Embrace the Noise: It Is OK to Ignore Measurement Error in a Covariate, Sometimes

Hao Dong () and Daniel Millimet
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Hao Dong: Southern Methodist University

No 16508, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: In linear regression models, measurement error in a covariate causes Ordinary Least Squares (OLS) to be biased and inconsistent. Instrumental Variables (IV) is a common solution. While IV is also biased, it is consistent. Here, we undertake an asymptotic comparison of OLS and IV in the case where a covariate is mismeasured for [Nδ] of N observations with δ ∊ [0, 1]. We show that OLS is consistent for δ

Keywords: errors-in-variables; measurement error; asymptotics (search for similar items in EconPapers)
JEL-codes: C13 C26 C52 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2023-10
New Economics Papers: this item is included in nep-ecm
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