Persuasion,binary choice,and the costs of dishonesty

We study the strategic interaction between a decision maker who needs to take a binary decision but is uncertain about relevant facts and an informed expert who can send a message to the decision maker but has a preference over the decision. We show that the probability that the expert can persuade the decision maker to take the expert’s preferred decision is a hump-shaped function of his costs of sending dishonest messages.     

Induced Preferences, Nonadditive Beliefs, and Multiple Priors

We study a decision maker who follows the Savage axioms. We show that if he or she is able to take unobservable actions that influence the probabilities of outcomes, then it can appear to an outsider as if his or her subjective probabilities are nonadditive. Implications for multiperiod decision are explored. We extend the model to include a second individual who is also able to take a hidden action. We show that this may induce uncertainty-averse preferences over some class of acts, even if the second individual acts to help the decision maker with high probability.     

Choosing the two finalists

This paper studies a decision maker who for each choice set selects a subset of (at most) two alternatives. We axiomatize three types of procedures: (i) The top two: the decision maker has in mind an ordering and chooses the two maximal alternatives. (ii) The two extremes: the decision maker has in mind an ordering and chooses the maximal and the minimal alternatives. (iii) The top and the top: the decision maker has in mind two orderings and he chooses the maximal element from each.     

PARTISAN ADVOCATES

This paper studies the problem of an uninformed decision maker who acquires expert advice prior to making a decision. I show that it is less costly to hire partisan agents than impartial agents, especially under advocacy, and that the decision maker prefers partisan advocacy to other forms of institutions. I also extend the literature, originating with Dewatripont and Tirole ( 1999 ), to a setting with contracts that condition on information provided and not just the decision made.     

Anti-herding and strategic consultation

In this paper I analyze how careerist decision makers aggregate and use information provided by others. I find that decision makers who are motivated by reputation concerns tend to ‘anti-herding’, i.e., they excessively contradict public information such as the prior or others’ recommendations. I also find that some decision makers may deliberately act unilaterally and not consult advisers although advice is costless. Moreover, advisers to the decision maker may not report their information truthfully. Even if the advisers care only about the outcome, they bias their recommendation since they anticipate inefficient anti-herding behavior by the decision maker.     

Payoff Assessments without Probabilities: A Simple Dynamic Model of Choice

We develop a model which reflects the tendency of people to simplify the decision problems they face. The decision maker chooses among alternate strategies only on the basis of the payoff she assesses she would obtain from them, and these assessments do not explicitly take into account her subjective judgements regarding the likelihood of alternate states of the world. At each stage, the decision maker chooses the strategy that she assesses to give the highest payoff. She updates her assessments adaptively. We show that such behavior leads to maxmin choices. We also consider the decision maker who experiences shocks. Journal of Economic Literature Classification Numbers: C7, D8.     

Aggregation of expert opinions

Conflicts of interest arise between a decision maker and agents who have information pertinent to the problem because of differences in their preferences over outcomes. We investigate how the decision maker can extract the information by distorting the decisions that will be taken. We show that only slight distortions will be necessary when agents' signals are sufficiently accurate or when the number of informed agents becomes large. We argue that the particular mechanisms analyzed are substantially less demanding informationally than those typically employed in implementation and virtual implementation. Further, the mechanisms are immune to manipulation by small groups of agents.     

New product launch: herd seeking or herd preventing?

A decision maker offers a new product to a number of potential adopers. He does not know the value of the product, but adopers receive some private information about it. We study how the decision maker may influence learning among adopers by manipulaing the launch sequence when both the decision maker and adopers can learn about the value of the product from previous adoption decisions. The conditions under which the decision maker prefers a sequential launch to a simultaneous launch depend on adopers?? prior beliefs about the value of the product and adoption costs. We derive the decision maker??s optimal launch sequence and study how it endogenizes informational herding.     

Aggregation of multiple prior opinions

Experts are asked to provide their advice in a situation of uncertainty. They adopt the decision maker?s utility function, but each has a potentially different set of prior probabilities, and so does the decision maker. The decision maker and the experts maximize the minimal expected utility with respect to their sets of priors. We show that a natural Pareto condition is equivalent to the existence of a set Λ of probability vectors over the experts, interpreted as possible allocations of weights to the experts, such that (i) the decision maker?s set of priors is precisely all the weighted-averages of priors, where an expert?s prior is taken from her set and the weight vector is taken from Λ; (ii) the decision maker?s valuation of an act is the minimal weighted valuation, over all weight vectors in Λ, of the experts? valuations.     

Prior symmetry, similarity-based reasoning, and endogenous categorization

This paper presents a rational theory of categorization and similarity-based reasoning. I study a model of sequential learning in which the decision maker infers unknown properties of an object from information about other objects. The decision maker may use the following heuristics: divide objects into categories with similar properties and predict that a member of a category has a property if some other member of this category has this property. The environment is symmetric: the decision maker has no reason to believe that the objects and properties are a priori different. In symmetric environments, categorization is an optimal solution to an inductive inference problem. Any optimal solution looks as if the decision maker categorizes. Various experimental observations about similarity-based reasoning coincide with the optimal behavior in my model.     

A Bayesian Approach to Uncertainty Aversion

The Ellsberg paradox demonstrates that people's beliefs over uncertain events might not be representable by subjective probability. We show that if a risk averse decision maker, who has a well defined Bayesian prior, perceives an Ellsberg type decision problem as possibly composed of a bundle of several positively correlated problems, she will be uncertainty averse. We generalize this argument and derive sufficient conditions for uncertainty aversion.     

