IDEAS home Printed from https://ideas.repec.org/a/ses/arsjes/2016-iii-3.html
   My bibliography  Save this article

Obesity and Health-Care Costs in Switzerland: Dealing with Endogeneity in Non-Linear Regression Models

Author

Listed:
  • Stefan J Meyer

Abstract

We draw microdata from the Swiss Household Panel to estimate the causal effect of obesity on the number of physician visits, the amount of hospital days, and the respective costs incurred. We do so by simultaneously coping with three endogeneity issues, comprising reporting errors, omitted variables, and simultaneity. Using the conditional expectation approach, we first account for the reporting errors in weight and height. Second, we address endogeneity in the body mass index (BMI) by applying a control function approach. In contrast to the method of two-stage least squares, this technique is consistent in non-linear regression settings. Using the mean BMI of relatives as an instrument for the respondent’s BMI, we show that naïve regression methods considerably underestimate the impact of weight on the use of inpatient care, outpatient care, and costs. Accordingly, an additional unit of BMI raises annual health-care costs by CHF 253 or 11.5%, while the non-IV estimate amounts to only CHF 34 or 1.5%. Several robustness checks suggest the average marginal effect to be in the range of between CHF 220 and CHF 294. The model also predicts that if the overweight and obese people in the sample lost weight to the threshold of being of normal weight (BMI = 25), health-care costs could be reduced by about –4.7%. We conclude that the negative external effects caused by overweight and obesity are considerably larger than previously thought.

Suggested Citation

  • Stefan J Meyer, 2016. "Obesity and Health-Care Costs in Switzerland: Dealing with Endogeneity in Non-Linear Regression Models," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 152(III), pages 243-286, September.
  • Handle: RePEc:ses:arsjes:2016-iii-3
    as

    Download full text from publisher

    File URL: http://www.sjes.ch/papers/2016-III-3.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Donal O’Neill & Olive Sweetman, 2013. "The consequences of measurement error when estimating the impact of obesity on income," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 2(1), pages 1-20, December.
    4. Schroeter, Christiane & Lusk, Jayson & Tyner, Wallace, 2008. "Determining the impact of food price and income changes on body weight," Journal of Health Economics, Elsevier, vol. 27(1), pages 45-68, January.
    5. Parks, Joanna C. & Alston, Julian M. & Okrent, Abigail M., 2012. "The Marginal External Cost of Obesity in the United States," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 125128, Agricultural and Applied Economics Association.
    6. Cawley, John & Ruhm, Christopher J., 2011. "The Economics of Risky Health Behaviors," Handbook of Health Economics, in: Mark V. Pauly & Thomas G. Mcguire & Pedro P. Barros (ed.), Handbook of Health Economics, volume 2, chapter 0, pages 95-199, Elsevier.
    7. Windmeijer, F A G & Silva, J M C Santos, 1997. "Endogeneity in Count Data Models: An Application to Demand for Health Care," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 281-294, May-June.
    8. Buntin, Melinda Beeuwkes & Zaslavsky, Alan M., 2004. "Too much ado about two-part models and transformation?: Comparing methods of modeling Medicare expenditures," Journal of Health Economics, Elsevier, vol. 23(3), pages 525-542, May.
    9. Gil, Joan & Mora, Toni, 2011. "The determinants of misreporting weight and height: The role of social norms," Economics & Human Biology, Elsevier, vol. 9(1), pages 78-91, January.
    10. Jason M. Fletcher & David Frisvold & Nathan Tefft, 2010. "Can Soft Drink Taxes Reduce Population Weight?," Contemporary Economic Policy, Western Economic Association International, vol. 28(1), pages 23-35, January.
    11. Jaeun Shin & Sangho Moon, 2007. "Do Hmo Plans Reduce Health Care Expenditure In The Private Sector?," Economic Inquiry, Western Economic Association International, vol. 45(1), pages 82-99, January.
    12. Shane Frederick & George Loewenstein & Ted O'Donoghue, 2002. "Time Discounting and Time Preference: A Critical Review," Journal of Economic Literature, American Economic Association, vol. 40(2), pages 351-401, June.
    13. Patrick Royston & Paul C. Lambert, 2011. "Flexible Parametric Survival Analysis Using Stata: Beyond the Cox Model," Stata Press books, StataCorp LP, number fpsaus, March.
    14. Lindrooth, Richard C. & Weisbrod, Burton A., 2007. "Do religious nonprofit and for-profit organizations respond differently to financial incentives? The hospice industry," Journal of Health Economics, Elsevier, vol. 26(2), pages 342-357, March.
    15. 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.
    16. Alexandra Schmid & Heinz Schneider & Alain Golay & Ulrich Keller, 2005. "Economic burden of obesity and its comorbidities in Switzerland," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 50(2), pages 87-94, April.
    17. 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.
    18. Mark V. Pauly & Thomas G. Mcguire & Pedro P. Barros (ed.), 2011. "Handbook of Health Economics," Handbook of Health Economics, Elsevier, volume 2, number 2.
    19. Marc Fox, 2003. "Medical student indebtedness and the propensity to enter academic medicine," Health Economics, John Wiley & Sons, Ltd., vol. 12(2), pages 101-112, February.
    20. Wooldridge, Jeffrey M., 2014. "Quasi-maximum likelihood estimation and testing for nonlinear models with endogenous explanatory variables," Journal of Econometrics, Elsevier, vol. 182(1), pages 226-234.
    21. Manning, Willard G. & Mullahy, John, 2001. "Estimating log models: to transform or not to transform?," Journal of Health Economics, Elsevier, vol. 20(4), pages 461-494, July.
    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. Abdul-Basit Tampuli Abukari & Suad Morro & Munkaila Lambongang, 2022. "Modeling rice consumption preferences: an improved approach," SN Business & Economics, Springer, vol. 2(12), pages 1-26, December.

