Semiparametric Instrumental Variable Estimation in an Endogenous Treatment Model
Roger Klein () and
Chan Shen ()
Additional contact information
Roger Klein: Rutgers University
Chan Shen: UT MD Anderson
Departmental Working Papers from Rutgers University, Department of Economics
We propose instrumental variable(IV) estimators for quantile marginal effects and the parameters upon which they depend in a semiparametric outcome model with endogenous discrete treatment variables. We prove identification, consistency, and asymptotic normality of the estimators. We also show that they are efficient under correct model specification. Further, we show that they are robust to misspecification of the treatment model in that consistency and asymptotic normality continue to hold in this case. In the Monte Carlo study, the estimators perform well over diverse designs covering both correct and incorrect treatment model specifications.
Keywords: semiparametric; IV; marginal effects; efficiency; robustness (search for similar items in EconPapers)
JEL-codes: C14 C16 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:rut:rutres:201511
Access Statistics for this paper
More papers in Departmental Working Papers from Rutgers University, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by ().