Flexible (panel) regression models for bivariate count-continuous data with an insurance application

Yang Lu

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Abstract: We propose a flexible regression model that is suitable for mixed count-continuous panel data. The model is based on a compound Poisson representation of the continuous variable , with bivariate random effect following a polynomial-expansion-based joint density. Besides the distributional flexibility that it offers, the model allows for closed form forecast updating formu-lae.This property is especially important for insurance applications, in which the future individual insurance premium should be regularly updated according to one's own past claim history. An application to vehicle insurance claims is provided.

Keywords: Mixed data; Sequential forecasting and pricing; polynomial expansion; random effect; sequential forecast- ing/pricing (search for similar items in EconPapers)
Date: 2019
New Economics Papers: this item is included in nep-ecm, nep-for and nep-ias
Note: View the original document on HAL open archive server: https://hal.science/hal-02419024
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Citations: View citations in EconPapers (4)

Published in Journal of the Royal Statistical Society: Series A Statistics in Society, 2019

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Journal Article: Flexible (panel) regression models for bivariate count–continuous data with an insurance application (2019)
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