Confidence and decision

Many real-life decisions have to be taken on the basis of probability judgements of which the decision maker is not entirely sure. This paper develops a decision rule for taking such decisions, which incorporates the decision makerʼs confidence in his probability judgements according to the following maxim: the larger the stakes involved in a decision, the more confidence is required in a probability judgement for it to play a role in the decision. A formal representation of the decision makerʼs confidence is proposed and used to formulate a family of decision models conforming to this maxim. A natural member of this family is studied in detail. It is structurally simpler than other recent models of decision under uncertainty, which may make it easier to apply to practical decisions, whilst being axiomatically sound, permitting the separation of beliefs and tastes, and allowing comparative statics analysis of attitudes to choosing in the absence of confidence.     

On the Composition of Committees

This article is concerned with the role of committees in collectivedecision making processes in a world where agents must be motivatedto collect information. Committees improve the quality of decisionmaking by providing information and by coordinating the collectionof information. We address two types of questions. First, howdoes the composition of a committee affect final decisions?Second, what is the optimal composition of a committee fromthe decision maker's point of view? As to the latter question,we show that the cost of information collection plays an importantrole. If this cost is low, then the preferences of the committeemembers should be aligned to those of the decision maker. Memberswith similar preferences as the decision maker collect the properpieces of information. Moreover, manipulation of informationdoes not occur if the preferences of the decision maker andthe members are consonant. If the cost of searching is high,then the committee should be composed of members with polarizedpreferences. Outliers have a strong incentive to search forinformation.     

Strategic argumentation

I analyze a game between an uninformed decision maker and a possibly biased expert. The expert receives a set of arguments, and each argument favors one of two alternatives. He can disclose each argument credibly, but cannot prove whether he has disclosed everything. In all equilibria, the biased expert sends messages containing arguments both for and against his preferred alternative. However, the decision maker is not influenced by the unfavorable arguments revealed by the biased expert. The latter is able to convince the decision maker to choose the biased expert?s preferred alternative only if he reveals sufficiently many favorable arguments.     

Information transmission when the sender''s preferences are uncertain

In deciding on the magnitude of a certain action (say, investment), a decision maker relies on the report of an informed and interested expert who can suppress favorable information. The main departure from the related literature is that the decision maker is uncertain as to whether the expert is of a type that wants to minimize the magnitude of the action or to maximize it. The unique equilibrium outcome is fully characterized by a threshold level of favorable information. If the information is more favorable than that threshold level and if the expert is of the type that wants to maximize the magnitude of the action, the information is fully revealed. In all other cases, the expert report less favorable information and the equilibrium inference is that, in expectation, the actual information is just as favorable as the threshold level.     

Measuring Inequalities without Linearity in Envy: Choquet Integrals for Symmetric Capacities

The (generalized) Gini indices rely on the social welfare function of a decision maker who behaves in accordance with Yaari's model, with a function f that transforms frequencies. This SWF can also be represented as the weighted sum of the welfare of all the possible coalitions in the society, where the welfare of a coalition is defined as the income of the worst-off member of that coalition. We provide a set of axioms (Ak) and prove that the three following statements are equivalent: (i) the decision maker respects (Ak), (ii) f is a polynomial of degree k, (iii) the weight of all coalitions with more than k members is equal to zero. Journal of Economic Literature Classification Number: D63.     

Minimax regret with imperfect ex-post knowledge of the state

We consider decision problems under complete ignorance and extend the minimax regret principle to situations where, after taking an action, the decision maker does not necessarily learn the state of the world. For example, if the decision maker only learns what the outcome is, then all she knows is that the actual state is one of the (possibly several) states that yield the observed outcome under the chosen action. We refer to this situation as imperfect ex-post information. We show that, given a choice between more information and less information, the decision maker prefers the latter. We also extend the framework to encompass the possibility of less than the extreme degree of pessimism that characterizes the minimax regret criterion.     

The value of a stochastic information structure

Upon observing a signal, a Bayesian decision maker updates her probability distribution over the state space, chooses an action, and receives a payoff that depends on the state and the action taken. An information structure determines the set of possible signals and the probability of each signal given a state. For a fixed decision problem, the value of an information structure is the maximal expected utility that the decision maker can get when the observed signals are governed by this structure. Thus, every decision problem induces a preference order over information structures according to their value. We characterize preference orders that can be obtained in this way. We also characterize the functions defined over information structures that measure their value.     

Inter-temporal choices with temporal reference dependence

I develop an intertemporal choice model for rational deviators whose preferences depend not only on their actual consumption but also on comparison to their beliefs about the optimal consumption. The standard decision maker is loss averse with respect to this belief-dependent reference point. When psychologically weighted loss aversion is low, a decision maker deviates from the standard intertemporal choice behavior and over-consumption, as well as the alternative possibility of under-consumption can be rationalized. When the decision maker has time-varying degrees of loss aversion, he re-optimizes the consumption plan through adjusted beliefs as subsequent selves realize that past decision for the present period is no longer optimal. In the dynamic model, I solve for consistent intertemporal optimization rules by which a dynamic deviator should meet rational intertemporal consistency at each point in time. Finally, I demonstrate that the dynamic reference dependent model can solve a puzzling feature in lifecycle consumption data.     

Financial Decision Making and Cognition in a Family Context

In this paper, we studied the association of cognitive traits and in particular numeracy of both spouses on financial outcomes of the family. We found significant effects, particularly for numeracy for financial and non-financial respondents alike, but much larger effects for the financial decision maker in the family. We also examined who makes these financial decisions in the family and why. Once again, cognitive traits such as numeracy were an important component of that decision with larger effects of numeracy for husbands compared to wives.