In: Journal of the Royal Statistical Society Series B, 2017, vol. 79, no. 5, p. 1645-1666
The paper discusses the non‐parametric identification of causal direct and indirect effects of a binary treatment based on instrumental variables. We identify the indirect effect, which operates through a mediator (i.e. intermediate variable) that is situated on the causal path between the treatment and the outcome, as well as the unmediated direct effect of the treatment by using distinct...
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In: Journal of Applied Econometrics, 2017, vol. 32, no. 1, p. 56-79
In the presence of an endogenous binary treatment and a valid binary instru- ment, causal effects are point identified only for the subpopulation of compliers, given that the treatment is monotone in the instrument. With the exception of the entire population, causal inference for further subpopulations has been widely ignored in econometrics. We invoke treatment monotonicity and/or dominance...
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In: Review of economics and statistics, 2015, vol. 97, no. 2, p. 398-411
We derive testable implications of instrument validity in just identified treat- ment effect models with endogeneity and consider several tests. The identifying assump- tions of the local average treatment effect allow us to both point identify and bound the mean potential outcomes (i) of the always takers under treatment and (ii) of the never takers under non-treatment. The point identified...
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