Heterogeneous effect of coinsurance rate on healthcare costs: generalized finite mixtures and matching estimators

The paper proposes a combination of finite mixture models and matching estimators to account for heterogeneous and nonlinear effects of the coinsurance rate on healthcare expenditure. We use loglinear model and generalized linear models with different distribution families, and measure the conditional average treatment effect of a rise in the coinsurance rate in each component of the model. The estimations with panel data for adult Japanese consumers in 2008-2010 and for female consumers in 2000-2010 demonstrate the presence of subpopulations with high, medium and low healthcare expenditure, and subpopulation membership is explained by lifestyle variables. Generalized linear models 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.