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The Medical Care Costs of Mood Disorders: A Coarsened Exact Matching Approach

Author

Listed:
  • Schurer, Stefanie

    (University of Sydney)

  • Alspach, Michael

    (Statistics New Zealand)

  • MacRae, Jayden

    (Compass Health)

  • Martin, Greg L.

    (Victoria University of Wellington)

Abstract

This paper is the first to use the method of coarsened exact matching (CEM) to estimate the impact of mood disorders on medical care costs in order to address the endogeneity of mood disorders. Models are estimated using restricted-use, general practice patient records data from New Zealand for 2009-2012. The CEM model, which exploits a discretization of the data to identify for each patient with a mood disorder a perfect statistical twin, yields estimates of the impact of mood disorders on medical costs that are lower than the estimates obtained from random effects models or conventional matching methods. For example, mood disorders lead to NZ$366 higher annual medical costs (in 2012 dollars) when perfect balancing of covariates is achieved, while minimal and conventional balancing yield estimated costs of over NZ$465 and NZ$400, respectively. The national government expenditures on managing mood disorders is estimated to be 13.4% of total general practice funding (NZ$123 Million) based on CEM.

Suggested Citation

  • Schurer, Stefanie & Alspach, Michael & MacRae, Jayden & Martin, Greg L., 2015. "The Medical Care Costs of Mood Disorders: A Coarsened Exact Matching Approach," IZA Discussion Papers 8814, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp8814
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    References listed on IDEAS

    as
    1. Iacus, Stefano M. & King, Gary & Porro, Giuseppe, 2011. "Multivariate Matching Methods That Are Monotonic Imbalance Bounding," Journal of the American Statistical Association, American Statistical Association, vol. 106(493), pages 345-361.
    2. Ho, Daniel E. & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2007. "Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference," Political Analysis, Cambridge University Press, vol. 15(3), pages 199-236, July.
    3. Berndt, Ernst R. & Finkelstein, Stan N. & Greenberg, Paul E. & Howland, Robert H. & Keith, Alison & Rush, A. John & Russell, James & Keller, Martin B., 1998. "Workplace performance effects from chronic depression and its treatment," Journal of Health Economics, Elsevier, vol. 17(5), pages 511-535, October.
    4. John Roy & Stefanie Schurer, 2013. "Getting Stuck In The Blues: Persistence Of Mental Health Problems In Australia," Health Economics, John Wiley & Sons, Ltd., vol. 22(9), pages 1139-1157, September.
    5. Alan D. Lopez & Colin D. Mathers & Majid Ezzati & Dean T. Jamison & Christopher J. L. Murray, 2006. "Global Burden of Disease and Risk Factors," World Bank Publications - Books, The World Bank Group, number 7039, December.
    6. Andrew M. Jones & Nigel Rice & Pedro Rosa Dias, 2011. "Long-Term Effects of School Quality on Health and Lifestyle: Evidence from Comprehensive Schooling Reforms in England," Journal of Human Capital, University of Chicago Press, vol. 5(3), pages 342-376.
    7. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    coarsened exact matching; national government expenditures; medical care cost; mood disorder; patient record data; general practice;
    All these keywords.

    JEL classification:

    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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