Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/92272
Authors: 
O'Neill, Donal
Sweetman, Olive
Year of Publication: 
2013
Citation: 
[Journal:] IZA Journal of Labor Economics [ISSN:] 2193-8997 [Publisher:] Springer [Place:] Heidelberg [Volume:] 2 [Year:] 2013 [Pages:] 1-20
Abstract: 
This paper examines the consequences of using self-reported measures of BMI when estimating the effect of BMI on income for women using both Irish and US data. We find that self-reported BMI is subject to substantial measurement error and that this error deviates from classical measurement error. These errors cause the traditional least squares estimator to overestimate the relationship between BMI and income. We show that neither the conditional expectation estimator nor the instrumental variables approach adequately address the bias and briefly discuss alternative approaches that could be considered when faced with non-classical measurement error.
Subjects: 
obesity
non-classical measurement error
auxiliary data
instrumental variables
JEL: 
C13
C26
I14
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/2.0/
Document Type: 
Article
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