Subjective Dynamic Information Constraints

Abstract

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.