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Abstract

China implements different social endowment insurance policies between urban and rural areas which may cause differences in investment decisions of urban and rural households. Based on the 2013 to 2017 China Household Finance Survey (CHFS) data and the two-way fixed effect panel model, this study aims to investigate the effect of social endowment insurance on the inequality of household portfolio between China’s urban and rural areas and the moderating effect of financial literacy on the relationship between social endowment insurance and household portfolio. The empirical results show that (1) the participation of social endowment insurance is positively related to the possibility of holding risky financial assets and the ratio of risky financial assets; (2) the effect of social endowment insurance is strong and significant in urban areas but weak and not significant in rural areas; (3) the moderating effect of financial literacy on the relationship between social endowment insurance and household portfolio widens the gap of the household portfolio between the urban and rural areas. This paper indicates that the social endowment insurance would affect the household portfolio decisions positively and the financial literacy positively moderates the relationship between social endowment insurance and household portfolio, which just can be applied to urban households. This paper provides evidence of the inequality between the urban and rural households in China and discusses the possible causes of the urban-rural income gap.

Keywords

social endowment insurance financial literacy household portfolio inequality

Introduction

The scale of household wealth in China has expanded, but there is a large gap between urban and rural household wealth. Participating in social endowment insurance can prompt residents to change family investment decisions, reduce preventive savings, increase risky financial asset holdings, and expand family wealth (Feldstein, 1974). Basic social endowment insurance is a social insurance system established by the People’s Republic of China in accordance with the relevant laws and regulations to cover the basic livelihood of workers after they have reach the working age limit set by the State for being relieved of their labor obligations or after they have withdrawn from work due to incapacity in old age. The aim is to use social insurance as a means to safeguard the basic needs of the elderly and provide them with a stable and reliable source of livelihood. China’s endowment insurance consists of four levels. The first level is the basic pension insurance, the second level is the enterprise supplementary pension insurance, the third level is the individual savings pension insurance and the fourth level is the commercial pension insurance. In this multi-level social endowment insurance system, the basic endowment insurance can be called the first level and the highest level. The structure of China’s social endowment insurance system can be divided into three major parts according to the type of population: urban enterprise employees’ endowment insurance, public institutions’ endowment insurance and rural endowment insurance. In 2014, China merged the New Rural Social Endowment Insurance with the Social Endowment Insurance for Urban Residents and implemented the “basic endowment insurance for urban and rural residents” (BEIURR) aimed at alleviating the gap in wealth between urban and rural households (Wu & Yuan, 2016). However, due to the differences in the level of financial literacy between urban and rural residents, BEIURR may not have the effect of narrowing the gap between urban and rural household wealth (Dong & Shi, 2019). Based on the China Household Finance Survey (CHFS) data, we examine the impact of China’s social basic endowment insurance on the household portfolio of Chinese urban and rural residents, and analyze the role of financial literacy in it.

The China Economic Daily reported that the scale of Chinese household assets had expanded, the per capita asset scale of Chinese households reached 30,000 US dollars in 2017 and the average annual growth rate of household assets per capita from 2013 to 2017 was 9.71%. However, compared with other developed countries, Chinese households allocate too many risk-free financial assets. In 2017, Chinese households’ risk-free financial assets (including cash, demand deposits, time deposits, etc.) accounted for more than 50% of total household financial assets (including risk-free financial assets and risky financial assets such as stocks, bonds, funds, etc.) (Han, 2018) This indicator was only 13.6% in American households (Board of Governors of the Federal Reserve System, 2020) and 34.4% in EU households (European Central Bank, 2020). It is worth noting that the problem of irrational allocation of household financial assets structure is more prominent among Chinese rural households. Compared with urban households, rural households have a higher proportion of risk-free financial assets, and rural households’ financial assets are more concentrated on low-risk and low-yield deposits (Han, 2018).

The social endowment insurance is an important factor in the process of decision-making of household portfolio. According to the life cycle theory proposed by Feldstein (1974), social endowment insurance can mitigate the impact of background risks (Gormley et al., 2010), change household investment decisions, reduce precautionary savings, and increase risk asset holdings ((Dicks-Mireaux & King, 1983).But the conclusions are affected by many micro-level heterogeneities (Delavande & Rohwedder, 2011; Sun et al., 2020). For example, many scholars believe that China’s social basic endowment insurance system plays different roles on household portfolio between urban and rural areas (Liang et al., 2020; Zong et al., 2015). Therefore the BEIURR may not achieve its purpose of coordinating urban and rural development but widen the gap between urban and rural household assets.

In addition to the social endowment insurance, financial literacy is also an important factor affecting household portfolio. The higher the level of residents’ financial literacy, the more inclined to obtain higher risk investment income by formulating pension plans and allocating a higher proportion of risky assets to maintain their living after retirement (Dohmen et al., 2010; Lusardi & Mitchell, 2011). It is common that China’s rural residents have lower level of financial literacy (Behrman et al., 2012). Perhaps financial literacy is not only the factor affecting the decision-making of household portfolio between urban and rural families but the reason for underutilized of BEIURR.

Therefore, this paper explores the impact of social endowment insurance on the decision-making of household portfolio between urban and rural families from the perspective of financial literacy and aims to verify the following questions: (1) the effect of social endowment insurance on the decision-making of household portfolio between urban and rural families in China; (2) the effect of financial literacy on the decision-making of household portfolio between urban and rural families in China; (3) the moderating effect of financial literacy on the relationship of social endowment insurance and household portfolio.

Literature Review

The research on the factors influencing household portfolio mainly focuses on individual heterogeneity and background risk.

