Isolation in the construction of natural experiments
Jos\'e R. Zubizarreta, Dylan S. Small, Paul R. Rosenbaum

TL;DR
This paper introduces the concept of isolation in natural experiments, focusing on rare moments of near-random treatment assignment within biased observational data to identify causal effects.
Contribution
It develops the theory of isolation and demonstrates its application through a reanalysis of a study on fertility's impact on workforce participation.
Findings
Mothers of twins work approximately 5% less than mothers of a single child.
Isolation can extract near-random treatment variations from biased data.
The method helps identify causal effects in observational studies.
Abstract
A natural experiment is a type of observational study in which treatment assignment, though not randomized by the investigator, is plausibly close to random. A process that assigns treatments in a highly nonrandom, inequitable manner may, in rare and brief moments, assign aspects of treatments at random or nearly so. Isolating those moments and aspects may extract a natural experiment from a setting in which treatment assignment is otherwise quite biased, far from random. Isolation is a tool that focuses on those rare, brief instances, extracting a small natural experiment from otherwise useless data. We discuss the theory behind isolation and illustrate its use in a reanalysis of a well-known study of the effects of fertility on workforce participation. Whether a woman becomes pregnant at a certain moment in her life and whether she brings that pregnancy to term may reflect her…
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