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 of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp6898
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp6898.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Keese, Matthias & Schmitz, Hendrik, 2010. "Broke, Ill, and Obese: The Effect of Household Debt on Health," Ruhr Economic Papers 234, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    2. Sascha O. Becker & Marco Caliendo, 2007. "Sensitivity analysis for average treatment effects," Stata Journal, StataCorp LP, vol. 7(1), pages 71-83, February.
    3. Petra E. Todd & Jeffrey A. Smith, 2001. "Reconciling Conflicting Evidence on the Performance of Propensity-Score Matching Methods," American Economic Review, American Economic Association, vol. 91(2), pages 112-118, May.
    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. 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.
    6. 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.
    7. 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.
    8. Dehejia, Rajeev, 2005. "Practical propensity score matching: a reply to Smith and Todd," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 355-364.
    9. 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.
    10. 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.
    11. Denis Conniffe & Vanessa Gash & Philip J. O'Connell, 2000. "Evaluating State Programmes - “Natural Experiments” and Propensity Scores," The Economic and Social Review, Economic and Social Studies, vol. 31(4), pages 283-308.
    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. Drentea, Patricia & Lavrakas, Paul J., 2000. "Over the limit: the association among health, race and debt," Social Science & Medicine, Elsevier, vol. 50(4), pages 517-529, February.
    14. 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.
    15. Black, Dan A. & Smith, J.A.Jeffrey A., 2004. "How robust is the evidence on the effects of college quality? Evidence from matching," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 99-124.
    16. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2008. "Using Selection on Observed Variables to Assess Bias from Unobservables When Evaluating Swan-Ganz Catheterization," American Economic Review, American Economic Association, vol. 98(2), pages 345-350, May.
    17. 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.
    18. Angela C. Lyons & Tansel Yilmazer, 2005. "Health and Financial Strain: Evidence from the Survey of Consumer Finances," Southern Economic Journal, John Wiley & Sons, vol. 71(4), pages 873-890, April.
    19. repec:zbw:rwirep:0234 is not listed on IDEAS
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Averett, Susan L. & Smith, Julie K., 2014. "Financial hardship and obesity," Economics & Human Biology, Elsevier, vol. 15(C), pages 201-212.
    2. Tommaso Nannicini, 2007. "Simulation-based sensitivity analysis for matching estimators," Stata Journal, StataCorp LP, vol. 7(3), pages 334-350, September.
    3. 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.
    4. Carlos A. Flores & Oscar A. Mitnik, 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," Working Papers 2010-10, University of Miami, Department of Economics.
    5. Phadera,Lokendra & Sharma,Dhiraj & Wai-Poi,Matthew Grant, 2020. "Iraq's Universal Public Distribution System : Utilization and Impacts During Displacement," Policy Research Working Paper Series 9155, The World Bank.
    6. D. Mark Anderson, 2013. "The Impact Of Hiv Education On Behavior Among Youths: A Propensity Score Matching Approach," Contemporary Economic Policy, Western Economic Association International, vol. 31(3), pages 503-527, July.
    7. Gonzalo Nunez-Chaim & Henry G. Overman & Capucine Riom, 2024. "Does subsidising business advice improve firm performance? Evidence from a large RCT," CEP Discussion Papers dp1977, Centre for Economic Performance, LSE.
    8. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    9. Eliasson, Kent, 2006. "How Robust is the Evidence on the Returns to College Choice? Results Using Swedish Administrative Data," Umeå Economic Studies 692, Umeå University, Department of Economics.
    10. Simone Bertoli & Francesca Marchetta, 2014. "Migration, Remittances and Poverty in Ecuador," Journal of Development Studies, Taylor & Francis Journals, vol. 50(8), pages 1067-1089, August.
    11. Stephan, Gesine & Pahnke, André, 2008. "The Relative Effectiveness of Selected Active Labour Market Programmes and the Common Support Problem," IZA Discussion Papers 3767, Institute of Labor Economics (IZA).
    12. Helena Holmlund & Olmo Silva, 2014. "Targeting Noncognitive Skills to Improve Cognitive Outcomes: Evidence from a Remedial Education Intervention," Journal of Human Capital, University of Chicago Press, vol. 8(2), pages 126-160.
    13. Rodrigo Martín-García & Jorge Morán Santor, 2021. "Public guarantees: a countercyclical instrument for SME growth. Evidence from the Spanish Region of Madrid," Small Business Economics, Springer, vol. 56(1), pages 427-449, January.
    14. Seonho Shin, 2022. "Evaluating the Effect of the Matching Grant Program for Refugees: An Observational Study Using Matching, Weighting, and the Mantel-Haenszel Test," Journal of Labor Research, Springer, vol. 43(1), pages 103-133, March.
    15. Riccardo Turati, 2020. "Network-based Connectedness and the Diffusion of Cultural Traits," LIDAM Discussion Papers IRES 2020012, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    16. Lockwood Reynolds, C., 2012. "Where to attend? Estimating the effects of beginning college at a two-year institution," Economics of Education Review, Elsevier, vol. 31(4), pages 345-362.
    17. Bagnoli, Lisa, 2019. "Does health insurance improve health for all? Heterogeneous effects on children in Ghana," World Development, Elsevier, vol. 124(C), pages 1-1.
    18. Dettmann, E. & Becker, C. & Schmeißer, C., 2011. "Distance functions for matching in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1942-1960, May.
    19. Johar, Meliyanni, 2009. "The impact of the Indonesian health card program: A matching estimator approach," Journal of Health Economics, Elsevier, vol. 28(1), pages 35-53, January.
    20. Giorgia Casalone & Eliana Baici, 2023. "Education, Off-the-Job Vocational Training, and Early Employment Outcomes: Evidence from Italy," Merits, MDPI, vol. 3(2), pages 1-15, May.

    More about this item

    Keywords

    propensity score matching; credit card debt; obesity;
    All these keywords.

    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.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.