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Health disparities across education: The role of differential reporting error

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  • Anna Choi
  • John Cawley

Abstract

One of the most robust findings in health economics is that higher educated individuals tend to be in better health. This paper tests whether health disparities across education are to some extent due to differences in reporting error across education. We test this hypothesis using data from the pooled National Health and Nutrition Examination Survey (NHANES) for 1999–2012, which include both self‐reports and objective verification for an extensive set of health behaviors and conditions, including smoking, obesity, high blood pressure, high cholesterol, and diabetes. We find that college graduates are more likely to give false negative reports of obesity and high total cholesterol; one possible explanation for this is social desirability bias. However, college graduates are also significantly less likely to give false positive reports of smoking, obesity, and high cholesterol. Because there are far more truly negative people (who are less likely to give a false positive report) than more truly positive people (who are more likely to give a false negative report), we find that college graduates report their health significantly more accurately overall.

Suggested Citation

  • Anna Choi & John Cawley, 2018. "Health disparities across education: The role of differential reporting error," Health Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 1-29, March.
  • Handle: RePEc:wly:hlthec:v:27:y:2018:i:3:p:e1-e29
    DOI: 10.1002/hec.3609
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    Cited by:

    1. Irina Kislaya & Julian Perelman & Hanna Tolonen & Baltazar Nunes, 2019. "Do self-reported data accurately measure health inequalities in risk factors for cardiovascular disease?," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 64(5), pages 721-729, June.
    2. Arni, Patrick & Dragone, Davide & Goette, Lorenz & Ziebarth, Nicolas R., 2021. "Biased health perceptions and risky health behaviors—Theory and evidence," Journal of Health Economics, Elsevier, vol. 76(C).
    3. Chad Cotti & Erik Nesson & Nathan Tefft, 2019. "Impacts of the ACA Medicaid expansion on health behaviors: Evidence from household panel data," Health Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 219-244, February.
    4. Perry Singleton & Ling Li, 2016. "A Framework for Measurement Error in Self-Reported Health Conditions," Center for Policy Research Working Papers 191, Center for Policy Research, Maxwell School, Syracuse University.
    5. Cawley, John & Maclean, Johanna Catherine & Sikora Kessler, Asia, 2017. "Reporting error in weight and height among older adults: Implications for estimating healthcare costs," The Journal of the Economics of Ageing, Elsevier, vol. 9(C), pages 122-144.
    6. Cawley, John & Maclean, Johanna Catherine & Hammer, Mette & Wintfeld, Neil, 2015. "Reporting error in weight and its implications for bias in economic models," Economics & Human Biology, Elsevier, vol. 19(C), pages 27-44.
    7. Cullinan, John & Cawley, John, 2017. "Parental misclassification of child overweight/obese status: The role of parental education and parental weight status," Economics & Human Biology, Elsevier, vol. 24(C), pages 92-103.
    8. Nesson, Erik T. & Robinson, Joshua J., 2019. "On the measurement of health and its effect on the measurement of health inequality," Economics & Human Biology, Elsevier, vol. 35(C), pages 207-221.
    9. Glenn W. Harrison & Andre Hofmeyr & Don Ross & J. Todd Swarthout, 2018. "Risk Preferences, Time Preferences, and Smoking Behavior," Southern Economic Journal, John Wiley & Sons, vol. 85(2), pages 313-348, October.
    10. Glenn W. Harrison, 2017. "Behavioral responses to surveys about nicotine dependence," Health Economics, John Wiley & Sons, Ltd., vol. 26(S3), pages 114-123, December.
    11. Nolan, Anne & Smyth, Emer, 2020. "Clusters of health behaviours among young adults in Ireland," Research Series, Economic and Social Research Institute (ESRI), number RS101, June.
    12. Harris, Matthew C., 2017. "Imperfect information on physical activity and caloric intake," Economics & Human Biology, Elsevier, vol. 26(C), pages 112-125.
    13. Vincenzo Carrieri & Andrew M. Jones, 2017. "The Income–Health Relationship ‘Beyond the Mean’: New Evidence from Biomarkers," Health Economics, John Wiley & Sons, Ltd., vol. 26(7), pages 937-956, July.

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    More about this item

    JEL classification:

    • I1 - Health, Education, and Welfare - - Health
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I20 - Health, Education, and Welfare - - Education - - - General
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty

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