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收入水平、城镇化与寿险需求的非线性门限效应关系研究——基于面板平滑转换回归模型PSTR的检验

Research on the Nonlinear Relationship among Urbanization and Life Insurance Demand——Examination Based on PSTR
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摘要 首次采用面板平滑转换回归模型,并在非线性的框架下对我国30个省份2000—2015年的寿险需求进行分析。在此过程中,我们构建城镇化综合衡量指标,研究收入水平与寿险需求的非线性门限效应并解释不同省份寿险发展不平衡的原因。研究发现,收入水平是影响寿险需求的关键因素,在不同的城镇化过程中,收入增长对寿险需求存在显著的非线性影响;同时,研究发现,综合城镇化水平的差异也是造成不同省份寿险需求发展不平衡的重要原因。其中经济增长、金融发展、教育水平、城镇化率能增强收入增长的寿险需求效应,而社会保障支出则弱化收入的寿险需求效应。说明要促进不同区域保险业的平衡发展需要兼顾收入水平和综合城镇化水平的提高。最后,在此基础上我们提出了现阶段促进保险业均衡发展的若干政策建议和措施。 This paper for the first time uses panel smooth transition regression model to uncover the factors influencing life insurance demand for thirty provinces and regions from 2000 to 2015 with a nonlinear framework. We find that economic income is a key factor affecting insurance demand,and has obvious non- linear effect on the life insurance demand in different urbanization processes. At the same time,the differ- ence between economic income and the level of urbanization is also an important reason for the uneven de- velopment of insurance demand in different provinces,in which economic growth,financial development,edu- cation level,urbanization rate can enhance the income growth of life insurance demand effect,while the social security expenditure will weaken the income of life insurance demand effect. Therefore ,to promote the bal- anced development of the insurance industry in different regions,it is necessary to take into account the e- conomic income and the improvement of the level of urbanization.At last this paper puts forward some mea- sures for policy-makers to ensure the balanced development of the present insurance industry.
作者 黄楚光 黄满佳 HUANG Chuguang HUANG Manjia(School of Economics and Management School of Mathematics and Information, South China Agricultural University, Guangzhou 510006, China)
出处 《广西财经学院学报》 2017年第3期36-51,共16页 Journal of Guangxi University of Finance and Economics
基金 全国统计科研计划项目"非线性动态面板平滑转换回归模型:理论建模与金融应用"(2013LY084)
关键词 收入水平 城镇化 寿险需求 面板平滑转换回归模型 economic income urbanization life insurance demand Panel Smooth Transitional RegressionModel
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