IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp6898.html
   My bibliography  Save this paper

Indebted and Overweight: The Link Between Weight and Household Debt

Author

Listed:
  • Averett, Susan L.

    () (Lafayette College)

  • Smith, Julie K.

    () (Lafayette College)

Abstract

There is a substantial correlation between household debt and bodyweight. Theory suggests that a causal relationship between debt and bodyweight could run in either direction or both could be caused by unobserved common factors. We use OLS and Propensity Score Matching to ascertain if household debt (measured by credit card indebtedness and having trouble paying bills) is a potential cause of obesity. We find a strong positive correlation between debt and weight for women but this seems driven largely by unobservables. In contrast, men with trouble paying their bills are thinner and this is robust to various specification checks.

Suggested Citation

  • Averett, Susan L. & Smith, Julie K., 2012. "Indebted and Overweight: The Link Between Weight and Household Debt," IZA Discussion Papers 6898, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp6898
    as

    Download full text from publisher

    File URL: http://ftp.iza.org/dp6898.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Caliendo, Marco & Lee, Wang-Sheng, 2013. "Fat chance! Obesity and the transition from unemployment to employment," Economics & Human Biology, Elsevier, vol. 11(2), pages 121-133.
    2. Becker, Sascha O. & Caliendo, Marco, 2007. "mhbounds – Sensitivity Analysis for Average Treatment Effects," IZA Discussion Papers 2542, Institute for the Study of Labor (IZA).
    3. Angela C. Lyons & Tansel Yilmazer, 2005. "Health and Financial Strain: Evidence from the Survey of Consumer Finances," Southern Economic Journal, Southern Economic Association, vol. 71(4), pages 873-890, April.
    4. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    5. Rajeev H. Dehejia & Sadek Wahba, 2002. "Propensity Score-Matching Methods For Nonexperimental Causal Studies," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 151-161, February.
    6. Irina Grafova, 2007. "Your Money or Your Life: Managing Health, Managing Money," Journal of Family and Economic Issues, Springer, vol. 28(2), pages 285-303, June.
    7. Smith Trenton G. & Stoddard Christiana & Barnes Michael G, 2009. "Why the Poor Get Fat: Weight Gain and Economic Insecurity," Forum for Health Economics & Policy, De Gruyter, vol. 12(2), pages 1-31, June.
    8. Charles Michalopoulos & Howard S. Bloom & Carolyn J. Hill, 2004. "Can Propensity-Score Methods Match the Findings from a Random Assignment Evaluation of Mandatory Welfare-to-Work Programs?," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 156-179, February.
    9. Dehejia, Rajeev, 2005. "Practical propensity score matching: a reply to Smith and Todd," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 355-364.
    10. Edwin Leuven & Barbara Sianesi, 2003. "PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing," Statistical Software Components S432001, Boston College Department of Economics, revised 01 Feb 2018.
    11. Sascha O. Becker & Marco Caliendo, 2007. "Sensitivity analysis for average treatment effects," Stata Journal, StataCorp LP, vol. 7(1), pages 71-83, February.
    12. Burkhauser, Richard V. & Cawley, John, 2008. "Beyond BMI: The value of more accurate measures of fatness and obesity in social science research," Journal of Health Economics, Elsevier, vol. 27(2), pages 519-529, March.
    13. Zhong Zhao, 2004. "Using Matching to Estimate Treatment Effects: Data Requirements, Matching Metrics, and Monte Carlo Evidence," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 91-107, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Leigh Ann Leung & Catherine Lau, 2017. "Effect of mortgage indebtedness on health of U.S. homeowners," Review of Economics of the Household, Springer, vol. 15(1), pages 239-264, March.

    More about this item

    Keywords

    credit card debt; propensity score matching; obesity;

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp6898. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mark Fallak). General contact details of provider: http://www.iza.org .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.