Risk Attitude, Financial Knowledge and Commercial Life Insurance Needs

This paper uses the 2015 China Household Finance Survey (CHFS) to study the impact of risk attitudes and financial knowledge on household business life insurance demand from a micro perspective. By constructing the Probit and Tobit models, it is found that risk-averse families will reduce the demand for life insurance, and the increase in financial knowledge will significantly increase the participation and depth of family life insurance. It is possible to purchase commercial life insurance, and its life insurance premium expenditure industry is more. Finally, this article puts forward suggestions for promoting the development of China’s commercial life insurance from the perspective of popularizing financial knowledge and providing different insurance products for different risk attitudes. of attitudes and financial knowledge on household business life insurance demand. The results show that increased risk aversion has dampened the demand for family life insurance, and increased financial knowledge has promoted the purchase of family life insurance. Further research also found that the degree of risk aversion has a significant negative impact on the depth of life insurance participation, and financial knowledge has a significant positive impact on the depth of life insurance participation, that is, families with a higher risk appetite or families with a higher level of financial knowledge. The average annual premium expenditure is also higher. In addition,

In the past, the demand for commercial life insurance was mainly studied from the aspects of population structure and family wealth. This article mainly considers the impact of family's subjective risk attitude and financial knowledge on the demand for life insurance. Risk attitude is a variable that has fundamental significance to insurance demand. In the decision of household asset allocation, risk attitude often plays an important role. According to different risk attitudes, it can be divided into three types: risk preference, risk neutral and risk aversion.
Gusio and Paiella (2008) research found that risk aversion reduces the allocation of risk assets [1]. Unlike the traditional theory that risk aversion people will choose to purchase commercial insurance to avoid risks, He Xingqiang and Li Tao (2009) risk attitude is significantly positively related to the demand for household commercial insurance [2]. In addition, financial knowledge also plays an important role in household financial decision-making. Rooij et al. (2011) found that lack of financial knowledge will reduce household participation in the stock market [3]. Gerrans et al. (2017) pointed out that many people who cannot accept the right financial advice and do not understand their financial knowledge level often make irrational financial decisions [4]. And financial knowledge is not the same as education level, nor can we simply equate finance with financial knowledge. So how does risk attitude and financial knowledge affect the demand for commercial life insurance in China? Therefore, this paper uses the 2015 China Household Finance Survey data to study its impact on household business life insurance demand from two perspectives: risk attitude and financial knowledge.
Therefore, this paper uses the principal component factor method to construct financial knowledge variables, and constructs a Probit model to explore The rest of the paper is organized as follows: Section 2 introduces the literature review, Section 3 describes the samples and variables used in this article, Section 4 gives the regression model and regression results, and Section 5 concludes.

Literature Review
Research on the impact on the demand for commercial life insurance has always been one of the key areas of concern for economic and financial scientists, and it is also one of the hot topics in the research of insurance theory in China.

Demographic Factors and Demand for Life Insurance
In 1989, Lewis introduced family structure as an influencing factor for the first time in the model [5]. Brown and Kim (1993) Truett and Truett (1990) compared the factors influencing life insurance demand in Mexico and the United States and found that the income elasticity of Mexican life insurance demand is more than three times that of the United States [11]. Showers and Shotick (1994) found that household income, household size, and head age were significantly positively related to insurance demand

Subjective Attitude Factors and Demand for Life Insurance
The earliest empirical research by Greene (1963) found that there was no significant correlation between risk attitudes and life insurance demand [15]. Outreville (2014) reviewed relevant literature on the impact of risk attitudes on insurance demand [16]. Burnett and Palmer (1984) examined the impact of multiple subjective psychological factors on the demand for life insurance and found that traditional professional ethics, fatalism, social preferences, religious beliefs and self-confidence significantly affect the demand for life insurance [17]. In addition, many studies have found that the higher the residents' computing power and financial literacy, the higher their probability of participating in the stock market [18] [19]. A survey of Portuguese investors by Abreu and Mendes (2010) found that residents with a higher education level and higher financial literacy would better understand the decentralization of investment [20]. In terms of debt decision-making, Hilgert, Hogarth and Beverly (2003) found that respondents with low financial literacy were less likely to return credit card debts in a timely manner, and fewer people made financial budgets [21].