Health risks and labor income risks in background risks are significant factors that affect household portfolio decisions. As far as health risks are concerned, the decline in health status means the increase of health risks would reduce the proportion of households’ risky assets in total assets (Berkowitz & Qiu, 2006). Besides, the impact is significant among Chinese urban families (Lei & Zhou, 2010). What worth mentioning is that the index of health status is usually measured by the subjective evaluation index (self-evaluated health). Because individual investment decisions were generally affected by their subjective health cognition (Adams et al., 2003). This view was confirmed in subsequent studies. Bressan et al. (2014) mentioned that the self-evaluated health index rather than the objective evaluation index (limitations in activities of daily living and chronic diseases) had a negative effect on household portfolio choice. As far as labor income risks are concerned, groups with higher income uncertainty are more risk-averse (Guiso & Paiella, 2008). The risk-aversion raises the precautionary saving rates and reduces the ratio of risky assets for China’s urban households (Chamon et al., 2013).

Social security reduces health risks and labor income risks in background risks through medical insurance, pension, and other social welfare policy, and encourages residents to hold more risky financial assets (Atella et al., 2012). But the effect is affected by heterogeneous factors. Zhou et al. (2015) noted that China’s medical insurance positively affected the proportion of risky financial assets in total assets for urban households, while negatively affected the proportion of risky financial assets in total assets for rural households (Zhou et al., 2015). Because China’s farmers have been influenced by the traditional mindset of making a living just by farming, the insured rural households would rather purchase more agricultural equipment rather than invest. Many scholars believed that social basic endowment insurance would significantly increase the probability of holding risky financial assets and the proportion of risky financial assets for urban households (Li & Yang, 2021; Zong et al., 2015). However, the effect of social endowment insurance on household portfolio choice for Chinese rural families are controversial. Zong et al. (2015) believed that the New Rural Social Endowment Insurance had a weak effect on the household asset allocation behaviors for Chinese rural families. But Boughton et al. (2007) noted that the ratio of risky financial assets in total household assets and the probability of participating in the risky financial market had increased when rural families insured the New Rural Social Endowment Insurance. Therefore, whether social endowment insurance affects Chines rural households’ portfolio remains controversial. Furthermore, we haven’t seen the empirical analysis of the reasons for the effect of social endowment insurance on the urban and rural household portfolios.

There are many factors of individual heterogeneity affecting household portfolio choices. These factors influence the investment decisions through three ways: risk affordability, risk preference, and risk awareness. The increase of other household assets such as real estate enhances the family’s risk affordability and encourages families to participate in the risky financial market and holding more risky financial assets (Cardak & Wilkins, 2009; Jang & Abdel-Ghany, 2000; Tin, 1998). Age is an important factor affecting risk preference. The adventurous young people prefer to invest in risky financial assets while the elder prefer conservative investment (McCarthy, 2004). Education (Behrman et al., 2012), cognitive ability (Christelis et al., 2010) and other personal characteristics (Bucciol & Zarri, 2017) affect the household portfolio choices significantly through risk awareness. Financial literacy affects household portfolio decisions by influencing individuals’ risk preference and risk awareness. The higher the level of households’ financial literacy, the more risk they prefer (Dohmen et al., 2010). The investors with better financial literacy invest rationally because they have a clear understanding of financial risks (Lu et al., 2020). Compared with the rural residents in China, the urban residents generally have a higher level of financial literacy and a stronger awareness of investment. They may consider the function of risk diversification from social endowment insurance when making investment decisions, and thus are more inclined to invest in risky financial assets. As a result, the wealth gap between urban and rural households has further widened.

In summary, due to the gap in the level of financial literacy, social endowment insurance may increase the household wealth gap between China’s urban and rural families by influencing household portfolio choices. But no scholars have yet conducted relevant research on this issue. Therefore, the paper intends to discuss the differences in investment decisions of Chinese urban and rural households before and after participating in social endowment insurance and their reasons from the perspective of financial knowledge and propose relevant policy recommendations accordingly.

Research Methodology

Data

The data used in this study comes from three rounds of household financial surveys conducted by the China Household Finance Survey (CHFS) and Research Center of Southwestern University of Finance and Economics from 2013 to 2017. In 2013, the survey samples were distributed in 29 provinces (cities, districts), 262 counties, 1,048 village (residential) committees, and 28,000 households. The survey samples in 2015 and 2017 were distributed in 29 provinces (cities, districts), 363 counties, 1,439 village (neighborhood) committees, and 40,000 households in total. The data involved various relevant information of micro-households from 2013 to 2017, including household assets, liabilities and credit constraints, income, consumption, social security and insurance, demographic characteristics, employment, and payment habits (CHFS, 2018).

Variables

The purpose of this study is to explore the differences in the impact of social endowment insurance and financial literacy on the allocation of risky financial assets of urban and rural households. We use “whether to hold risk assets” and “the proportion of risk assets held” to measure the allocation of household risk assets from the perspective of extensive margin and intensive margin. According to the data characteristics of CHFS, we divide household financial assets into risk-free assets and risky assets. Risk-free financial assets include the sum of cash, time deposits and demand deposits. Risky financial assets include the total market value of stocks, funds, bonds, financial derivatives (futures, warrants and other financial derivatives), bank wealth management products and non-RMB assets. The CHFS survey data also included risky financial assets such as Internet wealth management since 2015. However, in order to maintain the consistency of the classification standards, this study does not include them. CHFS has interpolated the missing data of many asset variables, including the amount of cash held, total time deposits, current market value of stocks, total market value of funds currently owned, bonds, total financial derivatives, total bank wealth management products and total non-RMB assets, this study uses the data after interpolation processing.

