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The Consequences of Measurement Error when Estimating the Impact of BMI on Labour Market Outcomes

Author

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  • O'Neill, Donal

    (National University of Ireland, Maynooth)

  • Sweetman, Olive

    (National University of Ireland, Maynooth)

Abstract

This paper uses data on both self-reported and true measures of individual Body Mass Index (BMI) to examine the nature of measurement error in self-reported BMI and to look at the consequences of using self-reported measures when estimating the effect of BMI on economic outcomes. In keeping with previous studies we find that self-reported BMI is subject to significant measurement error and this error is negatively correlated with the true measure of BMI. In our analysis this non-classical measurement error causes the traditional approach to overestimate the relationship between BMI and both income and education. Furthermore we show that popular alternatives estimators that have been adopted to address problems of measurement error in BMI, such as the conditional expectation approach and the instrumental variables approach, also exhibit significant biases.

Suggested Citation

  • O'Neill, Donal & Sweetman, Olive, 2012. "The Consequences of Measurement Error when Estimating the Impact of BMI on Labour Market Outcomes," IZA Discussion Papers 7008, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp7008
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    Cited by:

    1. Donal O'Neill & Olive Sweetman, 2013. "Estimating Obesity Rates in Europe in the Presence of Self-Reporting Errors," Economics Department Working Paper Series n236-13.pdf, Department of Economics, National University of Ireland - Maynooth.
    2. Castelnovo, Paolo, 2014. "Short and Long-run Effects of Obesity on Cognitive Skills: Evidence from an English Cohort," MPRA Paper 107706, University Library of Munich, Germany, revised 2014.

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    More about this item

    Keywords

    non-classical measurement error; instrumental variables; obesity; auxiliary data;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

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