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Article on multivariate Poisson-Generalized Inverse Gaussian (MVPGIG) regression model

How can claims from different types of insurance be optimally bundled and efficiently linked? This question was pursued by Despoina Makariou (University of St. Gallen) together with George Tzougas (Heriot-Watt University) in the recently published article “The multivariate Poisson-Generalized Inverse Gaussian claim count regression model with varying dispersion and shape parameters” in the journal Risk Management and Insurance Review. In it, they presented a claim count regression model with varying dispersion and shape to model different types of claims in non-life insurance. The implementation of the model was demonstrated using bodily injury and property damage count data from a European motor insurer.

Author: Elisabeth Heidecke

Date: 24. October 2022