Temptation with uncertain normative preferences

We model a decision maker who anticipates being affected by temptation but is also uncertain about what is normatively best. Our model is an extended version of Gul and Pesendorfer's (2001) where there are three time periods: in the ex-ante period the agent chooses a set of menus, in the interim period she chooses a menu from this set, and in the final period she chooses from the menu. We posit axioms from the ex-ante perspective. Our main axiom on preference states that the agent prefers to have the option to commit in the interim period. Our representation is a generalization of Dekel et al.'s (2009) and identifies the agent's multiple normative preferences and multiple temptations. We also characterize the uncertain normative preference analogue to the representation in Stovall (2010). Finally, we characterize the special case where normative preference is not uncertain. This special case allows us to uniquely identify the representations of Dekel et al. (2009) and Stovall (2010)

The Price of Flexibility: Towards a Theory of Thinking Aversion

The goal of this paper is to model an agent who dislikes large choice sets because of the "cost of thinking" involved in choosing from them. We take as a primitive a preference relation over lotteries of menus and impose novel axioms that allow us to separately identify the genuine preference over the content of menus, and the cost of choosing from them. Using this, we formally define the notion of thinking aversion, much in line with the definitions of risk or ambiguity aversion. We represent such preference as the difference between a monotone and affine evaluation of the content of the set and an anticipated thinking cost function that assigns to each set a thinking cost. We further extend this characterization to the case of monotonicity of the genuine rank and introduce a measure of comparative thinking aversion. Finally, we propose behavioral axioms that guarantee that the cost of thinking can be represented as the sum of the cost to find the optimal choice in a set and the cost to find out which is the optimal choice.Cost of Thinking, Contemplation Cost, Bounded Rationality, Preference Over Menus, Preference for Flexibility, Choice overload

Temptation–Driven Preferences

What behavior can be explained using the hypothesis that the agent faces temptation but is otherwise a “standard rational agent”? In earlier work, Gul–Pesendorfer [2001] use a set betweenness axiom to restrict the set of preferences considered by Dekel, Lipman, and Rustichini [2001] to those explainable via temptation. We argue that set betweenness rules out plausible and interesting forms of temptation including some which may be important in applications. We propose a pair of alternative axioms called DFC, desire for commitment, and AIC, approximate improvements are chosen. DFC characterizes temptation as situations where given any set of alternatives, the agent prefers committing herself to some particular item from the set rather than leaving herself the flexibility of choosing later. AIC is based on the idea that if adding an option to a menu improves the menu, it is because that option is chosen under some circumstances. From this interpretation, the axiom concludes that if an improvement is worse (as a commitment) than some commitment from the menu, then the best commitment from the menu is strictly preferred to facing the menu. We show that these axioms characterize a natural generalization of the Gul–Pesendorfer representation.

Freedom, Opportunity and Wellbeing

This paper reexamines key results from the measurement of opportunity freedom, or the extent to which a set of options offers a decision maker real opportunities to achieve. Three cases are investigated: no preferences, a single preference, and plural preferences. The three co the cardinality relation, the indirect utility relation, and the effective freedom relation variations are considered within a common axiomatic framework. Special attention is given to representations of freedom rankings, with the goal of providing practical approaches for measuring opportunity freedom and the extent of capabilities.

Dynamic Random Utility

Under dynamic random utility, an agent (or population of agents) solves a dynamic decision problem subject to evolving private information. We analyze the fully general and non-parametric model, axiomatically characterizing the implied dynamic stochastic choice behavior. A key new feature relative to static or i.i.d. versions of the model is that when private information displays serial correlation, choices appear history dependent: different sequences of past choices reflect different private information of the agent, and hence typically lead to different distributions of current choices. Our axiomatization imposes discipline on the form of history dependence that can arise under arbitrary serial correlation. Dynamic stochastic choice data lets us distinguish central models that coincide in static domains, in particular private information in the form of utility shocks vs. learning, and to study inherently dynamic phenomena such as choice persistence. We relate our model to specifications of utility shocks widely used in empirical work, highlighting new modeling tradeoffs in the dynamic discrete choice literature. Finally, we extend our characterization to allow past consumption to directly affect the agent’s utility process, accommodating models of habit formation and experimentation

Conditional Preference for Flexibility: Eliciting Beliefs from Behavior

Following Kreps (1979), we consider a decision maker with uncertain beliefs about her own future taste. This uncertainty leaves the decision maker with preference for flexibility: When choosing among menus containing alternatives for future choice, she weakly prefers larger menus. Existing representations accommodating this choice pattern cannot distinguish tastes (indexed by a subjective state space) and beliefs (a probability measure over the subjective states) as different concepts, making it impossible to relate parameters of the representation to choice behavior. We allow choice among menus to depend on exogenous states, interpreted as information. Our axioms yield a representation that uniquely identifies beliefs, provided the impact of information on choice is rich. The result is suggested as a choice theoretic foundation for the assumption, commonly made in the incomplete contracting literature, that contracting parties, who know each other's ranking of contracts, also share beliefs about each others future tastes in the face of unforeseen contingencies.Preference for Flexibility; Uniqueness; Contracts; Subjective Uncertainty

Dynamic Random Utility

We provide an axiomatic analysis of dynamic random utility, characterizing the stochastic choice behavior of agents who solve dynamic decision problems by maximizing some stochastic process (U_t) of utilities. We show first that even when (U_t) is arbitrary, dynamic random utility imposes new testable restrictions on how behavior across periods is related, over and above period-by-period analogs of the static random utility axioms: An important feature of dynamic random utility is that behavior may appear history dependent, because past choices reveal information about agents’ past utilities and (U_t) may be serially correlated; however, our key new axioms highlight that the model entails specific limits on the form of history dependence that can arise. Second, we show that when agents’ choices today influence their menu tomorrow (e.g., in consumption-savings or stopping problems), imposing natural Bayesian rationality axioms restricts the form of randomness that (U_t) can display. By contrast, a specification of utility shocks that is widely used in empirical work violates these restrictions, leading to behavior that may display a negative option value and can produce biased parameter estimates. Finally, dynamic stochastic choice data allows us to characterize important special cases of random utility—in particular, learning and taste persistence—that on static domains are indistinguishable from the general model