
AbstractThe purpose of the paper is to use the age of claims in the prediction of risks. A dynamic random effects model on longitudinal count data is presented, and estimated on the portfolio of a major Spanish insurance company. The estimated autocorrelation coefficients of stationary random effects are decreasing. A consequence is that the predictive ability of a claim decreases with the lag between the period of risk prediction and the period of occurrence. There is a wide gap between the long term properties of actuarial and real-world experience rating schemes. This gap can be partly filled if the age of claims is taken into account in the actuarial model.
Time-independent and dynamic random effects, Autocorrelation function for stationary random effects, autocorrelation function for stationary random effects, Risk theory, insurance, time-independent and dynamic random effects, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, [SHS.ECO] Humanities and Social Sciences/Economics and Finance, Autocorrelation function for stationary random effects.
Time-independent and dynamic random effects, Autocorrelation function for stationary random effects, autocorrelation function for stationary random effects, Risk theory, insurance, time-independent and dynamic random effects, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, [SHS.ECO] Humanities and Social Sciences/Economics and Finance, Autocorrelation function for stationary random effects.
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