Details

Subject(s)

• Economics—Psychological aspects [Browse]

Related name

• DellaVigna, Stefano [Browse]
• Laibson, David [Browse]

Series

Handbooks in economics. [More in this series]

Bibliographic references

Includes bibliographical references and index.

Source of description

Description based on publisher supplied metadata and other sources.

Contents

• Front Cover
• Handbook of Behavioral Economics - Foundations and Applications 2
• Copyright
• Contents
• Contributors
• Introduction to the series
• Preface
• 1 Intertemporal choice
• 1 Introduction
• 2 Present-focused preferences: theoretical commonalities
• 2.1 Present-biased preferences
• 2.2 Unitary-self models with temptation
• 2.3 Multiple-self models with simultaneous selves
• 2.4 Objective risks that reduce future value
• 2.5 Models with psychometric distortions
• 2.6 Models of myopia
• 2.7 Overview of models of present-focused preferences
• 2.8 Models that do not generate present-focused preferences
• 3 Empirical regularities and open puzzles
• 3.1 Preferences over monetary receipt timing
• 3.2 Preferences over consumption timing
• 3.3 Preference reversals
• 3.4 Procrastination
• 3.4.1 Explanations for procrastination
• 3.5 Naiveté
• 3.6 The effect of transactions costs
• 3.7 Lack of liquidity on household balance sheets
• 3.8 Commitment
• 3.9 Paternalistic policy and welfare
• 3.10 Preference for improving sequences
• 4 Puzzles without associated empirical regularities
• 4.1 How soon is now?
• 4.2 The role of temptation
• 4.3 Other mechanisms and complementary psychological conceptions
• 4.3.1 Risk
• 4.3.2 Heuristics
• 4.3.3 Other theories
• 4.4 Stability and domain generality
• 4.5 Malleability and self-management
• 4.6 Retirement saving adequacy
• 5 Conclusion
• References
• 2 Errors in probabilistic reasoning and judgment biases
• 2 Biased beliefs about random sequences
• 2.1 The gambler's fallacy and the Law of Small Numbers
• 2.2 The hot-hand bias
• 2.3 Additional biases in beliefs about random sequences
• 3 Biased beliefs about sampling distributions
• 3.1 Partition dependence
• 3.2 Sample-size neglect and Non-Belief in the Law of Large Numbers.
• 3.3 Sampling-distribution-tails diminishing sensitivity
• 3.4 Overweighting the mean and the fallacy of large numbers
• 3.5 Sampling-distribution beliefs for small samples
• 3.6 Summary and comparison of sequence beliefs with sampling-distribution beliefs
• 4 Evidence on belief updating
• 4.1 Conceptual framework
• 4.2 Evidence from simultaneous samples
• 4.3 Evidence from sequential samples
• 5 Theories of biased inference
• 5.1 Biased sampling-distribution beliefs
• 5.2 Conservatism bias
• 5.3 Extreme-belief aversion
• 5.4 Summary
• 6 Base-rate neglect
• 7 The representativeness heuristic
• 7.1 Representativeness
• 7.2 The strength-versus-weight theory of biased updating
• 7.3 Economic models of representativeness
• 7.4 Modeling representativeness versus speci c biases
• 8 Prior-biased inference
• 8.1 Conceptual framework
• 8.2 Evidence and models
• 9 Preference-biased inference
• 9.1 Conceptual framework
• 9.2 Evidence and models
• 10 Discussion
• 10.1 When do people update too much or too little?
• 10.2 Modeling challenges
• 10.3 Generalizability from the lab to the eld
• 10.4 Connecting with other areas of economics
• 10.5 Some possible directions for future research
• 3 Errors in strategic reasoning
• 1.1 Game-theory background
• 1.2 Behavioral-game-theory background
• 1.3 Chapter aims
• 1.4 Exclusions
• 1.5 Modeling approaches
• 2 Setup and taxonomy of errors
• 3 Mispredicting actions
• 3.1 Lab evidence
• 3.1.1 Reasoning about others' rationality
• 3.2 Field evidence
• 3.3 Models
• 3.3.1 The Level-k model
• 3.3.2 Self-con rming equilibrium
• 3.3.3 Analogy-based-expectations equilibrium
• 3.3.4 Comparing Level k to ABEE in a dynamic game
• 4 Underinference and misinference
• 4.1 Folk wisdom on underinference
• 4.2 Lab evidence
• 4.2.1 Bilateral trade.
• 4.2.2 Auctions
• 4.2.3 Social learning
• 4.2.4 Voting
• 4.3 Field evidence
• 4.4 Models
• 4.4.1 Fully cursed equilibrium
• 4.4.2 Analogy-based-expectations equilibrium
• 4.4.3 Partially cursed equilibrium
• 4.4.4 Behavioral equilibrium
• 4.5 Social versus private inference
• 4.6 Learning
• 4.7 Implications
• 4.8 Misinference
• 4.8.1 Observational learning
• 4.8.2 Self-con rming equilibrium
• 5 Failure to best respond
• 5.1 Epsilon equilibrium
• 5.2 Quantal-response equilibrium
• 5.3 Applications of QRE
• 5.4 Failure to understand payoffs
• 6 From horserace to foxtrot: applying solution concepts
• 7 Conclusion
• 4 Behavioral inattention
• 2 A simple framework for modeling attention
• 2.1 An introduction: Anchoring and adjustment via Gaussian signal extraction
• 2.2 Models with deterministic attention and action
