Campus Units

Economics

Document Type

Article

Publication Version

Published Version

Publication Date

11-2010

Journal or Book Title

Review of Economics and Statistics

Volume

92

Issue

4

First Page or Article ID Number

1017

Last Page

1023

DOI

10.1162/REST_a_00044

Abstract

Recent evidence from Bound, Brown, and Mathiowetz (2001) and Black, Sanders, and Taylor (2003) suggests that reporting errors in survey data routinely violate all of the classical measurement error assumptions. The econometrics literature has not considered the consequences of fully arbitrary measurement error for identification of regression coefficients. This paper highlights the severity of the identification problem given the presence of even infrequent arbitrary errors in a binary regressor. In the empirical component, health insurance misclassification rates of less than 1.3% generate double-digit percentage point ranges of uncertainty about the variable's true marginal effect on the use of health services.

Comments

This article is published as Kreider, Brent. "Regression coefficient identification decay in the presence of infrequent classification errors." The Review of Economics and Statistics 92, no. 4 (2010): 1017-1023. doi: 10.1162/REST_a_00044 . For more information see https://www.mitpressjournals.org/loi/rest. Posted with permission.

Copyright Owner

President and Fellows of Harvard College and the Massachusetts Institute of Technology

Language

en

File Format

application/pdf

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