    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. Stefan Meyer, 2016. "Obesity and Health-Care Costs in Switzerland: Dealing with Endogeneity in Non-Linear Regression Models," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 152(3), pages 243-286, July.
    2. 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.
    3. Cawley, John, 2015. "An economy of scales: A selective review of obesity's economic causes, consequences, and solutions," Journal of Health Economics, Elsevier, vol. 43(C), pages 244-268.
    4. Åsa Ljungvall & Ulf Gerdtham & Ulf Lindblad, 2015. "Misreporting and misclassification: implications for socioeconomic disparities in body-mass index and obesity," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(1), pages 5-20, January.
    5. 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.
    6. Pastore, Chiara & Schurer, Stefanie & Tymula, Agnieszka & Fuller, Nicholas & Caterson, Ian, 2020. "Economic Preferences and Obesity: Evidence from a Clinical Lab-in-Field Experiment," IZA Discussion Papers 13915, Institute of Labor Economics (IZA).
    7. Xuezheng Qin & Jay Pan, 2016. "The Medical Cost Attributable to Obesity and Overweight in China: Estimation Based on Longitudinal Surveys," Health Economics, John Wiley & Sons, Ltd., vol. 25(10), pages 1291-1311, October.
    8. J. M. C. Santos Silva & Silvana Tenreyro, 2022. "The Log of Gravity at 15," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 21(3), pages 423-437, September.
    9. Toni Mora & Joan Gil & Antoni Sicras-Mainar, 2012. "The Influence of BMI, Obesity and Overweight on Medical Costs: A Panel Data Approach," Working Papers 2012-08, FEDEA.
    10. Zarko Kalamov, 2020. "A sales tax is better at promoting healthy diets than the fat tax and the thin subsidy," Health Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 353-366, March.
    11. Toni Mora & Joan Gil & Antoni Sicras-Mainar, 2015. "The influence of obesity and overweight on medical costs: a panel data perspective," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(2), pages 161-173, March.
    12. Chee‐Ruey Hsieh & Xuezheng Qin, 2018. "Depression hurts, depression costs: The medical spending attributable to depression and depressive symptoms in China," Health Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 525-544, March.
    13. Charles J. Courtemanche & Joshua C. Pinkston & Christopher J. Ruhm & George L. Wehby, 2016. "Can Changing Economic Factors Explain the Rise in Obesity?," Southern Economic Journal, John Wiley & Sons, vol. 82(4), pages 1266-1310, April.
    14. O’Neill, Donal, 2015. "Measuring obesity in the absence of a gold standard," Economics & Human Biology, Elsevier, vol. 17(C), pages 116-128.
    15. Patacchini, Eleonora & Bisin, Alberto, 2019. "Dynamic Social Interactions and Health Risk Behavior," CEPR Discussion Papers 13918, C.E.P.R. Discussion Papers.
    16. Wameq A. Raza & Ellen van de Poel & Arjun Bedi & Frans Rutten, 2016. "Impact of Community‐based Health Insurance on Access and Financial Protection: Evidence from Three Randomized Control Trials in Rural India," Health Economics, John Wiley & Sons, Ltd., vol. 25(6), pages 675-687, June.
    17. Nathalie Mathieu‐Bolh, 2022. "The elusive link between income and obesity," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 935-968, September.
    18. Donal O'Neill, 2015. "Correcting for Self-Reporting Bias in BMI: A Multiple Imputation Approach," Economics Department Working Paper Series n263-15.pdf, Department of Economics, National University of Ireland - Maynooth.
    19. Emily Wang & Christian Rojas & Francesca Colantuoni, 2017. "Heterogeneous Behavior, Obesity, and Storability in the Demand for Soft Drinks," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(1), pages 18-33.
    20. Galina Besstremyannaya, 2014. "Heterogeneous effect of coinsurance rate on healthcare costs: generalized finite mixtures and matching estimators," Discussion Papers 14-014, Stanford Institute for Economic Policy Research.

    More about this item

    Keywords

    obesity; health expenditure; measurement errors; endogeneity; control functions;
    All these keywords.

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

    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:ses:arsjes:2016-iii-3. 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: Kurt Schmidheiny (email available below). General contact details of provider: https://edirc.repec.org/data/sgvssea.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.