Part 1: A Selected History of Quantitative Causal Inference
The Extraordinary Role of Data Workers and Data Theorists at Princeton and Harvard
This is Part 1 in a three part substack that I am calling “A Selected History of Quantitative Causal Inference”. I had previously had all of it in one super long scroll, but I think it’s better to break it up into three parts so it’s more digestible. This first part discusses the philosophical and statistical origins of the potential outcomes model, as well as its historical link to the randomized experiment. Some of you may know this by heart, but I still think it’s a good essay to give to new students who are learning causal inference for the first time, particularly if they need something that they can sink their teeth into as they begin working with terms and concepts and models that are perhaps a little esoteric to them.
What are stories and why do we tell them? And what is a true story or are stories ever true? What even is truth? I wonder this a lot when I consider that a hundred people could watch the same event and all come away reporting one hundred different thi…
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