Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/227852
Authors: 
Zetterqvist, Johan
Waernbaum, Ingeborg
Year of Publication: 
2020
Series/Report no.: 
Working Paper No. 2020:4
Abstract: 
An estimand of interest in empirical studies with observational data is the average treatment effect of a multi-valued treatment in the treated subpopulation. We demonstrate three estimation approaches: outcome regression, inverse probability weighting and inverse probability weighted regression, where the latter estimator holds a so called doubly robust property. Here, we define the estimators in the framework of partial M-estimation and derive corresponding sandwich estimators of their variances. The finite sample properties of the estimators and the proposed variance estimators are evaluated in simulations that reproduce designs from a previous simulation study in the literature of multi-valued treatment effects. The proposed variance estimators are investigated and compared to a bootstrap estimator.
Subjects: 
ATT
causal inference
inverse probability weighting
doubly robust
weighted ordinary least squares
JEL: 
C14
Document Type: 
Working Paper

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