The core explanatory variables are social endowment insurance and financial literacy. We use “Whether to participate in social endowment insurance, yes = 1, no = 0” as the proxy variable of social endowment insurance; “How much do you pay attention to economic and financial information? Never pay attention = 1, rarely pay attention = 2, Generally = 3, Very Concerned = 4, Very Concerned = 5” as the proxy variable of financial knowledge. As long as you have one of the social basic endowment insurance including the basic endowment insurance for civil servants and public sector employees(BEICSPSE), the basic endowment insurance for urban enterprise employees(BEIUEE), the new rural social endowment insurance(NRSEI) and the social endowment insurance for urban residents(SEIUR), we regard it as having social basic endowment insurance. In the questionnaires about social endowment insurance in 2015 and 2017, there is an answer option of “the basic endowment insurance for urban and rural residents.” Consider that the participation of Chinese residents in basic endowment insurance is restricted by their household registration, we choose the population of this option is divided by household registration, the population of “agricultural household registration” is merged into “the new rural social endowment insurance,” and the population of “urban household registration” is merged into “the social endowment insurance for urban residents.” There are many definitions of financial literacy in the existing literature, mainly subjective financial literacy indicators and objective financial literacy indicators to measure it. Data from the 2013, 2015, and 2017 China Household Financial Surveys (CHFS), the questions in the questionnaire related to financial literacy are multifaceted and vary across years. In order to ensure the consistency of data across multiple studies, and drawing on existing research, we finally choose to use the subjective financial information concern to measure financial literacy. Allgood and Walstad (2016) find that the impact of subjective financial literacy on residents’ household financial behavior is as important as the impact of objective financial literacy on residents’ household financial behavior. Here, this paper argues that financial information can be used as a substitute for financial literacy for the following reasons: the Spearman correlation coefficient showed that the two showed a high correlation; OlS regression showed a very significant correlation between the two.

The participation of social endowment insurance and financial literacy may be related to many other household heterogeneous characteristics, and these household heterogeneous characteristics may directly affect the household portfolio choices. If we omit these heterogeneous characteristics, it will lead to omitted variable deviations. Therefore, the control variables we choose include: age of the head of household, marital status (married or not), subjective risk preference attitude, annual family income, whether the family is in debt, whether the family owns a house, the number of elderly over 60, and the number of children under 10. The question about risk preference attitude in the questionnaires is: “If you have a certain amount of capital for investment, which investment project are you most willing to choose? 1. High-risk and high-return projects; 2. Slightly higher-risk and slightly higher-return projects; 3. Projects with average risk and average return; 4. Projects with slightly lower risk and lower return; 5. Unwilling to take any risks; 6. Don’t know,” refer to Zong et al. (2015) and Wu and Yuan (2016), we define options 1 and 2 as “investment risk appetite,” option 3 as “investment risk neutral,” and options 4 and 5 as “investment risk aversion.” The 2015 and 2017 household questionnaires contain official total household debts. Therefore, in the next two periods, we use this indicator to generate a dummy variable of whether the household is in debt. There is no such variable in the household questionnaire in 2013. Based on the variable description of the total household debt in 2015 and 2017, the household has “"agricultural debt, industrial and commercial debt, real estate debt, vehicle debt, other non-financial, asset liabilities, Equity liabilities, other financial asset liabilities, education liabilities, medical liabilities and other liabilities”. Any one of the liabilities in “is deemed as the family has liabilities.”

In addition, we screened the samples: (1) Excluding families who have received pensions and whose heads of households are under 16 and over 60 years old, because these samples will not face the decision of whether to participate in social endowment insurance; (2) The abnormal samples whose annual household income is less than 0 in the database are eliminated; (3) The samples that do not hold any financial assets are deleted because these families do not Financial assets will not face the problem of asset portfolio allocation. Finally, the households visited in 2013, 2015, and 2017 were merged into three phases of panel data, and finally 7,442 households were retained, including 4,790 urban households and 2,652 rural households.

Descriptive Evidence

Table 1 shows the descriptive statistics of the main variables. The independent variable “insurance” means 74.6% of households in the sample have social endowment insurance. Specifically, 72.30% of the rural group in the sample had social endowment insurance, compared to 75.84% of the urban group. In terms of “risky assets,” 15.5% of households in the full sample hold risky financial assets, and “ratio of risky assets” means risky financial assets account for an average of 7.4% in total samples. In the sample of household heads with social endowment insurance, 18% of households hold risky assets, and the average proportion of risky assets is 8.8%, while only 8.3% of households without social endowment insurance choose to hold risky assets in the sample and the average proportion of risky assets is 3.3%, which shows that there are certain differences in risky assets allocation between families with and without social endowment insurance. But this phenomenon may also be caused by the differences in other aspects. Whether participation in social endowment insurance has an effect on household portfolio choices needs further analysis.

Table 1.

Descriptive Statistics of Main Variables.

