Last updated on September 12, 2020
I am happy to share a leaner, meaner version of my paper with Jeff Bloem and Noah Wexler titled “The Paper of How: Estimating Treatment Effects with the Front-Door Criterion,” which we finished last week.
Here is the abstract:
We present the first application of Pearl’s (1995) front-door criterion to observational data wherein the required point-identification assumptions plausibly hold. For identification, the front-door criterion exploits exogenous mediator variables on the causal path. We estimate the effect of authorizing a shared Uber or Lyft ride on tipping by exploiting the plausibly exogenous variation in whether one actually shares a ride with a stranger conditional on authorizing sharing, on fare level, and on time-and-place fixed effects. We find that most of the observed negative effect on tipping is driven by selection. We then explore the consequences of violating the identification assumptions.
This version has benefited from comments from many people who were very generous with their time. We are grateful for any and all additional comments.