The effectiveness and choice of public pension scheme among Donglan county residents in China

Abstract

Background

China has made strides to achieve universal pension coverage through implementing the Public Pension Scheme for Urban and Rural Residents (PPSURR) program since 2014. This study explores the effectiveness of implementing the PPSURR in an impoverished county in China and investigates the determinants of residents’ choice on the contribution level of the PPSURR.

Methodology

Binary logit regression models were conducted using datasets extracted from the Chinese General Social Survey in 2021 and datasets collected through surveying 321 residents in Donglan county, China.

Result

The PPSURR is demonstrated to be effective in reducing coverage gap between urban and rural residents in Donglan county, indicating the feasibility to utilize administrative support and public policies (such as financial subsidies) to address the urban-rural disparity in pension coverage at the county-level. Our study also found that county residents who are rich, had higher education attainment and better understanding towards policies were more likely to participate in the PPSURR; insured residents with higher income and live in urban area were more likely to select a higher contribution level.

Conclusion

It’s urgent to gradually narrow benefits gap between urban and rural residents. Policy makers are suggested to offer more financial assistance for those from less wealthy backgrounds, promote public understanding towards related policies, and reduce the regional disparities.

Introduction

Population aging slows economic growth throughout much of the world [1]. In line with international practices, as the population ages in China, the government has been making continuous efforts to come up with a decent and sustainable public pension system in the last three decades [2]. In 1993, the Chinese government established a multi-pillar social security system (there were diversified public pension schemes for employees working in public institutions, urban employees as well as personal pensions plans) [3] and developed a public pension plan for residents based on the separation of urban and rural areas [4]. In 2003, the government in office stressed the role of family in ensuring security for rural older adults [5], but the fact was that rural elders in this period were left behind as an increasing number of rural young and middle-aged people sought for work in urban areas [6]. The financial contribution for rural residents’ pensions was clearly defined only after the establishment of the New Pension Scheme for R ural Residents (NPSRR) in 2009. Around the same time, the Pension Scheme for Urban Residents (PSUR), which followed a similar system to the NPSRR, was introduced to provide pension coverage for urban residents without existing coverage, helping to alleviate their financial burdens. However, these attempts failed to adapt to the changing demographics in China where the population aging was worsening especially in rural area where there are a surging number of rural - to - urban migrant workers. In 2013, the 18th Communist Party of China’s Central Committee strongly appealed to push merging the two public pension schemes (the NPSRR and the PSUR). In the subsequent year, the NPSRR and the PSUR were smoothly integrated into the Public Pension Scheme for Urban and Rural Residents (PPSURR) in China [7], with the goal of establishing universal pension coverage for, but not limited to, farmers and the urban non-working residents, integrating the traditionally fragmented pension systems, and addressing the challenges of rapid population aging and large-scale population mobility in China [7–8]. The PPSURR could be considered as a sustainable public pension system by the Chinese government to reduce the urban - rural divide, promote social equity, and ensure the basic living needs of the elderly.

The PPSURR was a partially funded system designed to balance the responsibilities and benefits between individuals and the state. It offers a flexible and adaptable approach to pension financing, taking into account both the needs of the retired and the economic realities of the country. In practice, the fund of the PPSURR was collected from a combination of individual contribution as well as financial subsidies from both the central and local government, and was deposited into the individual pension account of the insured residents; the pension treatment per capita per month included the minimum pension guaranteed by the government and the individual pension account divided by 139 months. The pension system offered more financial subsidies for insured residents who chose a higher contribution level [9], and ensured lifelong pension benefits for individuals aged 60 and above. However, the PPSURR is a voluntary pension scheme, and it was stated in the National Bureau of Statistics of the People’s Republic of China that about 260 million rural residents and urban informal workers were still uninsured by the end of 2018. Meanwhile, the average individual contribution of all insured residents was extremely small at CNY 187.74 (about USD 27.79) in 2019 and is expected to be at such a low level for a long period [10]. As such, It is essential to explore the effectiveness of the PPSURR implementation, and more importantly, to investigate what factors might impact residents’ decision to engage in the PPSURR and their selection on the associated contribution level.

Many studies have concluded that multiple demographic factors, such as gender, the “hukou” (a system of household registration in China), age, health conditions, marital status, education, income, and number of off-spring were related to individuals’ choice on a pension scheme [11,12,13,14,15]. However, extant evidence is controversial regarding the impacts of these demographic characteristics on the selection of the pension program and associated contribution level. Specifically, Wen Haihong et al. (2014) found that gender, the “hukou”, age, marital status and income had significant impacts on the decision to select a contribution level, while Luo Hanqun (2014) demonstrated that income and education had no effect. Likewise, Ebenstein & Leung (2010) found that the number of off-spring lowered rural residents’ willingness to participate in the public pension scheme and was linked with a lower contribution level [12], while a subsequent study found that it had no impact on the contribution level [11]. Given the controversial research findings and the changing demographics in China, all the aforementioned demographic factors will be included in our study.

