effect of these two decision variables, price and freeware quality, on the adoption of software using static and evolutionary game theory.