Abstract
The article proposes a combination of finite mixture models and matching estimators to account for heterogeneous and nonlinear effects of the coinsurance rate on healthcare expenditure. The analysis with panel data for adult Japanese consumers in 2008–2010 and for female consumers in 2000–2010 demonstrates the presence of subpopulations with high, medium and low healthcare expenditure, and subpopulation membership is explained by lifestyle variables. Generalized finite mixtures provide adequate fit compared to loglinear model. Conditional average treatment effect estimations reveal the existence of nonlinear effects of the coinsurance rate in the subpopulation with high expenditure.
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