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Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model
by
McKay, Alisdair
, Matějka, Filip
in
A priori knowledge
/ Attention deficits
/ Beliefs
/ Conditional probabilities
/ Cost functions
/ Decision
/ Decision making
/ Economic models
/ Economic theory
/ Entropy
/ Expected utility
/ Individuals
/ Information
/ Interviews
/ Noise
/ Optimal strategies
/ Pay-off
/ Payoffs
/ Rational choice theory
/ Return on investment
/ State of nature
/ Studies
2015
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Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model
by
McKay, Alisdair
, Matějka, Filip
in
A priori knowledge
/ Attention deficits
/ Beliefs
/ Conditional probabilities
/ Cost functions
/ Decision
/ Decision making
/ Economic models
/ Economic theory
/ Entropy
/ Expected utility
/ Individuals
/ Information
/ Interviews
/ Noise
/ Optimal strategies
/ Pay-off
/ Payoffs
/ Rational choice theory
/ Return on investment
/ State of nature
/ Studies
2015
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Do you wish to request the book?
Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model
by
McKay, Alisdair
, Matějka, Filip
in
A priori knowledge
/ Attention deficits
/ Beliefs
/ Conditional probabilities
/ Cost functions
/ Decision
/ Decision making
/ Economic models
/ Economic theory
/ Entropy
/ Expected utility
/ Individuals
/ Information
/ Interviews
/ Noise
/ Optimal strategies
/ Pay-off
/ Payoffs
/ Rational choice theory
/ Return on investment
/ State of nature
/ Studies
2015
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Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model
Journal Article
Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model
2015
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Overview
Individuals must often choose among discrete actions with imperfect information about their payoffs. Before choosing, they have an opportunity to study the payoffs, but doing so is costly. This creates new choices such as the number of and types of questions to ask. We model these situations using the rational inattention approach to information frictions. We find that the decision maker's optimal strategy results in choosing probabilistically in line with a generalized multinomial logit model, which depends both on the actions' true payoffs as well as on prior beliefs.
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