1. A flexible copula regression model with Bernoulli and Tweedie margins for estimating the effect of spending on mental health
- Author
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Marra, G., Fasiolo, M., Radice, R., Winkelmann, R., University of Zurich, and Winkelmann, Rainer
- Subjects
History ,binary response ,Polymers and Plastics ,Health Policy ,HB ,I13 ,simultaneous estimation ,2719 Health Policy ,Industrial and Manufacturing Engineering ,330 Economics ,Tweedie distribution ,co ,co-payment ,ECON Department of Economics ,payment ,10007 Department of Economics ,ddc:330 ,copula ,penalized regression spline ,health expenditures ,Business and International Management ,C31 ,Rand experiment ,RA - Abstract
Previous evidence shows that better insurance coverage increases medical expenditure. However, formal studies on the effect of spending on health outcomes, and especially mental health, are lacking. To fill this gap, we reanalyze data from the Rand Health Insurance Experiment and estimate a joint non-linear model of spending and mental health. We address the endogeneity of spending in a flexible copula regression model with Bernoulli and Tweedie margins and discuss its implementation in the freely available GJRM R package. Results confirm the importance of accounting for endogeneity: in the joint model, a $1000 spending in mental care is estimated to reduce the probability of low mental health by 1.3 percentage points, but this effect is not statistically significant. Ignoring endogeneity leads to a spurious (upwardly biased) estimate.
- Published
- 2023