Variables	Total	No-joined	Joined
Variables	Total	No-joined	Total	BEICSPSE	BEIUEE	SEIUR	NRSEI
Dependent variable
Risky assets	0.155	0.083	0.180	0.347	0.329	0.196	0.040
Risky assets	(0.362)	(0.276)	(0.384)	(0.476)	(0.470)	(0.397)	(0.196)
Ratio of risky assets	0.074	0.033	0.088	0.173	0.168	0.095	0.014
Ratio of risky assets	(0.214)	(0.143)	(0.231)	(0.301)	(0.300)	(0.238)	(0.092)
Core independent variable
Insurance	0.746 (0.436)	-	-	-	-	-	-
Financial literacy	2.208 (1.080)	2.051 (1.051)	2.261 (1.086)	2.574 (1.074)	2.462 (1.050)	2.210 (1.053)	2.074 (1.082)
Control variables
Age of head	45.553 (8.042)	43.888 (8.525)	46.121 (7.790)	46.154 (8.265)	44.546 (8.575)	45.943 (7.326)	47.286 (6.951)
No-education	0.026 (0.158)	0.041 (0.198)	0.020 (0.142)	0.000 (0.000)	0.001 (0.034)	0.011 (0.103)	0.040 (0.197)
Primary school	0.182	0.253	0.158	0.019	0.033	0.102	0.283
Primary school	(0.386)	(0.435)	(0.364)	(0.136)	(0.179)	(0.302)	(0.450)
Middle school	0.391	0.454	0.370	0.127	0.228	0.416	0.504
Middle school	(0.488)	(0.498)	(0.483)	(0.334)	(0.419)	(0.493)	(0.500)
High school	0.178	0.132	0.193	0.183	0.254	0.257	0.139
High school	(0.382)	(0.338)	(0.395)	(0.387)	(0.436)	(0.437)	(0.346)
Technical secondary school	0.050	0.039	0.054	0.063	0.099	0.066	0.019
Technical secondary school	(0.219)	(0.193)	(0.227)	(0.244)	(0.299)	(0.248)	(0.135)
Junior college	0.091	0.046	0.106	0.238	0.206	0.096	0.012
Junior college	(0.287)	(0.209)	(0.307)	(0.426)	(0.404)	(0.295)	(0.109)
Bachelor	0.074	0.031	0.089	0.326	0.161	0.048	0.003
Bachelor	(0.262)	(0.173)	(0.284)	(0.469)	(0.368)	(0.213)	(0.053)
Master	0.007	0.004	0.008	0.026	0.0147	0.002	0.000
Master	(0.080)	(0.061)	(0.086)	(0.158)	(0.120)	(0.045)	(0.016)
Doctor	0.002	0.001	0.003	0.018	0.003	0.002	0.000
Doctor	(0.048)	(0.032)	(0.052)	(0.131)	(0.056)	(0.044)	(0.000)
Marriage	0.918	0.898	0.925	0.911	0.902	0.896	0.950
Marriage	(0.274)	(0.303)	(0.263)	(0.285)	(0.297)	(0.305)	(0.217)
Risk preference	0.077	0.080	0.075	0.115	0.091	0.063	0.059
Risk preference	(0.266)	(0.271)	(0.263)	(0.320)	(0.288)	(0.244)	(0.236)
(0, 3,000)	0.128	0.288	0.182	0.041	0.073	0.167	0.288
(0, 3,000)	(0.287)	(0.326)	(0.271)	(0.136)	(0.184)	(0.263)	(0.329)
(3,000, 8,000)	0.274	0.303	0.264	0.176	0.210	0.268	0.317
(3,000, 8,000)	(0.446)	(0.459)	(0.441)	(0.381)	(0.408)	(0.443)	(0.465)
(8,000, 15,000)	0.285	0.251	0.297	0.353	0.345	0.283	0.255
(8,000, 15,000)	(0.451)	(0.433)	(0.457)	(0.478)	(0.475)	(0.451)	(0.436)
(15,000, 30,000)	0.161	0.113	0.177	0.298	0.246	0.184	0.107
(15,000, 30,000)	(0.368)	(0.317)	(0.382)	(0.457)	(0.431)	(0.387)	(0.309)
(30,000, 45,000)	0.038	0.024	0.043	0.078	0.067	0.055	0.017
(30,000, 45,000)	(0.191)	(0.152)	(0.202)	(0.268)	(0.250)	(0.228)	(0.128)
(45,000, 80,000)	0.020	0.012	0.022	0.040	0.036	0.023	0.010
(45,000, 80,000)	(0.139)	(0.108)	(0.148)	(0.196)	(0.186)	(0.150)	(0.097)
(80,000, 150,000)	0.008	0.005	0.010	0.013	0.017	0.013	0.003
(80,000, 150,000)	(0.091)	(0.069)	(0.098)	(0.114)	(0.130)	(0.112)	(0.056)
(150,000, ∞)	0.004	0.003	0.004	0.001	0.006	0.007	0.003
(150,000, ∞)	(0.063)	(0.054)	(0.066)	(0.038)	(0.079)	(0.086)	(0.053)
Debt	0.442	0.482	0.429	0.432	0.367	0.370	0.483
Debt	(0.497)	(0.500)	(0.494)	(0.496)	(0.482)	(0.483)	(0.500)
Estate	0.930	0.903	0.939	0.946	0.909	0.894	0.969
Estate	(0.255)	(0.297)	(0.238)	(0.225)	(0.288)	(0.308)	(0.172)

Note. The cell shows the mean and standard error (in parentheses) of the variables. BEICSPSE = means the basic endowment insurance for civil servants and public sector employees; BEIUEE = means the basic endowment insurance for urban enterprise employees; SEIUR = means the social endowment insurance for urban residents; NRSEI = means the new rural social endowment insurance.

The variable “financial literacy” tells us rural households’ financial literacy level (2.074) is significantly lower than the average (2.261) in the insured sample. There are obvious differences in the financial literacy level between urban and rural households in China. The risky assets participation rate and the ratio of risky financial assets in total financial assets of the urban households insured social endowment insurance in the sample are much higher than the average value (18%, 8%) of having social endowment insurance. The risky assets participation rate and the ratio of risky financial assets from the rural households are the lowest, only 4% and 1.4%. The data shows that even if the households have participated in social endowment insurance, there are still huge differences in financial literacy and portfolio choices between urban and rural households in China.

Model

Effect of Social Endowment Insurance on Household Portfolio Choices

We want to identify the impact of participation in social endowment insurance on the household risky assets. Since the three rounds of survey data from CHFS 2013 to 2017 are integrated, we can use the fixed-effect panel model to identify the impact of social endowment insurance on household risky assets allocation. The advantage of using the fixed-effect panel model is that the influence of unobservable heterogeneity that does not change with time can be eliminated by differential transformation, including the non-observable heterogeneity of an individual that does not change with time, and the area where it is located. Non-observational heterogeneity includes terrain, customs, etc.

