Random Rationalizability
Introductory Workshop: Mathematics and Computer Science of Market and Mechanism Design September 11, 2023 - September 15, 2023
Location: SLMath: Eisenbud Auditorium, Atrium
Primary Mathematics Subject Classification
No Primary AMS MSC
Secondary Mathematics Subject Classification
No Secondary AMS MSC
This paper studies the testability of theories when data might be subject to errors. The paper considers a general revealed preference framework for rationalizing data and refuting theories subject to noisy observations. The paper gives several conditions under which features of a model might be estimated or tested using such data, making use of ideas in topological data analysis. Examples including consumer demand and market equilibrium illustrate the main results.