摘要
随着我国经济的高速发展，居民家庭获取金融服务更加高效、便捷，同时对于金融产品与金融服务的需求更加多样化，而2023年4月通过的《中国家庭风险保障体系白皮书》指出，大多数家庭更倾向于选择社会保险的风险管理方式，采用商业保险的风险管理方式较少，此外，家庭居民的资产中房地产与储蓄比例较高，而风险金融资产的配置较少。这种资产配置方式不利于充分发挥家庭风险金融资产的功能，以及提高风险管理能力，学术界从商业保险的角度对家庭风险金融资产的配置的研究较少。因此，本文从商业保险的角度分析家庭居民的风险金融资产的配置。
首先，根据中国家庭金融调查数据（CHFS）的2019的数据进行整理，在不同区域影响下，分析了商业保险与家庭金融资产的发展状况，对研究变量进行选取，构建Probit模型、Tobit模型对风险金融资产持有率及比例的影响进行分析。运用PSM倾向得分匹配、共同支撑假设、平衡性检验进行内生性分析。其次，根据城乡、区域、风险态度的分类进行异质性分析，接着进行稳健性检验。最后，基于以上研究得出结论：第一，我国商业保险参保率较低，家庭风险金融资产配置不均衡。我国购买商业保险的数量占全部样本数13.38%，其中最具代表的两类商业保险，商业人寿与商业健康比例分别为6.77%、5.62%，都远远落后于社会保险95.7%的购买比例。在风险金融资产中，股票、理财、借出款的占比较高，而其他风险金融资产的参与率较低，家庭风险金融资产配置不均衡。第二，持有商业保险的家庭能增加家庭风险金融资产的可能性与比例。通过回归分析以及PSM倾向得分检验，持有商业保险的家庭能增加13.5%的家庭风险金融资产的持有率，提高8.7%的家庭风险金融资产的占比。第三，在异质性回归分析中，农村对家庭风险金融资产的持有率与比例都略高于城镇家庭，中部、西部相对于东部家庭风险金融资产的持有概率与比例较高，风险偏好家庭相较于风险中立、风险厌恶的家庭持有风险金融资产的持有比例高。最后针对问题提出相关对策建议。

关键词：商业保险 风险金融资产配置 倾向得分匹配 

Abstract
With the rapid development of China's economy, households have become more efficient and convenient to obtain financial services, and their demand for financial products and financial services has become more diversified, and the White Paper on China's Family Risk Protection System adopted in April 2023 pointed out that most families are more inclined to choose the risk management method of social insurance, and the risk management method of commercial insurance is less. This asset allocation method is not conducive to giving full play to the function of household risk financial assets and improving risk management capabilities, and there are few studies on the allocation of household risk financial assets from the perspective of commercial insurance. Therefore, this paper analyzes the allocation of risky financial assets of household residents from the perspective of commercial insurance.
Firstly, according to the data of China Household Finance Survey (CHFS) in 2019, the development of commercial insurance and household financial assets was analyzed under the influence of different regions, and the research variables were selected, and the impact of Probit model and Tobit model on the holding and proportion of risky financial assets was analyzed. The endogeneity analysis was carried out by using PSM propensity score matching, co-support hypothesis and equilibrium test. Secondly, heterogeneity analysis was carried out according to the classification of urban and rural, regional and risk attitudes, and then the robustness test was carried out. Finally, based on the above research, it is concluded that: first, the participation rate of commercial insurance in China is low, and the allocation of family risk financial assets is unbalanced. The number of commercial insurance purchases in China accounts for 13.38% of the total sample size, and the two most representative types of commercial insurance, commercial life and commercial health, account for 6.77% and 5.62% respectively, both of which are far behind the purchase ratio of social insurance of 95.7%. Among the risky financial assets, the proportion of stocks, wealth management and loans is relatively high, while the participation rate of other risky financial assets is low, and the allocation of household risky financial assets is unbalanced. Second, households with commercial insurance can increase the likelihood and proportion of their family's risky financial assets. Through regression analysis and PSM propensity score test, households holding commercial insurance can increase the holding rate of household risk financial assets by 13.5% and the proportion of household risk financial assets by 8.7%. Thirdly, in the heterogeneous regression analysis, the holding and proportion of household risk financial assets in rural areas are slightly higher than those of urban households, the probability and proportion of risk financial assets held by households in the central and western regions are higher than those in the east, and the proportion of risk-averse households holding risk-averse financial assets is higher than that of risk-neutral and risk-averse households. Finally, relevant countermeasures and suggestions are put forward for the problem.

Keywords: Commercial insurance; Allocation of risky financial Assets; Propensity score matching