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

Stefanie Schurer, Michael Alspach, Jayden MacRae and Greg L. Martin
Additional contact information
Michael Alspach: Statistics New Zealand
Jayden MacRae: Compass Health
Greg L. Martin: Victoria University of Wellington

No 8814, IZA Discussion Papers from Institute of Labor Economics (IZA)

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.

Keywords: coarsened exact matching; national government expenditures; medical care cost; mood disorder; patient record data; general practice (search for similar items in EconPapers)
JEL-codes: H51 I18 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2015-01
New Economics Papers: this item is included in nep-hea
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Published - published in: Economic Record, 2016, 92 (296), 81–93

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Journal Article: The Medical Care Costs of Mood Disorders: A Coarsened Exact Matching Approach (2016)
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