Inference in additively separable models with a high-dimensional set of conditioning variables

This paper studies nonparametric series estimation and inference for the effect of a single variable of interest x on an outcome y in the presence of potentially high-dimensional conditioning variables z. The context is an additively separable model E[y

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Year of publication:	2018
Authors:	Kozbur, Damian
Publisher:	Zurich : University of Zurich, Department of Economics
Subject:	Additive nonparametric models \| high-dimensional sparse regression \| inference under imperfect model selection

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Series:	Working Paper ; 284
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	10.5167/uzh-151161 [DOI] 1019873655 [GVK] hdl:10419/192893 [Handle]
Classification:	C1 - Econometric and Statistical Methods: General
Source:	EconStor

Persistent link: https://www.econbiz.de/10011969195