Final Part 3: A Selected History of Quantitative Causal Inference

The Extraordinary Role of Data Workers and Data Theorists at Princeton and Harvard

In the previous part 1 in this series, I discussed the rise of the potential outcomes model with Neyman, the realization that physical randomization solved the fundamental problem of causal inference from Fisher. In Part 2, I discussed the role that Princeton’s Industrial Relations Section had in shifts made within empirical microeconomics by highlighti…