基于分位数自回归模型的健康险保费收入研究

Study on the Health Insurance Premiums Income Based on Quartile Autoregression Model

摘要: 健康险保费收入是度量健康保险业发展情况的关键经济指标。本文结合分位数回归方法对我国1991年1月~2017年6月健康险保费收入的时序数据建模：首先识别了AR(3)模型，之后运用分位数回归方法建立分位数自回归模型，并较准确地拟合出原数据的增减趋势，最后用自回归AR(3)模型和分位数自回归QAR(3)模型分别做短期预测，基于多个评价指标比较两种模型预测效果，结果表明分位数自回归模型预测效果更好。

Abstract: Health insurance premium income is a key economic indicator to measure the development of health insurance industry. In this paper, the time series data of health insurance premium income from January 1991 to June 2017 were modeled with the quantile regression method. Firstly, the model AR(3) was identified, and then the quantile autoregressive model was established by the method of quantile regression, and the increase and decrease trend of the original data was fitted accurately. Finally, the short-term prediction is made by autoregressive AR(3) model and quantile autoregressive QAR(3) model respectively. The prediction results of the two models were compared based on several evaluation indicators. The results show that the quantile autoregressive model is more effective.