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1
Introduction
2
Statistical Approach
3
SelfSelection Bias
4
Imitation Learning
5
Selective Reporting
6
Market Disequilibrium
7
Nonparametric Setting
8
Summary
9
Applications
10
Linear Models
11
Comparison
12
Assumptions
13
Selector Function
14
Results
15
Lucky Problem
16
Gradient Descent
17
Conclusion
Description:
Explore the challenges and complexities of learning from strategically-influenced data in this thought-provoking lecture. Delve into the concept of self-selection bias and its impact on statistical models, using the analogy of fishermen to illustrate how data collection can miss crucial information. Examine recent progress in addressing econometric challenges, including estimating linear models under self-selection bias and identifying non-parametric auction models. Discover the implications of this research for various fields, from understanding student and employee performance to learning from expert demonstrations and analyzing strategic behavior in markets. Gain insights into potential solutions and open directions for future investigation in this critical area of study.

What Does It Take to Be a Good Fisherman?

Simons Institute
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