Testing for the presence of measurement error in Stata

In this paper, we describe how to test for the presence of measurement error in explanatory variables. First, we discuss the test of such hypotheses in parametric models such as linear regressions and then introduce a new Stata command [R] dgmtest for a nonparametric test proposed in Wilhelm (2018). To illustrate the new command, we provide Monte Carlo simulations and an empirical application to testing for measurement error in administrative earnings data.

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Year of publication:	2019
Authors:	Lee, Young Jun ; Wilhelm, Daniel
Publisher:	London : Centre for Microdata Methods and Practice (cemmap)
Subject:	st0001 \| nonparametric test \| measurement error \| measurement errorbias

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Series:	cemmap working paper ; CWP47/19
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	10.1920/wp.cem.2019.4719 [DOI] 1677708468 [GVK] hdl:10419/211140 [Handle] RePEc:ifs:cemmap:47/19 [RePEc]
Source:	EconStor

Persistent link: https://www.econbiz.de/10012146399