forthcoming in: Journal of the Royal Statistical Society, Series A
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 < 1 and is asymptotically normal and more efficient than IV for δ < 0.5. Simulations and an application to the impact of body mass index on family income demonstrate the practical usefulness of this result.
We use cookies to provide you with an optimal website experience. This includes cookies that are necessary for the operation of the site as well as cookies that are only used for anonymous statistical purposes, for comfort settings or to display personalized content. You can decide for yourself which categories you want to allow. Please note that based on your settings, you may not be able to use all of the site's functions.
Cookie settings
These necessary cookies are required to activate the core functionality of the website. An opt-out from these technologies is not available.
In order to further improve our offer and our website, we collect anonymous data for statistics and analyses. With the help of these cookies we can, for example, determine the number of visitors and the effect of certain pages on our website and optimize our content.