An Introduction to Nonparametric Regression for Labor Economists

In this article we overview nonparametric (spline and kernel) regression methods and illustrate how they may be used in labor economic applications. We focus our attention on issues commonly found in the labor literature such as how to account for endogeneity via instrumental variables in a nonparametric setting. We showcase these methods via data from the Current Population Survey.

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Year of publication:	2018
Authors:	Henderson, Daniel J. ; Souto, Anne-Charlotte
Publisher:	Bonn : Institute of Labor Economics (IZA)
Subject:	endogeneity \| kernel \| labor \| nonparametic \| regression \| spline

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Series:	IZA Discussion Papers ; 11914
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	1043631569 [GVK] hdl:10419/193208 [Handle] RePEc:iza:izadps:dp11914 [RePEc]
Classification:	C14 - Semiparametric and Nonparametric Methods ; c26 ; i24 ; J24 - Human Capital; Skills; Occupational Choice; Labor Productivity ; J31 - Wage Level and Structure; Wage Differentials by Skill, Training, Occupation, etc
Source:	EconStor

Persistent link: https://www.econbiz.de/10011984474