That mistakes are made is clear. What is meant by that is not. Measuring whatever might be meant and scientifically studying it is therefore even more challenging.
These lectures introduce an interdisciplinary science of mistakes to cut the Gordian knot. The key building blocks are model constructs drawn from the economic tradition, methods of measurement drawn from the psychometric tradition, and analytic methods drawn from economic theory.
Contents:
Overview
The Operational Model:
Operationalizing the Blackwell Model
Costly Information Representations and Attention Switches
All Rationalizing Cost Functions
Revealed Bayesian Learning: A Full Characterization
Full Recovery of Costs and Welfare
Comparison of Revealed Experiments
Posterior-Separable Cost Functions and Behavior
The Shannon Model of Rational Inattention:
Solving the Shannon Model
Optimal Consideration Sets and the Invariant Likelihood Ratio Hyperplanes
Equilibrium, Exchangeability, and Symmetry
Applications:
Modeling Machine Learning
Teaching, Testing, and Learning
Management Skills and Productive Efficiency
Decision-Making Skills, Job Transitions, and Income
Communication Policies
Readership: For economists, psychologists, and data scientists interested in a common analytic framework for understanding mistakes. The book is suitable for advanced undergraduates, graduate students, and researchers in economics, psychology and data science. Key Features:
Presents a coherent scientific approach to understanding mistakes that is interdisciplinary in nature