Sanjit Dhami - Bounded Rationality: Heuristics, Judgment, and Public Policy

Bounded Rationality

Heuristics, Judgment, and Public Policy

Sanjit Dhami and Cass R. Sunstein

The MIT Press

Cambridge, Massachusetts

London, England

2022 Sanjit Dhami and Cass R. Sunstein

All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher.

The MIT Press would like to thank the anonymous peer reviewers who provided comments on drafts of this book. The generous work of academic experts is essential for establishing the authority and quality of our publications. We acknowledge with gratitude the contributions of these otherwise uncredited readers.

Library of Congress Cataloging-in-Publication Data

Names: Dhami, Sanjit S., author. | Sunstein, Cass R., author.

Title: Bounded rationality: heuristics, judgment, and public policy / Sanjit Dhami, Cass R. Sunstein.

Description: [Cambridge, Massachusetts]: The MIT Press, [2022] | Includes bibliographical references and index.

Identifiers: LCCN 2021037261 | ISBN 9780262543705 (paperback) Subjects: LCSH: Rational choice theory. | Rational choice theoryMathematical models. | Mathematical optimization. | Social sciencesMethodology.

Classification: LCC HM495.D44 2022 | DDC 300.1dc23/eng/20211108

LC record available at https://lccn.loc.gov/2021037261

d_r0

1. List of Figures
2. 
   The discount rate in ().
3. 
   Sample size neglect for samples of 10, 100, 1000. Source: Benjamin (2018).
4. 
   Plots of w(p) = e(ln p)0.5 and w(p) = e(ln p)2.
5. 
   The utility function under prospect theory.
6. 
   First period effort levels in different contracts / treatments.
7. 
   Second period effort levels in different contracts / treatments.
8. 
   Schematic description of the risk as feelings thesis.
   Source: Copyright 2001 by the American Psychological Association. Risk as feelings. Loewenstein et al., Ned. Psychological Bulletin, 127(2), March 2001, 267286.
9. 
   A plot of the logistic map for = 4 and for two initial conditions: (a) x0 = 0.2 (thicker curve) and (b) x0 = 0.20001 (dashed curve).
10. 
    A plot of f(x(L)) in ().
11. 
    Simulated plot of the transitions between the two states. The vertical axis is the fraction of players who play L; the horizontal axis is the time (step size 0.05).
12. 
    Simulated values for S(t), I(t), R(t) for the case N = 100, I(0) = 1, c = 0.005, r = 0.05.
13. 
    A plot of the Prelec function for low probabilities.
14. 
    A hypothetical probability weighting function.
    Source: Kahneman & Tversky (1979, p. 282).
15. 
    The composite Prelec weighting function (CPF) in al-Nowaihi and Dhami (2010).
16. 
    Retail level data for Lotto Texas wins. Source: Guryan & Kearney (2008).
17. 
    Does the given alternation rate arise from basketball shots or a coin toss? Source: Ayton & Fischer (2004).
18. 
    The bias-variance dilemma for two different cases.
19. 
    Deadweight loss of a consumption tax under limited attention.
20. 
    Efficiency of sugar taxes in the presence of internalities.
21. List of Tables
22. 
    Percentage of responses consistent with Bayes rule. Sample sizes in parentheses.
23. 
    Fourfold classification of risk under prospect theory.
24. 
    The prisoners dilemma game
25. 
    A two-player, large-dimensional coordination game
26. 
    The prisoners dilemma game
27. 
    Expectations of voters from each political party
28. 
    A prisoners dilemma game
29. 
    A model of neighborhood segregation
30. 
    A simple coordination game
31. 
    Determining which of two foods has more cholesterol

We are grateful to many people for help with this book. Thanks go first to Ali al-Nowaihi, coauthor on the essay out of which this book grew, for many indispensable contributions.

We are grateful to many people who were generous with their time and offered comments, suggestions, and advice on the manuscript that enabled us to effect many improvements. In particular, we would like to thank Junaid Arshad, Gary Charness, Vincent Crawford, Xavier Gabaix, Gerd Gigerenzer, Aditya Goenka, and Teimuraz Gogsadze. Three anonymous reviewers, chosen by MIT Press, provided numerous valuable comments and constructive criticisms, for which we are very grateful. Ali Mehdizadeh and Lia Cattaneo did a thorough job of checking the references for us. We would also like to thank Emily Taber, our editor, for her support and suggestions of many kinds.

Cass is grateful to many collaborators on other projects, who have also taught him much, even if they have not read this book (and have no responsibility for our errors). These are Daniel Kahneman, Sendhil Mullainathan, Lucia Reisch, Tali Sharot, and Richard Thaler. The Program on Behavioral Economics and Public Policy at Harvard Law School provided valuable support. Sanjit would like to acknowledge, without implicating for any errors, Ali al-Nowaihi, Vincent Crawford, Ernst Fehr, Herbert Gintis, and Peter Wakker, who have been generous with their time, support, and wisdom on behavioral economics over many years.

In some places, we have drawn on previous work, and we are grateful for permission to do that. The kernel of the book can be found in Sanjit Dhami, Ali al-Nowaihi, and Cass R. Sunstein, Heuristics and Public Policy: Decision-making under Bounded Rationality, Studies in Microeconomics 7 (Sage Journals, 2019). Parts of chapters 7, 9, 10, and 11 draw from Cass R. Sunstein, Behavioral Science and Public Policy (Cambridge University Press, 2020).

A project of this size always requires enormous support and sacrifice from the family. Sanjit would like to express his gratitude to his parents, Manohar and Baljeet, his wife Shammi, his son Sahaj, and his niece Mehar. Cass would like to thank his wife, Samantha Power, his children Ellyn, Declan, and Rian, and his Labrador retrievers (and constant companions) Snow and Finley.

In this book we have two main goals. The first is to offer a fresh understanding of bounded rationalityof how human beings depart from perfect rationality. This understanding will draw on, and attempt to clarify and formalize, decades of pathbreaking research about judgment and decision-making. The second is to explore the concrete implications of that understanding for public policy and law, with reference to foundational questions about choice, welfare, and freedom.

We aim to promote those goals both for specialists, who might benefit from a discussion of how the existing boundaries might be pushed forward, and for newcomers, who might be interested in the idea of bounded rationality and curious to learn what all the shouting is about. To promote our two goals, we offer a wide range of empirical findings about human behavior and also explore and assess theoretical work that attempts to explain those findings by reference to general models and to offer testable hypotheses. We show that the empirical evidence and the general models have important implications for public policy and law, for how to think about paternalism, and for how to improve human welfare, in part by lengthening lives. At the same time, we emphasize how much remains to be learned.