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Correlation != causation



The title of the NPR article would be more accurate as "Cities See a Reduction in Ambulance Usage After Uber is Introduced".

The paper looks at 700 different cities, each with a different Uber market entry time over a two year period. The researchers also control for some seasonality effects.

Perhaps more covariates could have been considered, but this seems like a pretty decent design to measure a before/after causal effect.


Yea, the percentage stated is super low. It might be true, but the data isn't enough to reflect the statement.




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