Semi-parametric estimation of multi-valued treatment effects for the treated:estimating equations and sandwich estimators
Johan Zetterqvist () and
Ingeborg Waernbaum ()
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Johan Zetterqvist: Karolinska institutet, Postal: Karolinska institutet, Stockholm, Sweden
Ingeborg Waernbaum: IFAU - Institute for Evaluation of Labour Market and Education Policy, Postal: Institute for Evaluation of Labour Market and Education Policy, P O Box 513, SE-751 20 Uppsala, Sweden
No 2020:4, Working Paper Series from IFAU - Institute for Evaluation of Labour Market and Education Policy
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.
Keywords: ATT; causal inference; inverse probability weighting; doubly robust; weighted ordinary least squares (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Pages: 65 pages
Date: 2020-03-05
New Economics Papers: this item is included in nep-ecm and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:ifauwp:2020_004
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