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A treatment effect is the causal effect of some "treatment" or policy intervention on an outcome variable. Such effects can be estimated with data from randomized or quasi experiments, and clinical trials or with observational data and methods for causal inference.
1
vote
Instrument Variables and Exclusion Restriction from a Mediation perspective
You correctly state that under the LATE-style IV assumptions with a causal effect of the IV Z on the treatment S, exogenous instrument, and no direct effect on the outcome Y, your treatment effect B o …
2
votes
Accepted
Understanding the perfect randomization assumption in treatment models
No, you do not have marginal independence, not even under restrictive parametric assumptions.
Let's ignore $X$ and let Y = g(U) be linear, so that
$$Y = \beta D + U. $$
Furthermore, let $D \sim Uni …
4
votes
Instrumental variables: In which cases would the average treatment effect on the treated (AT...
No, this is not correct. Let's walk through the basics to see why, and to see under what other assumptions ATT = LATE.
Let us call treatment assignment $Z$, and actual treatment taken $D$. Compliers …
4
votes
Difference-in-difference model with mediators: Estimating the effect of different elements o...
You need to explicitly think about a causal model for $Y$ including the $M^x$. It seems you are assuming the effect of $D$ on $Y$ is a constant $\phi$, so I'll assume constant effects throughout.
You …