• 2.3 Unifying behavioral biases: Much of behavioral economics may re ect a form of inattention
• 2.3.1 Inattention to true prices and shrouding of add-on costs
• 2.3.2 Inattention to taxes
• 2.3.3 Nominal illusion
• 2.3.4 Hyperbolic discounting: Inattention to the future
• 2.3.5 When will we see overreaction vs. underreaction?
• 2.3.6 Prospect theory: Inattention to the true probability
• 2.3.7 Projection bias: Inattention to future circumstances by anchoring on present circumstances
• 2.3.8 Coarse probabilities and partition dependence
• 2.3.9 Base-rate neglect: Inattention to the base rate
• 2.3.10 Correlation neglect
• 2.3.11 Insensitivity to sample size
• 2.3.12 Insensitivity to predictability/misconceptions of regression to the mean/illusion of validity: Inattention to randomness and noise
• 2.3.13 Overcon dence: Inattention to my true ability
• 2.3.14 Cursedness: Inattention to the conditional probability
• 2.3.15 Left-digit bias: Inattention to non-leading digits.
• 2.3.16 Exponential growth bias
• 2.3.17 Taking stock of these examples
• 2.4 Psychological underpinnings
• 2.4.1 Conscious versus unconscious attention
• 2.4.2 Reliance on defaults
• 2.4.3 Neuroscience: The neural correlates of "mental cost" and "limited attention
• 2.4.4 Other themes
• 3 Measuring attention: Methods and ndings
• 3.1 Measuring attention: Methods
• 3.1.1 Measuring inattention via deviation from an optimal action
• 3.1.2 Deviations from Slutsky symmetry
• 3.1.3 Process tracking: Time on task, Mouselab, eye tracking, pupil dilatation, etc.
• 3.1.4 Surveys
• 3.1.5 Impact of reminders, advice
• 3.2 Measuring attention: Findings
• 3.2.1 Inattention to taxes
• 3.2.2 Shrouded attributes
• 3.2.3 Inattention in health plan choices
• 3.2.4 Inattention to health consequences
• 3.2.5 People use rounded numbers
• 3.2.6 Do people account for the net present value of future costs and bene ts?
• 3.2.7 Inattention in nance
• 3.2.8 Evidence of reaction to macro news with a lag
• 3.2.9 Evidence on level-k thinking in games
• 3.3 Attention across stakes and studies
• 3.4 Different meanings of "attention
• 4 Models of endogenous attention: Deterministic action
• 4.1 Paying more attention to more important variables: The sparsity model
• 4.1.1 The sparse max without constraints
• 4.1.2 Sparse max allowing for constraints
• 4.2 Proportional thinking: The salience model of Bordalo, Gennaioli, Shleifer
• 4.2.1 The salience framework in the absence of uncertainty
• 4.2.2 Salience and choice over lotteries
• 4.3 Other themes
• 4.3.1 Attention to various time dimensions: "Focusing
• 4.3.2 Motivated attention
• 4.3.3 Other decision-theoretic models of bounded rationality
• 4.4 Limitation of these models
• 5 A behavioral update of basic microeconomics: Consumer theory, Arrow-Debreu
• 5.1 Textbook consumer theory.
• 5.1.1 Basic consumer theory: Marshallian demand
• 5.1.2 Asymmetric Slutsky matrix, and inferring attention from choice data, and nominal illusion
• 5.2 Textbook competitive equilibrium theory
• 5.2.1 First and second welfare theorems: (In)ef ciency of equilibrium
• 5.2.2 Excess volatility of prices in a behavioral economy
• 5.3 What is robust in basic microeconomics?
• 6 Models with stochastic attention and choice of precision
• 6.1 Bayesian models with choice of information
• 6.2 Entropy-based inattention: "Rational inattention
• 6.2.1 Information theory: A crash course
• 6.2.2 Using Shannon entropy as a measure of cost
• 6.3 Random choice via limited attention
• 6.3.1 Limited attention as noise in perception: Classic perspective
• 6.3.2 Random choice via entropy penalty
• 7 Allocation of attention over time
• 7.1 Generating sluggishness: Sticky action, sticky information, and habits
• 7.1.1 Sticky action and sticky information
• 7.1.2 Habit formation generates inertia
• 7.1.3 Adjustment costs generate inertia
• 7.1.4 Observable difference between inattention vs. habits/adjustment costs: Source-speci c inattention
• 7.1.5 Dynamic default value
• 7.2 Optimal dynamic inattention
• 7.3 Other ways to generate dynamic adjustment
• 7.3.1 Procrastination
• 7.3.2 Unintentional inattention
• 7.3.3 Slow accumulation of information with entropy-based cost
• 7.4 Behavioral macroeconomics
• 8 Open questions and conclusion
• A Further derivations and mathematical complements
• A.1 Further derivations
• A.2 Mathematical complements
• B Data methodology
• 5 Behavioral development economics
• 2 High rates of return without rapid growth
• 2.1 The Euler equation puzzle
• 2.2 Present bias
• 2.3 Reference-dependent preferences
• 2.4 Other behavioral factors
• 3 Health.
• 3.1 Underinvestment in preventive health.

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ISBN

• 9780444633965
• 0444633960

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