Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/108694
Authors: 
Schurer, Stefanie
Alspach, Michael
MacRae, Jayden
Martin, Greg L.
Year of Publication: 
2015
Series/Report no.: 
IZA Discussion Papers 8814
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.
Subjects: 
mood disorder
medical care cost
national government expenditures
coarsened exact matching
patient record data
general practice
JEL: 
H51
I18
Document Type: 
Working Paper

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