$\begin{matrix} y_{it} = α + γ_{i} \cdot D_{i} + λ_{t} \cdot T_{t} + β_{1} \cdot Insuranc e_{it} \\ + β_{2} \cdot Literac y_{it} + η \cdot X_{it} + ε_{it} \end{matrix}$ (1)

Among them, y_it represents whether the i family holds risky assets or the proportion of risky assets held in period t. Insurance_it indicates whether the i family has social endowment insurance in period t. Literacy_it represents the level of financial literacy of the i family in period t. D_i represents the household fixed effect, and X_it are the observable household characteristic variables that change over time and may affect the decisions of household risky assets allocation. The fixed-effects model eliminates unobservable individual heterogeneity through intra-group transformation, but there may still exist unobservable heterogeneity that changes over time, which is related to insurance policy or financial literacy and causes endogenous problems. Therefore, we solve the endogenous problem in the following ways. (1) Controlling the time fixed effect T_t of each individual. In other words, add the year dummy variable T_t to control the year fixed effect, then the above formula can be rewritten as a two-way fixed effect panel model. (2) Because the households with social endowment insurance and the households without social endowment insurance may have large geographic differences, the time trends of risky assets allocation decisions may be different in the two types of households. In order to reduce the potential selective bias, we allow the time trend of risky assets allocation decisions to change with the changes in some regional characteristics. So we add the interaction term of Z_it and Year_t to the above formula. The public data set of CHFS is only disclosed to the provincial national standard code, so we use the provincial per capita GDP to measure the regional characteristic Z_it of the households.

$\begin{matrix} y_{it} = α + γ_{i} \cdot D_{i} + λ_{t} \cdot T_{t} + β_{1} \cdot Insuranc e_{it} \\ + β_{2} \cdot Literac y_{it} + η \cdot X_{it} + δ \cdot Z_{it} \cdot Yea r_{t} + ε_{it} \end{matrix}$ (2)

Moderating Effect of Financial Literacy on the Relationship of Social Endowment Insurance and Household Portfolio Choices

The marginal impact of social endowment insurance on the household portfolio choices may not be constant. It may be related to the degree of households’ financial literacy. Financial literacy may have a moderating effect on the relationship of social endowment insurance and household portfolio choices. In order to verify this conjecture, we added the interactive item of social endowment insurance and financial literacy in the formula.

$\begin{matrix} y_{it} = α + γ_{i} \cdot D_{i} + λ_{t} \cdot T_{t} + β_{1} \cdot Insuranc e_{it} \\ + β_{2} \cdot Literac y_{it} + β_{3} \cdot Insuranc e_{it} \cdot Literac y_{it} \\ + η \cdot X_{it} + δ \cdot Z_{it} \cdot Yea r_{t} + ε_{it} \end{matrix}$ (3)

Empirical Analysis

Effect of Social Endowment Insurance on Household Portfolio Choices

Table 2 shows the results of a full sample analysis of factors affecting household portfolio choices. The column (1) shows the regression results of the equation that the explained variable is the risky market participation rate. This equation is used to measure the extensive effect of explanatory variables. The coefficients of social endowment insurance and financial literacy stabilized at 0.015 and 0.014, and both were significant at the 5% significance level. The results show that families with social endowment insurance are 1.5% more likely to allocate risk assets than those without social endowment insurance. At the same time, for every additional unit of financial literacy, the probability of participation of household risky assets increases by 1.4%. The higher the financial literacy level of the household head, the more likely the household purchase risky financial products. The column (2) shows the regression results of the equation that the explained variable is the proportion of household risky assets in total financial assets. This equation is used to measure the intensive effect of explanatory variables. The coefficient of social endowment insurance from column (2) is 0.005, but it is not significant at the 10% significance level. The effect of financial literacy on the proportion of holding risky assets is 0.007, and it is significant at a significance level of 1%, indicating that for every additional unit of financial literacy, the proportion of households allocated risky assets is 0.7% higher. It can be seen that the influence of social endowment insurance participation is only reflected in the extensive margin, while the influence of financial literacy is reflected in both the extensive margin and the intensive margin.

Table 2.

Regression Results of Formula (2).