Samples and Variables
The microdata used in this article are from the China Household Finance Survey It can be seen from Table 1  It can also be seen from Table 2  if the respondent responds to 4) a project with slightly lower risk and slightly lower return or 5) is unwilling to take on any risk, we consider it to be a risk-averse person and assign a value of 3. As the value increases, it indicates that respondents' risk It can be seen from Table 4 that the degree of attention and participation of Chinese residents in financial knowledge is very low. The number of households who never pay attention to economic and financial information is the largest, reaching 37.84%, while only 3.39% and 7.21% of the families are very concerned  (Table 6). According to the KMO test results in Table 7, the KMO value is 0.6480, which is greater than 0.6, and the P value of the Bartlett spherical test result is 0, which can be used for factor analysis. Then judge according to the size of the characteristic value in Table 5, choose Factor 1, Factor 2, and Factor 3 greater than 1 to measure financial knowledge. Table 8 Table 9.

Empirical Analysis
This

Risk Attitude, Financial Knowledge and Participation in Commercial Life Insurance
Using the above data and variables, in order to verify the impact of risk attitude and financial knowledge on the purchase decision of commercial life insurance, this paper builds the following Probit model:  Table 10 shows the Probit model of the impact of risk attitudes and financial knowledge on household business life insurance holdings.
The results in the first column of Table 10 indicate that the risk attitude has a significantly negative effect on the demand for family life insurance, that is, as the degree of risk aversion increases, the family's demand for commercial life insurance decreases. Smaller-risk family lifestyles require less risk and are more willing to hold money in their hands, and the demand for life insurance will also be lower. The results of the second column show that financial knowledge has a positive impact on the demand for family life insurance. It can be seen that increasing the popularity of financial knowledge is very important to increase the participation of commercial life insurance. From the perspective of controlling variables, the total family dependency ratio and the child dependency ratio have opposite effects on family life insurance demand. On the one hand, the higher the proportion of children aged 14 and under, the greater the demand for family life insurance. In order to protect and protect the children in the family, worrying that children's life and education will not be guaranteed when the family encounters a change, so they are more inclined to purchase life insurance for themselves. The total dependency ratio has a suppressive effect on the demand for life insurance. This is mainly because the elderly population in the family cannot participate in life insurance purchases because they are older than a certain age or suffer from certain diseases, which has curtailed the demand for life insurance products. From the personal characteristics of the head of household, the higher the education level of the head of household, the greater the demand for life insurance products; the coefficient of the primary term of the head of the household is significantly positive, and the coefficient of the quadratic term is significantly negative; The effect of gender on life insurance demand is significantly negative, indicating that female heads of households have greater demand for life insurance. As far as the family's financial situation is concerned, the average annual household income, household net assets and the proportion of financial assets in total assets will affect the ability to pay for insurance, thereby promoting participation in life insurance. At the same time, the demand for life insurance in rural households is much smaller than

Risk Attitude, Financial Knowledge and Depth of Participation in Commercial Life Insurance
In this article, the average annual household premium expenditure is used to measure the depth of participation of family life insurance. Since the family premium expenditure of non-purchased life insurance is 0, that is, the dependent variable data is truncated, the Tobit model is used to estimate the risk attitude and financial knowledge for family life insurance the impact of engagement depth.  (1). The regression results are shown in Table 11.
As can be seen from Table 11

Conclusions and Implications
Based  an increase in the average annual household income, an increase in the family's net assets, and an increase in the proportion of financial assets in total assets will promote the family's demand for commercial life insurance. The family dependency ratio, the age, gender, and education level of the head of households also contribute to family life insurance. Participation and depth of participation have important implications. Based on the research conclusions of this paper, two suggestions are made for the development of China's commercial life insurance: First, the government and financial institutions should increase the education and popularization of financial knowledge, increase the promotion and promotion of financial knowledge, and organize professionals to conduct financial knowledge explanation, improve the enthusiasm and initiative of residents to learn financial knowledge, so as to increase the participation and depth of households in commercial life insurance. Second, consider the differences in family attitudes to risk, and recommend and explain different types of commercial life insurance, make full use of insurance protection and investment functions, and ensure that families with various risk attitudes actively participate in the rational and scientific purchase of commercial life insurance. China, thus promoting the healthy development of China's insurance industry.
In addition, due to the limited data, the research in this paper also has certain limitations. The impact of family risk attitudes on the demand for life insurance is significantly negative, that is, the increase in risk aversion has suppressed the demand for life insurance. The characteristics of insurance with insurable functions are inconsistent. This may be due to the impact of different risk attitudes on different types of insurance. Further research requires more detailed data, which is also the direction of our further research.

Conflicts of Interest
The author declares no conflicts of interest regarding the publication of this paper.