Philipp Sadowski

Ashamed to be selfish

We study a two-stage choice problem, where alternatives are allocations between the decision maker (DM) and a passive recipient. The recipient observes choice behavior in stage two, while stage one choice is unobserved. Choosing selfishly in stage two, in the face of a fairer available alternative, may inflict shame on DM. DM has preferences over sets of alternatives that represent period two choices. We axiomatize a representation that identifies DMs selfish ranking, her norm of fairness and shame. Altruism is the most prominent motive that can explain non-selfish choice. We identify a condition under which shame to be selfish can mimic altruism, when only stage-two choice is observed by the experimenter. An additional condition implies that the norm of fairness can be characterized as the Nash solution of a bargaining game induced by the second-stage choice problem. The representation is generalized to allow for finitely many recipients and applied to explain a social decision makers incentive for obfuscation.

A Theory of Subjective Learning

We study an individual who faces a dynamic decision problem in which the process of information arrival is unobserved by the analyst. We derive two utility representations of preferences over menus of acts that capture the individual’s uncertainty about his future beliefs. The most general representation identifies a unique probability distribution over the set of posteriors that the decision maker might face at the time of choosing from the menu. We use this representation to characterize a notion of “more preference for flexibility” via a subjective analogue of Blackwell’s (1951, 1953) comparisons of experiments. A more specialized representation uniquely identifies information as a partition of the state space. This result allows us to compare individuals who expect to learn differently, even if they do not agree on their prior beliefs. We conclude by extending the basic model to accommodate an individual who expects to learn gradually over time by means of a subjective filtration.

A Theory of Subjective Learning, Second Version

We study an individual who faces a dynamic decision problem in which the process of information arrival is unobserved by the analyst. We elicit subjective information directly from choice behavior by deriving two utility representations of preferences over menus of acts. The most general representation identifies a unique probability distribution over the set of posteriors that the decision maker might face at the time of choosing from the menu. We use this representation to characterize a notion of †more preference for flexibility†via a subjective analogue of Blackwell’s (1951, 1953) comparisons of experiments. A more specialized representation uniquely identifies information as a partition of the state space. This result allows us to compare individuals who expect to learn differently, even if they do not agree on their prior beliefs. On the extended domain of dated-menus, we show how to accommodate an individual who expects to learn gradually over time by means of a subjective filtration.

A Theory of Subjective Learning, Third Version

We study an individual who faces a dynamic decision problem in which the process of information arrival is unobserved by the analyst. We elicit subjective information directly from choice behavior by deriving two utility representations of preferences over menus of acts. One representation uniquely identifies information as a probability measure over posteriors and the other identifies information as a partition of the state space. We compare individuals who expect to learn differently in terms of their preference for flexibility. On the extended domain of dated-menus, we show how to accommodate gradual learning over time by means of a subjective filtration.

Generalized Partition and Subjective Filtration

We study an individual who faces a dynamic decision problem in which the process of information arrival is unobserved by the analyst, and hence should be identified from observed choice data. An information structure is objectively describable if signals correspond to events of the objective state space. We derive a representation of preferences over menus of acts that captures the behavior of a Bayesian decision maker who expects to receive such signals. The class of information structures that can support such a representation generalizes the notion of a partition of the state space. The representation allows us to compare individuals in terms of the preciseness of their information structures without requiring that they share the same prior beliefs. We apply the model to study an individual who anticipates gradual resolution of uncertainty over time. Both the filtration (the timing of information arrival with the sequence of partitions it induces) and prior beliefs are uniquely identified.

Foundations for Cooperation in the Prisoners’ Dilemma

We provide axiomatic foundations for a simple model of play in the prisoners’ dilemma. The model accommodates cooperation and suggests that players behave as if their expectations about their opponents’ behavior vary with their own choice. We refer to this nonstandard updating as magical thinking. The degree to which players exhibit magical thinking may be heterogeneous in the population and is captured by a uniquely identified parameter for each player. Further, it is as if all players perceive these parameters to be i.i.d. draws from a common distribution. The model’s identification allows for tractable comparative statics.

Inertial Behavior and Generalized Partition

We call behavior inertial if it does not react to the apparent arrival of relevant information. In a context where the precise information content of signals is subjective, we formulate an axiom that captures inertial behavior, and provide a representation that explains such behavior as that of a rational decision maker who perceives a particular type of information structure, which we call a generalized partition. We characterize the learning processes that can be described by a generalized partition. We proceed to assume that there is a true underlying information structure that may not be a generalized partition, and investigate different channels that may lead the decision maker to nonetheless perceive a generalized partition (and thus to display inertial behavior): A cognitive bias referred to as cognitive inertia and a bound on rationality which we term shortsightedness.

Subjective Dynamic Information Constraints

We axiomatize a new class of recursive dynamic models that capture subjective constraints on the amount of information a decision maker can obtain, pay attention to, or absorb, via a Markov Decision Process for Information Choice (MIC). An MIC is a subjective decision process that specifies what type of information about the payoff-relevant state is feasible in the current period, and how the choice of what to learn now affects what can be learned in the future. The constraint imposed by the MIC is identified from choice behavior up to a recursive extension of Blackwell dominance. All the other parameters of the model, namely the anticipated evolution of the payoff-relevant state, state dependent consumption utilities, and the discount factor are also uniquely identified.

Randomly Evolving Tastes and Delayed Commitment

We consider a decision maker with randomly evolving tastes who faces dynamic decision situations that involve intertemporal tradeoffs, such as those in consumption savings problems. We axiomatize a recursive representation of choice that features uncertain consumption utilities, which evolve according to a subjective Markov process. The parameters of the representation, which are the subjective Markov process governing the evolution of utilities, and the discount factor, are uniquely identified from behavior. We relate the correlation of tastes over time and the desire to delay commitment to future consumption.

Preferences with Taste Shock Representations: Price Volatility and the Liquidity Premium

If price volatility is caused in some part by taste shocks, then it should be positively correlated with the liquidity premium. Our argument is based on Krishna and Sadowski (2014), who provide foundations for a representation of dynamic choice with taste shocks, and show that volatility in tastes corresponds to a desire to maintain flexibility. To formally connect volatile tastes to price volatility and preference for flexibility to the liquidity premium, we analyze a modified simple Lucas tree economy, where the representative agent is uncertain about his degree of future risk aversion, and where the productive asset cannot be traded in every period, while rights to output can. We show that a representative agent with a higher degree of uncertainty about his future risk aversion implies a higher liquidity premium (i.e., a lower price for the illiquid asset) and more price volatility.