Variables	(1)	(2)
Variables	Extensive margin	Intensive margin
Social endowment insurance	0.015**	0.005
Social endowment insurance	(0.006)	(0.004)
Financial literacy	0.014***	0.007***
Financial literacy	(0.003)	(0.002)
Age of household head	−0.001	−0.000
Age of household head	(0.001)	(0.000)
Marriage	0.028**	0.024***
Marriage	(0.014)	(0.008)
Primary school	0.014	0.002
Primary school	(0.023)	(0.013)
Middle school	0.004	0.002
Middle school	(0.024)	(0.014)
High school	0.030	0.004
High school	(0.026)	(0.015)
Technical secondary school	0.022	0.003
Technical secondary school	(0.030)	(0.018)
Junior college	0.062**	0.030*
Junior college	(0.030)	(0.017)
Bachelor	0.053	0.040**
Bachelor	(0.034)	(0.020)
Master	0.093	0.061*
Master	(0.060)	(0.035)
Doctor	−0.039	0.103*
Doctor	(0.102)	(0.059)
Risk preference	0.025***	0.024***
Risk preference	(0.009)	(0.005)
Annual income (0, 3,000)	0.010	0.001
Annual income (0, 3,000)	(0.010)	(0.006)
Annual income (3,000, 8,000)	0.011	0.002
Annual income (3,000, 8,000)	(0.008)	(0.005)
Annual income (8,000, 15,000)	0.021**	0.002
Annual income (8,000, 15,000)	(0.009)	(0.005)
Annual income (15,000, 30,000)	0.065***	0.020***
Annual income (15,000, 30,000)	(0.010)	(0.006)
Annual income (30,000, 45,000)	0.093***	0.027***
Annual income (30,000, 45,000)	(0.015)	(0.009)
Annual income (45,000, 80,000)	0.153***	0.076***
Annual income (45,000, 80,000)	(0.019)	(0.011)
Annual income (80,000, 150,000)	0.122***	0.072***
Annual income (80,000, 150,000)	(0.027)	(0.016)
Annual income (150,000, ∞)	0.143***	0.097***
Annual income (150,000, ∞)	(0.038)	(0.022)
Debt	−0.001	0.004
Debt	(0.005)	(0.003)
Number of properties	0.037***	0.021***
Number of properties	(0.011)	(0.007)
Number of the aged over 60	−0.004	−0.004
Number of the aged over 60	(0.007)	(0.004)
Number of the children under 10	0.007	0.002
Number of the children under 10	(0.006)	(0.003)
GDP per capita of province	0.028	0.014
GDP per capita of province	(0.033)	(0.019)
Constant term	−0.516	−0.301
Constant term	(0.353)	(0.206)
Individual fixed effect	Yes	Yes
Time fixed effect	Yes	Yes
GDP × year	Yes	Yes
Observations	21,863	21,863
R-squared	0.662	0.671

Note. What is reported in parentheses is the robust standard error of the coefficient.

, **, *** indicate significance at the significance level of 1%, 5%, and 10%, respectively.

Difference Between Urban and Rural Areas

Table 3 shows the urban-rural differences in the allocation of household risky assets by social endowment insurance and financial literacy. From column (1), it can be seen that participating in social endowment insurance can increase the probability of holding risky assets for urban households. Families participating in social endowment insurance are 2.3% more likely to hold risky assets than those not participating in social endowment insurance from urban samples. However, the coefficient of social endowment insurance in column (2) is small and insignificant. The result shows that participating in social endowment insurance does not increase the probability of holding risky assets for rural households, and the new rural social endowment insurance cannot play a role in reducing uncertainty expectations.

Table 3.

Comparison Between Urban and Rural Areas.

Variables	(1)	(2)	(3)	(4)
	Extensive margin		Intensive margin
	Urban	Rural	Urban	Rural
Social endowment insurance	0.023**	0.001	0.009	−0.001
Social endowment insurance	(0.010)	(0.006)	(0.006)	(0.003)
Financial literacy	0.023***	0.001	0.011***	−0.000
Financial literacy	(0.005)	(0.003)	(0.003)	(0.001)
Control variables	Yes	Yes	Yes	Yes
Individual fixed effect	Yes	Yes	Yes	Yes
Time fixed effect	Yes	Yes	Yes	Yes
GDP × year	Yes	Yes	Yes	Yes
Observations	14,061	7,677	14,061	7,677
R-squared	0.653	0.433	0.665	0.386

Note. What is reported in parentheses is the robust standard error of the coefficient.

, **, *** indicate significance at the significance level of 1%, 5%, and 10%, respectively.

On the other hand, increasing the attention of financial news can increase the probability of holding risky assets and the proportion of risky assets for urban households. For every additional unit of financial literacy, the probability of holding risk assets for urban households will increase by 2.3%, but it has no significant effect on the rural samples. The result may be related to the difference in risk preference between urban and rural residents. Affected by factors such as conservative investment concepts and the uncertainty of agricultural income, rural residents are more risk-averse. Even if their financial literacy level increases, they are still unwilling to try risky financial production. Column (3) and (4) of Table 3 show that social endowment insurance cannot increase the proportion of holding risky assets for urban and rural household samples. Further, it proves that social endowment insurance only has an extensive margin effect in urban areas. Financial literacy can only increase the proportion of risky assets held by urban households, and has no significant effect in rural samples. So financial literacy has extensive margin effect and intensive margin effect only in urban areas.

Moderating Effect of Financial Literacy

The marginal effect of social endowment insurance on the household portfolio choices may not be constant. It may be related to the degree of household financial literacy or financial literacy has a moderating effect on the relationship of household portfolios and social endowment insurance. To verify the conjecture, we added the interactive item of social endowment insurance and financial literacy in the regression. From the columns (1) and (4) of Table 4, it can be seen that the higher the financial literacy of insured households from total samples, the stronger the effect on the rate of participating in risky financial market and the proportion of risky assets, compared with uninsured households. However, the moderating effect only exists in urban samples, and there is no effect in rural samples.

Table 4.

Regression Results of Formula (3).

Variables	(1)	(2)	(3)	(4)	(5)	(6)
	Extensive margin			Intensive margin
	Total	Urban	Rural	Total	Urban	Rural
social endowment insurance	0.017*** (0.006)	0.025** (0.010)	−0.000 (0.006)	0.006 (0.004)	0.009 (0.006)	−0.001 (0.003)
Financial literacy	0.001 (0.005)	−0.000 (0.007)	0.004 (0.004)	0.000 (0.003)	0.001 (0.004)	−0.000 (0.002)
Insurance × financial literacy	0.018*** (0.005)	0.032*** (0.008)	−0.004 (0.005)	0.008*** (0.003)	0.014*** (0.005)	−0.000 (0.002)
Control variables	Yes	Yes	Yes	Yes	Yes	Yes
Individual fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
Time fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
GDP × year	Yes	Yes	Yes	Yes	Yes	Yes
Observations	21,863	14,061	7,677	21,863	14,061	7,677
R-squared	0.663	0.654	0.433	0.671	0.665	0.386

Note. What is reported in parentheses is the robust standard error of the coefficient.

