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Reporting error in weight and its implications for bias in economic models

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  • Cawley, John
  • Maclean, Johanna Catherine
  • Hammer, Mette
  • Wintfeld, Neil

Abstract

Most research on the economic consequences of obesity uses data on self-reported weight, which contains reporting error that has the potential to bias coefficient estimates in economic models. The purpose of this paper is to measure the extent and characteristics of reporting error in weight, and to examine its impact on regression coefficients in models of the healthcare consequences of obesity.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ehbiol:v:19:y:2015:i:c:p:27-44
    DOI: 10.1016/j.ehb.2015.07.001
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    References listed on IDEAS

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    8. John Cawley & Chad Meyerhoefer & Adam Biener & Mette Hammer & Neil Wintfeld, 2015. "Savings in Medical Expenditures Associated with Reductions in Body Mass Index Among US Adults with Obesity, by Diabetes Status," PharmacoEconomics, Springer, vol. 33(7), pages 707-722, July.
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    11. Cawley, John & Meyerhoefer, Chad, 2012. "The medical care costs of obesity: An instrumental variables approach," Journal of Health Economics, Elsevier, vol. 31(1), pages 219-230.
    12. Courtemanche, Charles & Pinkston, Joshua C. & Stewart, Jay, 2015. "Adjusting body mass for measurement error with invalid validation data," Economics & Human Biology, Elsevier, vol. 19(C), pages 275-293.
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    1. John Cawley & Euna Han & Jiyoon Kim & Edward C. Norton, 2019. "Testing for family influences on obesity: The role of genetic nurture," Health Economics, John Wiley & Sons, Ltd., vol. 28(7), pages 937-952, July.
    2. John Cawley & Alex Susskind & Barton Willage, 2020. "The Impact of Information Disclosure on Consumer Behavior: Evidence from a Randomized Field Experiment of Calorie Labels on Restaurant Menus," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(4), pages 1020-1042, September.
    3. Burke, Mary A. & Carman, Katherine G., 2017. "You can be too thin (but not too tall): Social desirability bias in self-reports of weight and height," Economics & Human Biology, Elsevier, vol. 27(PA), pages 198-222.
    4. Wang, Huixia & Wang, Chenggang & Halliday, Timothy J., 2018. "Health and health inequality during the great recession: Evidence from the PSID," Economics & Human Biology, Elsevier, vol. 29(C), pages 17-30.
    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. Peter A.G. van Bergeijk, 2017. "Making Data Measurement Errors Transparent: The Case of the IMF," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 18(3), pages 133-154, July.
    7. Chenggang Wang & Huixia Wang & Timothy J. Halliday, 2017. "Health and Health Inequality during the Great Recession: Evidence from the PSID," Working Papers 201703, University of Hawaii at Manoa, Department of Economics.
    8. 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.
    9. Dolton, Peter & Xiao, Mimi, 2017. "The intergenerational transmission of body mass index across countries," Economics & Human Biology, Elsevier, vol. 24(C), pages 140-152.
    10. Kabir Dasgupta & Keisha T.-Solomon, 2017. "Family Size Effects on Child Health: Evidence on the Quantity-Quality Trade-off using the NLSY," Working Papers 2017-04, Auckland University of Technology, Department of Economics.
    11. Susan Chen & Le Wang, 0. "SNAP participation, diet quality, and obesity: robust evidence with estimation techniques without external instrumental variables," Empirical Economics, Springer, vol. 0, pages 1-27.
    12. Davillas, Apostolos & Benzeval, Michaela, 2016. "Alternative measures to BMI: Exploring income-related inequalities in adiposity in Great Britain," Social Science & Medicine, Elsevier, vol. 166(C), pages 223-232.
    13. Johanna Catherine Maclean & Asia Sikora Kessler, 2015. "Reporting error in weight and height among the elderly: Implications and recommendations for estimating healthcare costs," DETU Working Papers 1501, Department of Economics, Temple University.
    14. Petri Böckerman & John Cawley & Jutta Viinikainen & Terho Lehtimäki & Suvi Rovio & Ilkka Seppälä & Jaakko Pehkonen & Olli Raitakari, 2019. "The effect of weight on labor market outcomes: An application of genetic instrumental variables," Health Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 65-77, January.
    15. John Cawley & Damien de Walque & Daniel Grossman, 2017. "The Effect of Stress on Later-Life Health: Evidence from the Vietnam Draft," NBER Working Papers 23334, National Bureau of Economic Research, Inc.
    16. Christina Hansen Edwards & Johan Håkon Bjørngaard & Jonas Minet Kinge, 2021. "The relationship between body mass index and income: Using genetic variants from HUNT as instrumental variables," Health Economics, John Wiley & Sons, Ltd., vol. 30(8), pages 1933-1949, August.
    17. Bozzi, Debra G. & Nicholas, Lauren Hersch, 2021. "A Causal Estimate of Long-Term Health Care Spending Attributable to Body Mass Index Among Adults," Economics & Human Biology, Elsevier, vol. 41(C).
    18. Seuring, Till & Serneels, Pieter & Suhrcke, Marc, 2019. "The impact of diabetes on labour market outcomes in Mexico: A panel data and biomarker analysis," Social Science & Medicine, Elsevier, vol. 233(C), pages 252-261.
    19. Zeng, Di & Thomsen, Michael R. & Nayga, Rodolfo M. & Bennett, Judy L., 2019. "Supermarket access and childhood bodyweight: Evidence from store openings and closings," Economics & Human Biology, Elsevier, vol. 33(C), pages 78-88.
    20. Dixon, Padraig & Hollingworth, William & Harrison, Sean & Davies, Neil M. & Davey Smith, George, 2020. "Mendelian Randomization analysis of the causal effect of adiposity on hospital costs," Journal of Health Economics, Elsevier, vol. 70(C).
    21. van Bergeijk, P.A.G., 2017. "Measurement error of global production," ISS Working Papers - General Series 632, International Institute of Social Studies of Erasmus University Rotterdam (ISS), The Hague.
    22. Black, Nicole & Hughes, Robert & Jones, Andrew M., 2018. "The health care costs of childhood obesity in Australia: An instrumental variables approach," Economics & Human Biology, Elsevier, vol. 31(C), pages 1-13.
    23. Davillas, Apostolos & Jones, Andrew M., 2020. "Regional inequalities in adiposity in England: distributional analysis of the contribution of individual-level characteristics and the small area obesogenic environment," Economics & Human Biology, Elsevier, vol. 38(C).
    24. Dasgupta, Kabir & Solomon, Keisha T., 2018. "Family size effects on childhood obesity: Evidence on the quantity-quality trade-off using the NLSY," Economics & Human Biology, Elsevier, vol. 29(C), pages 42-55.

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