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What is the intuition behind Regression Discontinuity Design (RDD)?
in Data Science by Wooden (4,850 points)
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Regression discontinuity designs: the treatment status changes discontinuously according to some underlying pre-treatment variable – the running variable

 

Basic idea: comparing units with similar values of the running variable, but different levels of treatment would lead to causal effect of the treatment at the threshold

The discontinuity is often created by a pre-fixed, artificial threshold of a policy

Treatment among the subjects around the threshold can be viewed as locally randomized

by Wooden (4,850 points)

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