, **, *** indicate significance at the significance level of 1%, 5%, and 10%, respectively.

Moderating Effects of Different Kinds of Social Endowment Insurance

Different types of social endowment insurance may have different effects. We divide social endowment insurance into the basic endowment insurance for civil servants and public sector employees (BEICSPSE), the basic endowment insurance for urban enterprise employees (BEIUEE), the social endowment insurance for urban residents (SEIUR), the new rural social endowment insurance (NRSEI). The control group is the households without social endowment insurance. From column (2) of Table 5, we can see that, with the same level of financial knowledge, households with BEICSPSE have a 3.7% higher probability of holding risk assets than the households without social endowment insurance. The households insured BEIUEE has a 3.3% higher probability of holding risky assets than the households without social endowment insurance. The effect of SEIUR on the probability of holding risky assets depends entirely on their financial literacy. Compared with the households without social endowment insurance, an increase of one unit of financial literacy for families with SEIUR can increase the probability of holding risky assets by 3.8%. However, the NRSEI has little effect on the probability of holding risky assets for rural households, and the coefficient (0.007) is not significant. The result is consistent with the previous conclusions. NRSEI does not effectively encourage rural residents to invest in risky financial markets.

Table 5.

Moderating Effects of Different Kinds of Social Endowment Insurance.

Variables	(1)	(2)	(3)	(4)
Variables	Extensive margin		Intensive margin
BEICSPSE	0.042***	0.037***	0.015*	0.014*
BEICSPSE	(0.014)	(0.014)	(0.008)	(0.008)
BEIUEE	0.033***	0.033***	0.015**	0.014**
BEIUEE	(0.010)	(0.010)	(0.006)	(0.006)
SEIUR	0.010	0.012	−0.003	−0.002
SEIUR	(0.012)	(0.012)	(0.007)	(0.007)
NRSEI	0.007	0.007	0.002	0.002
NRSEI	(0.008)	(0.008)	(0.005)	(0.005)
BEICSPSE × financial literacy		0.048***		0.017***
BEICSPSE × financial literacy		(0.011)		(0.006)
BEIUEE × financial literacy		0.035***		0.019***
BEIUEE × financial literacy		(0.007)		(0.004)
SEIUR × financial literacy		0.032***		0.013**
SEIUR × financial literacy		(0.010)		(0.006)
NRSEI × financial literacy		0.003		0.002
NRSEI × financial literacy		(0.006)		(0.004)
Control variables	Yes	Yes	Yes	Yes
Individual fixed effect	Yes	Yes	Yes	Yes
Time fixed effect	Yes	Yes	Yes	Yes
GDP × year	Yes	Yes	Yes	Yes
Observations	21,115	21,115	21,115	21,115
R-squared	0.672	0.673	0.679	0.679

Note. What is reported in parentheses is the robust standard error of the coefficient.

, **, *** indicate significance at the significance level of 1%, 5%, and 10%, respectively.

From column (4) of Table 5, we can see that, with the same level of financial literacy, households with BEICSPSE and BEIUEE have a higher proportion (1.4%) of risky assets than the households without social endowment insurance. The effect of SEIUR on the proportion of risky assets depends entirely on the households’ financial literacy. Compared with the households without social endowment insurance, an increase of one unit of financial literacy for families with SEIUR can increase the proportion of holding risky assets by 1.3%. The marginal effect of NRSEI on the proportion of risky financial assets is weak (0.002) and the interaction term is not significant, indicating that NRSEI may not be able to effectively encourage the rural households to invest in risky financial products.

Robustness Test

Whether the two-way fixed-effect panel model can identify the causal effect of social endowment insurance on household portfolio choices depends on a strong assumption: the treatment group and the control group have a common time trend. We use a placebo test to test whether this hypothesis holds. The core idea of the placebo test lies in the fictitious treatment group. If the regression results of the estimators under different fictitious methods are still significant, it means that the original estimation results are likely to be biased, and the changes in household portfolio choices are likely to be affected by other random factors.

In the regression, we regard the households whose head did not have any social endowment insurance in the three phases (2013, 2015, 2017) or insured before 2013 as the control group. For the households whose head participated in the social endowment insurance in 2015 or 2017, we made a fictional variable to advance their participation year by one period. If the estimated coefficient of the variable is not significant, that is to say, except for the effect of the region where the head insured, there is no systematic difference in the change trend of household portfolio choices between the treatment group and the control group.

The regression results are shown in Table 6. We can see that the coefficient of pseudo- social endowment insurance is not significant. The sign and significance of the coefficient of social endowment insurance are consistent with the previous conclusions. The results indicate that the difference in household portfolio choices is indeed due to the social endowment insurance.

Table 6.

Placebo Test.

Variables	(1)	(2)	(3)	(4)	(5)	(6)
	Extensive margin			Intensive margin
	Total	Urban	Rural	Total	Urban	Rural
Insurance	0.024***	0.036***	0.001	0.011**	0.015*	0.003
Insurance	(0.009)	(0.013)	(0.008)	(0.005)	(0.008)	(0.004)
Pseudo-insurance	−0.004	−0.015	0.006	0.004	0.009	−0.003
Pseudo-insurance	(0.022)	(0.035)	(0.018)	(0.013)	(0.021)	(0.008)
Literacy	0.002	0.001	0.005	0.002	0.004	0.001
Literacy	(0.006)	(0.009)	(0.005)	(0.003)	(0.005)	(0.002)
Insurance × literacy	0.020**	0.034***	−0.002	0.012***	0.020***	0.001
Insurance × literacy	(0.008)	(0.013)	(0.007)	(0.005)	(0.008)	(0.003)
Pseudo-insurance × literacy	−0.004	−0.003	−0.003	−0.006	−0.009	−0.002
Pseudo-insurance × literacy	(0.009)	(0.015)	(0.008)	(0.005)	(0.009)	(0.004)
Control variables	Yes	Yes	Yes	Yes	Yes	Yes
Individual fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
Time fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
GDP × year	Yes	Yes	Yes	Yes	Yes	Yes
Observations	21,863	14,061	7,677	21,863	14,061	7,677
R-squared	0.663	0.654	0.434	0.671	0.665	0.386

Note. What is reported in parentheses is the robust standard error of the coefficient.

