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A Flexible Copula Regression Model with Bernoulli and Tweedie Margins for Estimating the Effect of Spending on Mental Health

Marra, G., Fasiolo, M., Radice, R. ORCID: 0000-0002-6316-3961 & Winkelmann, R. (2023). A Flexible Copula Regression Model with Bernoulli and Tweedie Margins for Estimating the Effect of Spending on Mental Health. Health Economics, 32(6), pp. 1305-1322. doi: 10.1002/hec.4668

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.

Publication Type: Article
Additional Information: © 2023 The Authors. Health Economics published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
Publisher Keywords: Binary response; Copula; Health expenditures; Penalized regression spline; Rand experiment; Simultaneous estimation; Tweedie distribution
Subjects: H Social Sciences > HB Economic Theory
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Departments: Bayes Business School > Actuarial Science & Insurance
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