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Geometric Methods for Finite Rational Inattention

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Abstract

We present a geometric approach to the finite Rational Inattention (RI) model, recasting it as a convex optimization problem with reduced dimensionality that is well-suited to numerical methods. We provide an algorithm that outperforms existing RI computation techniques in terms of both speed and accuracy. We also introduce methods to quantify the impact of numerical inaccuracy on the behavioral predictions and to produce robust predictions regarding the most frequently implemented actions.

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  • Roc Armenter & Michèle Müller-Itten & Zachary Strangebye, 2021. "Geometric Methods for Finite Rational Inattention," Working Papers 21-30, Federal Reserve Bank of Philadelphia.
    • Handle: RePEc:fip:fedpwp:93054
    DOI: 10.21799/frbp.wp.2021.30
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    1. Roc Armenter & Michèle Müller-Itten & Zachary Stangebye, 2020. "Rational Inattention via Ignorance Equivalence," Working Papers 20-24, Federal Reserve Bank of Philadelphia.

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    More about this item

    Keywords

    rational inattention; Shannon entropy; information acquisition; learning; consideration sets;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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