, **, *** indicate significance at the significance level of 1%, 5%, and 10%, respectively.

Discussion

Previous studies have shown that social endowment insurance can diversify background risks, reduce precautionary savings, and invest in risky financial products more. Some scholars have found that China’s social endowment insurance system only positively affects household portfolio choices for urban households. But some scholars hold the opposite conclusion. In response to this dispute, based on CHFS data, this study uses a two-way fixed effect panel model to examine the effect of social endowment insurance on the household portfolio choices between urban and rural households. Furtherly, considering the heterogeneity between urban and rural residents, this study examines the moderating effect of financial literacy on the relationship between social endowment insurance and household portfolio choices.

This study shows that the function of diversifying background risks from social endowment insurance is effective just for the urban residents compared to the rural residents, and financial literacy would widen the gap in this effect. The difference in household portfolio choices between urban and rural areas may exacerbate the urban-rural income gap and cause the inequality between urban and rural areas, which runs counter to the social security’s goals in China.

There may be the following factors that cause the different effect of social endowment insurance and the different moderating effect of financial literacy on household portfolios. Firstly, the pension from personal account in NRSEI is lower than other social endowment insurance (Sun et al., 2020). So NRSEI’s function of spreading risk is insufficient for rural residents in China. Secondly, there existed obvious income gap and income inequality between urban and rural households in China (Sicular et al., 2007). Farmers with low income are more risk-averse and prefer risk-free savings. Thirdly, farmers are less educated and rarely have the concept of assets management (Fu, 2005). Because of the limits of education, even if they were insured, farmers did not have the awareness to purchase risky financial assets. Finally, disparity in allocating financial resources may be a more convincing explanation. There are large differences in the distribution and availability of financial resources between urban and rural areas in China (Wang, Feng et al., 2019). The China Financial Inclusion Indicators Analysis Report from 2017 shows that while China has long achieved full coverage of bank branches in urban areas, the coverage rate in rural areas is 95% and village coverage is only 50%, with few relevant channels for farmers to access market information on financial risks. The number of financial institutions per capita is significantly higher in urban than in rural areas. The uneven distribution of financial resources between urban and rural areas is an important reason why pension has failed to play a role in narrowing the asset allocation gap between urban and rural households.

Conclusion

Based on the 2013 to 2017 China Household Finance Survey (CHFS) data and a two-way fixed effects panel model, this study aims to investigate the impact of social endowment insurance on portfolio inequality among urban and rural households in China, and the moderating effect of financial literacy on the relationship between social endowment insurance and household portfolios. The empirical results reveal the following research conclusions: (1) social endowment insurance only has a positive and significant effect on the household portfolio in the urban area; social endowment insurance has a weak and non-significant effect on the household portfolio in the rural area; (2) social endowment insurance has an extensive margin effect on the household portfolios, that is, social endowment insurance can increase the probability of participation in risky financial markets for the urban insured families; (3) financial literacy has a positive and significant effect on the household portfolio in the urban area; financial literacy has a weak and non-significant effect on the household portfolio in the rural area; (4) financial literacy has both the extensive margin effect and the intensive margin effect on the household portfolios, that is, for the urban insured families, financial literacy can not only increase the probability of participation in risky financial markets but encourage households to invest in more risky financial assets; (5) just for the urban households, financial literacy positively moderates the relationship between social endowment insurance and household portfolios, which suggests that the higher the financial literacy of insured households, the stronger the moderating effect on the rate of participating in risky financial market and the proportion of risky assets, compared with uninsured households; (6) classifying the social endowment insurance, the positive moderating effect of financial literacy on the relationship between social endowment insurance and household portfolios is stronger in BEICSPSE (4.8%) than BEIUEE (3.5%) or SEIUR (3.2%), but the moderating effect of financial literacy is weak and not significant in NRSEI (0.3%), indicating the significant difference in the moderating effect of financial literacy on different social endowment insurance policies.

The study has the following contributions: providing empirical evidence for academic disputes over whether social endowment insurance affects the household portfolio choices; introducing financial literacy to examine its moderating effect on the relationship of social endowment insurance and household portfolio choices; comparing the effects of different types of social endowment insurance policies on household portfolio choices. There are some limitations need scholars to discuss furtherly. This paper does not conduct an empirical test on the reason (financial resources) for the differences in portfolio choices of urban and rural households. Besides, we do not analyze the institutional influence on the differences in household portfolio choices caused by different types of social endowment insurance policies.

Footnotes

The authors wish to acknowledge the invaluable work of participants in the study. For the data used in this study—China Household Finance Survey,thank you for the national and continuous large-scale social survey project designed by the Research Center of Southwestern University of Finance and Economics.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: This study was supported by “the Fundamental Research Funds for the Central Universities,” Zhongnan University of Economics and Law (Grant No. 202111203).

Ethics Statement

The project team of China Household Finance Survey and Research (chfs) approved the implementation of this study,but the ethics number has not been publicly released. All participants have signed the informed consent form.

ORCID iD

Shuo Zhang

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