This project will help develop a better understanding of human behavior in both individual decisions and in 'games', that is, settings where the decisions of various agents can interact and each agent's payoff may depend on the actions of others. In the setting of individual decisions, the project contributes to our understanding of dynamic choice, and in particular choice under uncertainty, where uncertainty includes uncertainty about one's own preferences (for a consumer, which goods will best serve their needs; for a firm, their costs and possible revenues) as well as uncertainty about the preferences of others (e.g. the costs of other firms) and also uncertainty about the plans and intentions of other agents. The project will also extend the PI's past work on temptation and self-control to take into account habit formation, with the idea that the amount of temptation depends on what the agent has learned about his preferences in the past. In the setting of games, the project will study how and when agents manage to cooperate via reciprocation even when they only imperfectly observe the intentions of the others- as for example when a friend says they are busy or sick and thus unable to come help you. The project will also develop improved ways to predict the long-run equilibrium outcomes of a game when players are initially uncertain about their opponent's strategies and learn about them by observation, where these observations are only partial: For example a losing bidder in an auction might see the winning bid but not see the losing ones, and not observe how much the other bidders would have been willing to pay.
Intellectual Merit: The work on choice under uncertainty will provide axiomatic characterizations of various sorts of stochastic choice behavior in dynamic settings, including the dynamic logit commonly used in empirical studies of consumer purchases, as the stochastic choice in these models can be interpreted as a consequence of the agent being uncertain of his or her own preferences. These theoretical foundations will shed light on when the specification is likely to be reasonable; they also may lead to alternative and equally tractable specifications that are better fits for some situations. The work on habit formation will incorporate insights from cognitive neuroscience to build more accurate models of how habits develop and how temptation distorts economics decisions. To understand reciprocal cooperation, the project will use experiments on repeated prisoner dilemma and ultimatum games when the intended actions are implemented with noise, comparing the outcomes to those when intentions as well as actions are observed, and to the outcomes in one-shot games. This will provide data to guide theories of altruism, reciprocation, and social preferences. The work on learning opponents? strategies will provide a better solution concept for many field settings and lab experiments, and thus a new tool for analyzing them.
Broader Impact: The project will be strengthen ties between economic theorists and experimenters interested in behavioral economics, between economists working on decision theory and those doing estimation of demand systems, and between economists and psychologists interested in addiction, habit formation, and willpower. The grant will also provide support for graduate students doing research on related topics. Taking a longer term view, we are hopeful that the proposed research will enhance our understanding of how and when reciprocal altruism leads to cooperation; this is of fundamental importance in many branches of social science and is also a key issue in evolutionary biology.
