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http://dx.doi.org/10.5351/KJAS.2013.26.2.237

Estimating Automobile Insurance Premiums Based on Time Series Regression  

Kim, Yeong-Hwa (Department of Applied Statistics, Chung-Ang University)
Park, Wonseo (Department of Statistics, Graduate School of Chung-Ang University)
Publication Information
The Korean Journal of Applied Statistics / v.26, no.2, 2013 , pp. 237-252 More about this Journal
Abstract
An estimation model for premiums and components is essential to determine reasonable insurance premiums. In this study, we introduce diverse models for the estimation of property damage premiums(premium, depth and frequency) that include a regression model using a dummy variable, additive independent variable model, autoregressive error model, seasonal ARIMA model and intervention model. In addition, the actual property damage premium data was used to estimate the premium, depth and frequency for each model. The estimation results of the models are comparatively examined by comparing the RMSE(Root Mean Squared Errors) of estimates and actual data. Based on real data analysis, we found that the autoregressive error model showed the best performance.
Keywords
Depth; Durbin-Watson; frequency; insurance; premium; regression; time series;
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