IDEAS home Printed from
   My bibliography  Save this article

What determines health: a causal analysis using county level data


  • Andrew Rettenmaier
  • Zijun Wang



This article revisits the long-standing issue of the determinants of health outcomes. We make two contributions to the literature. First, we use a large and comprehensive US county level health data set that has only recently become available. This data set includes five measures of health outcomes and 24 health risk factors in the categories of health behaviors, clinical care, social and economic factors, and physical environment. Second, to distinguish causality from correlation, we implement an emerging data-driven method to study the causal factors of health outcomes. Among all included potential health risk factors, we identify adult smoking, obesity, motor vehicle crash death rate, the percent of children in poverty, and violent crime rate to be major causal factors of premature mortality. Adult smoking, preventable hospital stays, college or higher education, employment, children in poverty, and adequacy of social support determine health-related quality of life. Finally, the Chlamydia rate, community safety, and liquor store density are three important factors causally related to low birth weight. Policy implications of these findings are discussed. Copyright Springer-Verlag 2013

Suggested Citation

  • Andrew Rettenmaier & Zijun Wang, 2013. "What determines health: a causal analysis using county level data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(5), pages 821-834, October.
  • Handle: RePEc:spr:eujhec:v:14:y:2013:i:5:p:821-834
    DOI: 10.1007/s10198-012-0429-0

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Alessio Moneta, 2008. "Graphical causal models and VARs: an empirical assessment of the real business cycles hypothesis," Empirical Economics, Springer, vol. 35(2), pages 275-300, September.
    2. Selva Demiralp & Kevin D. Hoover & Stephen J. Perez, 2008. "A Bootstrap Method for Identifying and Evaluating a Structural Vector Autoregression," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(4), pages 509-533, August.
    3. Michaud, Pierre-Carl & van Soest, Arthur, 2008. "Health and wealth of elderly couples: Causality tests using dynamic panel data models," Journal of Health Economics, Elsevier, vol. 27(5), pages 1312-1325, September.
    4. Jérôme Adda & James Banks & Hans-Martin von Gaudecker, 2009. "The Impact of Income Shocks on Health: Evidence from Cohort Data," Journal of the European Economic Association, MIT Press, vol. 7(6), pages 1361-1399, December.
    5. Christopher J. Ruhm, 2000. "Are Recessions Good for Your Health?," The Quarterly Journal of Economics, Oxford University Press, vol. 115(2), pages 617-650.
    6. Robert Moffitt, 2005. "Remarks on the analysis of causal relationships in population research," Demography, Springer;Population Association of America (PAA), vol. 42(1), pages 91-108, February.
    7. Michael S. Haigh & David A. Bessler, 2004. "Causality and Price Discovery: An Application of Directed Acyclic Graphs," The Journal of Business, University of Chicago Press, vol. 77(4), pages 1099-1121, October.
    8. John Nixon & Philippe Ulmann, 2006. "The relationship between health care expenditure and health outcomes," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 7(1), pages 7-18, March.
    9. David A. Bessler & Derya G. Akleman, 1998. "Farm Prices, Retail Prices, and Directed Graphs: Results for Pork and Beef," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 80(5), pages 1144-1149.
    10. Clive W. J. Granger, 2005. "Modeling, Evaluation, and Methodology in the New Century," Economic Inquiry, Western Economic Association International, vol. 43(1), pages 1-12, January.
    11. David Bessler & Zijun Wang, 2012. "D-separation, forecasting, and economic science: a conjecture," Theory and Decision, Springer, vol. 73(2), pages 295-314, August.
    12. Wang, Zijun & Yang, Jian & Li, Qi, 2007. "Interest rate linkages in the Eurocurrency market: Contemporaneous and out-of-sample Granger causality tests," Journal of International Money and Finance, Elsevier, vol. 26(1), pages 86-103, February.
    13. Frijters, Paul & Haisken-DeNew, John P. & Shields, Michael A., 2005. "The causal effect of income on health: Evidence from German reunification," Journal of Health Economics, Elsevier, vol. 24(5), pages 997-1017, September.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. Hope Corman & Dhaval M. Dave & Nancy E. Reichman, 2017. "Evolution of the Infant Health Production Function," NBER Working Papers 24131, National Bureau of Economic Research, Inc.
    2. Dharmasena, Senarath & Bessler, David A. & Capps, Oral, 2016. "Food environment in the United States as a complex economic system," Food Policy, Elsevier, vol. 61(C), pages 163-175.

    More about this item


    Health outcomes; Risk factors; Causal analysis; Directed graphs; US county data; I10;

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General


    Access and download statistics


    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:spr:eujhec:v:14:y:2013:i:5:p:821-834. 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: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: .

    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.