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What happens when agents can choose their information at a cost? What kinds of cost functions lead to behavior typically observed in economics and psychology experiments?
Agents are forward-looking and incorporate their future behavior into today’s decisions. This is captured by the Bellman equation. We break this axiomatically into preference for flexibility and rational expectations.
How do people choose between risky prospects? I discuss the model of random expected utility and its axiomatic characterization. Other models are discussed too, including models of nonexpected utility and models with additive shocks.
Dynamic discrete choice models, such as dynamic logit, are used extensively in industrial organization. This chapter exposits various classes of these models and studies their properties.
Sometimes agents don’t pay attention to all the items on the menu but restrict themselves to what is called a consideration set. We review a number of classical model of consideration sets.
Are fast choices better or worse than slow ones? This chapter explores models of stopping times, including sequential sampling models from statistics and drift-diffusion models from cognitive science.
Bayesian modeling is pervasive in economics and cognitive science. I formalize a general notion of a Bayes model and illustrate it using a variety of examples.
Observed choices are random in psychological experiments on perception and in economics experiments on choice. I discuss a number of possible explanations and introduce the random utility model.
Agents typically make choices in succession. This may lead to situations where past choices seem to influence future choices, but often such a correlation is spurious and goes away if the analyst has as much information as the agent.
I discuss a number of models widely used in the literature, including logit, mixed logit, Fechnerian utility, and perturbed utility. Axiomatic underpinnings of every model are discussed.
In discrete-choice econometrics, the alternatives are characterized by attributes and choice probabilities are a function of those attributes. Classical models are reviewed.