A flexible copula regression model with Bernoulli and Tweedie margins for estimating the effect of spending on mental health. (1st March 2023)

• Record Type: Journal Article
• Authors: Marra, Giampiero; Fasiolo, Matteo; Radice, Rosalba; Winkelmann, Rainer
• Is Part Of: Health economics. Volume 32:Number 6(2023)
• Page Start: 1305
• Page End: 1322
• Publication Date: 2023-03-01
• Subjects: binary response -- copula -- health expenditures -- penalized regression spline -- Rand experiment -- simultaneous estimation -- Tweedie distribution; Medical economics -- Periodicals; Economics, Medical -- Periodicals; Health Care Costs -- Periodicals; Health Policy -- economics -- Periodicals; Health Services -- economics -- Periodicals; 362.1
• DOI: 10.1002/hec.4668
• Languages: English
• ISSNs: 1057-9230

Abstract

Abstract: We develop a flexible two‐equation copula model to address endogeneity of medical expenditures in a distribution regression for health. The expenditure margin uses the compound gamma distribution, a special case of the Tweedie family of distributions, to account for a spike at zero and a highly skewed continuous part. An efficient estimation algorithm offers flexible choices of copulae and link functions, including logit, probit and cloglog for the health margin. Our empirical application revisits data from the Rand Health Insurance Experiment. In the joint model, using random insurance plan assignment as instrument for spending, a $ 1000 increase is estimated to reduce the probability of a low post‐program mental health index by 1.9 percentage points. The effect is not statistically significant. Ignoring endogeneity leads to a spurious positive effect estimate.