Behavioral Economics: Past, Present, Future

Behavioral economics increases the explanatory power of economics by providing it with more realistic psychological foundations. This book consists of representative recent articles in behavioral economics. This chapter is intended to provide an introduction to the approach and methods of behavioral economics, and to some of its major findings, applications, and promising new directions. It also seeks to fill some unavoidable gaps in the chapters’ coverage of topics

From Bounded Rationality to Behavioral Economics

The paper provides an brief overview of the “state of the art” in the theory of rational decision making since the 1950’s, and focuses specially on the evolutionary justification of rationality. It is claimed that this justification, and more generally the economic methodology inherited from the Chicago school, becomes untenable once taking into account Kauffman’s Nk model, showing that if evolution it is based on trial-and-error search process, it leads generally to sub- optimal stable solutions: the ‘as if’ justification of perfect rationality proves therefore to be a fallacious metaphor. The normative interpretation of decision-making theory is therefore questioned, and the two challenging views against this approach , Simon’s bounded rationality and Allais’ criticism to expected utility theory are discussed. On this ground it is shown that the cognitive characteristics of choice processes are becoming more and more important for explanation of economic behavior and of deviations from rationality. In particular, according to Kahneman’s Nobel Lecture, it is suggested that the distinction between two types of cognitive processes – the effortful process of deliberate reasoning on the one hand, and the automatic process of unconscious intuition on the other – can provide a different map with which to explain a broad class of deviations from pure ‘olympian’ rationality. This view requires re-establishing and revising connections between psychology and economics: an on-going challenge against the normative approach to economic methodology.Bounded Rationality, Behavioral Economics, Evolution, As If

On the normative status of mixed strategies

Flipping a coin to decide what to do is a common feature of everyday life. Mixed strategies, as these are called, have a thorny status in normative decision theories. This paper explores various ways to justify choosing one's actions at random. I conclude that it is hard to make sense of this behavior without dealing with some difficult consequences

On the normative status of mixed strategies

Flipping a coin to decide what to do is a common feature of everyday life. Mixed strategies, as these are called, have a thorny status in normative decision theories. This paper explores various ways to justify choosing one's actions at random. I conclude that it is hard to make sense of this behavior without dealing with some difficult consequences

A micro-foundation for the Laffer curve in a real effort experiment

A conjecture of Laffer, which had considerable influence on fiscal doctrine, is that tax revenues of a Leviathan state eventually decrease when the tax rate exceeds a threshold value. We conduct a real effort experiment, in which a "worker" is matched with a non-working partner, to elicit the conditions under which a Laffer curve can be observed. We ran four different treatments by manipulating work opportunities and the power to tax. In the endogenous treatment, the non-working partner chooses a tax rate among the set of possibilities and receives the revenue generated by her choice and the worker's effort response to this tax rate. In the exogenous treatment, the tax rate is randomly selected by the computer and the non-working partner merely receives the revenue from taxes. The Laffer curve phenomenon cannot be observed in the exogenous treatments, but arises in endogenous treatments. Tax revenues are then maximized at a 50% tax rate. We demonstrate that an "efficiency tax" model (with or without inequity aversion) falls short of predicting our experimental Laffer curve but an alternative model of social preferences provides a micro-foundation for the latter. This new model endogenously generates a social norm of fair taxation at a 50% tax rate under asymmetric information about workers' type. Taxpayers manage to enforce this norm by working less whenever it has been violated but do not systematically reward "kind" tax setters. Workers who maximize their expected wealth adjust work to the tax rate equitably so that tax revenues remain at a fair level. Workers who respond affectively to norm violations just refuse to work so that tax revenues are cut down. Workers endowed with higher work opportunities tend to respond more emotionally to unfair taxation in our experiment, which is consistent with the observed Laffer curve and with the history of tax revolts.Taxation and labor supply, Laffer curve, experimental economies.

Anxiety and Learning in Dynamic and Static Clock Game Experiments

In clock games, agents receive differently-timed private signals when an asset value is above its fundamental. The price crashes to the fundamental when K of N agents have decided to sell. If selling decisions are private, bubbles can be sustained because people delay selling, after receiving signals, knowing that others will delay too. Our results replicate the main features of the one previous experimental study of clock game (in two subject pools): Selling delays are shorter than predicted, but converge toward equilibrium predictions over repeated trials. We also find that delays are shorter in a dynamic game in which selling decisions unfold over time, compared to a static equivalent in which subjects precommit to selling decisions. A model of learning with growing anxiety after signal arrival can reproduce the empirical observations of shorter-than-predicted delay, smaller delay after later signal arrival, and shorter delays in dynamic games

Computational Results for Extensive-Form Adversarial Team Games

We provide, to the best of our knowledge, the first computational study of extensive-form adversarial team games. These games are sequential, zero-sum games in which a team of players, sharing the same utility function, faces an adversary. We define three different scenarios according to the communication capabilities of the team. In the first, the teammates can communicate and correlate their actions both before and during the play. In the second, they can only communicate before the play. In the third, no communication is possible at all. We define the most suitable solution concepts, and we study the inefficiency caused by partial or null communication, showing that the inefficiency can be arbitrarily large in the size of the game tree. Furthermore, we study the computational complexity of the equilibrium-finding problem in the three scenarios mentioned above, and we provide, for each of the three scenarios, an exact algorithm. Finally, we empirically evaluate the scalability of the algorithms in random games and the inefficiency caused by partial or null communication

Know Thyself: Incompetence and Overconfidence

Economic analyses of asymmetric information typically start with the assumption that individuals know more about their own characteristics than outside observers. This assumption implies that individuals can accurately assess their own competence in a given domain. However, individuals can only judge their competence if they are sufficiently competent. The relationship between competence and self-awareness explains a great deal of the overconfidence observed among economic agents. More specifically, overconfidence is inversely proportional to competence. Through a series of experiments and analyses of field data, the link between incompetence and overconfidence is confirmed and its implications for economic theory are explored.overconfidence, competence, asymmetric information, gender, economic experiment

Learning in Networks: a survey

This paper presents a survey of research on learning with a special focus on the structure of interaction between individual entities. The structure is formally modelled as a network: the nodes of the network are individuals while the arcs admit a variety of interpretations (ranging from information channels to social and economic ties). I first examine the nature of learning about optimal actions for a given network architecture. I then discuss learning about optimal links and actions in evolving networks.