Readings

All readings are available for download from the readings folder on Google Drive.

Week 1

• Kahneman & Tversky (1979) — Prospect Theory: An Analysis of Decision under Risk

• Conlisk (1989) — Three Variants on the Allais Example

• Camerer, Ho, and Chong (2004) — A Cognitive Hierarchy Model of Games
• McKelvey & Palfrey (1995) — Quantal Response Equilibria for Normal Form Games
• Wright & Leyton-Brown (2017) — Predicting human behavior in unrepeated, simultaneous-move games

Week 2

• Crawford & Iriberri (2007) — Fatal attraction: Salience, naivete, and sophistication in experimental “hide-and-seek” games
• Burchardi and Penczynski (2014) — Out of your mind: Eliciting individual reasoning in one shot games

• Wright & Leyton-Brown (2019) — Level-0 Models for Predicting Human Behavior in Games

• Kahneman, Knetsch, and Thaler (1986) — Fairness as a Constraint on Profit Seeking: Entitlements in the Market
• Gal et al. (2017) — Which Is the Fairest (Rent Division) of Them All?

Week 3

• Hart & Mas-Colell (2000) — A Simple Adaptive Procedure Leading to Correlated Equilibrium
• Nekipelov, Syrgkanis, and Tardos (2015) — Econometrics for Learning Agents

• Morrill et al. (2021) — Efficient Deviation Types and Learning for Hindsight Rationality in Extensive-Form Games

• Li (2017) — Obviously Strategy-Proof Mechanisms
• Nagel & Saitto (2023) — A Measure of Complexity for Strategy-Proof Mechanisms
• Zinkevich et al. (2007) — Regret Minimization in Games with Incomplete Information

Week 4

• Kiekintveld et al. (2009) — Computing Optimal Randomized Resource Allocations for Massive Security Games
• Deng, Schneider, and Sivan (2019) — Strategizing against No-regret Learners

• Brown et al. (2023) — Is Learning in Games Good for the Learners?

• Benartzi & Thaler (1995) — Myopic Loss Aversion and the Equity Premium Puzzle
• Khaw et al. (2017) — Risk Aversion as a Perceptual Bias
• Rabin (2000) — Risk Aversion and Expected-Utility Theory: A Calibration Theorem

Additional topics

• Bargaining: Camerer, Nave, and Smith (2018): Dynamic Unstructured Bargaining with Private Information: Theory, Experiment, and Outcome Prediction via Machine Learning

• Behavioral Macroeconomics: De Grauwe & Ji (2016): International Correlation of Business Cycles in a Behavioral Macroeconomic Model

• Behavioral Macroeconomics: Wu & Brynjolfsson (2015): The Future of Prediction: How Google Searches Foreshadow Housing Prices and Sales

• Experimental Design: Mason & Suri (2012): Conducting behavioral research on Amazon’s Mechanical Turk

• Experimental Design: Kneeland (2015): Identifying higher-order rationality

• Repeated interactions: Camerer & Ho (1999): Experience-Weighted Attraction Learning in Normal Form Games
• Repeated interactions: Chen, Liu, Chen, and Lee (2011): Bounded memory, inertia, sampling and weighting model for market entry games
• Repeated interactions: Erev, Ert, Plonsky, Cohen, and Cohen, (2017): From Anomalies to Forecasts: Toward a Descriptive Model of Decisions under Risk, under Ambiguity, and from Experience