A number of studies also pointed out that the understanding of related policies and trust in government were associated with the decision to participate a pension scheme and decision on a contribution level, although the conclusions on the effects were not unanimous [4, 14, 16–17]. For instance, Luo Hanqun (2014) and Du (2021) demonstrated that understanding related policies had a substantial impact on the contribution level of the NPSRR. Meanwhile, Zhong & Li (2010) found that a better understanding of related policies positively affected residents’ willingness to join the NPSRR. In contrast, Wang (2013) found that a better understanding of related policies had no statistically significant influence on the decision to participate in the NPSRR. Despite some valuable insights from a considerable body of literature focusing on the NPSRR, little is known about determinants of residents’ decision to enroll in the newly introduced pension scheme (the PPSURR) that differs from the traditionally pension systems in some fundamental ways in China.

Taken together, this paper contributes to the extant research through finding the PPSURR effectiveness and investigating what factors affect residents’ decision to participate in the PPSURR and their selection on the contribution level of the PPSURR. This manuscript will be structured in the following manner: the next section will introduce our data sources, measures of key variables, and statistical methods employed. Key research findings will then be outlined before being discussed. We end with providing a conclusion on key findings and possible suggestions to inspire future public pension insurance reform in China.

Methodology

Background

In China, the minimum contribution (subsidies) from Central government and individuals was CNY 30 and CNY 100 per capita per year, respectively, and the maximum individual contribution of the suggested national standard was CNY 2,000 per year. In Guangxi Zhuang Autonomous Region, the minimum contribution (subsidies) from government and individuals was CNY 35 and CNY 200 per capita per year, respectively, and the maximum individual contribution was CNY 6,000 in 2021, which is significantly higher than the suggested national standard (more details can be found in Table 1).

Table 1 Introduction of the PPSURR

Donglan is a low-income county located in Guangxi Zhuang Autonomous Region, China. In Donglan, the population aged 60 or above accounted for 21.15% of the permanent residents in 2020, higher than the national figure of 18.70% and the Guangxi figure of 16.69% [18]; meanwhile, the minimum contribution (subsidies) from government was CNY 35 per year per capita, and the individual contribution level of the PPSURR was consistent with that in Guangxi Region ranging from CNY 200 to CNY 6,000. In order to expand the pension coverage, Government of Donglan county issued the Notice on Measures for the Implementation of the PPSURR in 2014, pointing out that the government would pay part or all of the individual contribution for the economically disadvantaged groups and increase the minimum pension treatment per capita per month by CNY 5 above the national and Guangxi Zhuang autonomous region’s standard. It is clear that Donglan county has expedited the integration of the NPSRR with the PSUR, demonstrating its commitment and effective social mobilization in implementing the administrative directives from higher authorities to increase the pension coverage. However, there was a decline in the coverage of the PPSURR from 2018 to 2020 (Bureau of Statistics of Guangxi Zhuang Autonomous Region, 2019–2021), and in 2021, residents’ coverage in Donglan county was 68%, slightly lower than the national figure of 72.8% from the Chinese General Social Survey (CGSS), with most of the participants opting for the minimum contribution level of the PPSURR (CNY 200).

Data sources

As stated earlier, governmental contributions and the related policies varied by region, the analysis based on the CGSS could help us understand the overall trends of the PPSURR participation in a vast country as China, and further analysis of Donglan county could help us understand the unique dynamics in an underdeveloped county. Therefore, the Chinese General Social Survey and a collected dataset consisting of 321 residents in Donglan county in 2021 were used to explore the effectiveness of the PPSURR implementation and then investigate the influencing factors of residents’ decision towards the PPSURR.

When collecting the dataset in Donglan county, we authors designed the questionnaire (comprising information on individuals’ demographic characteristics, whether the individual had the PPSURR enrollment, and the contribution level of the PPSURR, policy perceptions related to the PPSURR, and public trust in government) and dispensed it online from January 14 to February 17, 2022. After checking for missing and invalid values, we obtained 7671 valid observations from 8148 samples of the Chinese General Social Survey. At the same time, we considered 321 samples out of 343 questionnaires to be valid. The scale used to measure policy perception and government trust had good internal consistency (with their Cronbach’s alpha coefficient being larger than 0.72) and excellent construct validity (with the value of the Kaiser-Meyer-Olkin test being 0.81 and the Bartlett sphericity test being statistically significant).

Measures of variables

The PPSURR enrollment and the associated contribution level were the two outcomes of our interest. The PPSURR enrollment was measured by a binary variable (1 = Yes, 0 = No). The contribution level was also measured by a binary variable with 1 representing a low level of contribution and 0 otherwise. We divided the current contribution levels (ranging from CNY 200 to CNY 6,000 per year) into two categories: a low contribution level (ranging from CNY 200 to CNY 400 per year) and a high contribution level (ranging from CNY 500 per year to CNY 6,000 per year) as the Guangxi government offered a higher level of subsidy if an individual’s contribution level is more than CNY 500 (DHRSS & FPRC of Guangxi Zhuang Autonomous Region, 2018).

Gender (male or female), residential location (rural or urban), age (≤ 30, 31–40, 41–50, or >51 years old), education (bachelor’s degree and above, college diploma, high school, primary school education and below), health conditions (self-rated health status being measured by a three-point Likert scale, ranging from “good” to “poor”), marital status (single, married, or divorced/widowed), number of off-spring (0, 1, or ≥ 2), and monthly household per capita income (far below the average, below the average, average, above the average) were included as our independent variables [11,12,13, 19–20].

Besides, policy perception was measured by the individual’s understanding of the PPSURR policies (including the contribution level of the pension scheme, the varying financial subsidies based on different contribution levels, and the required years for contribution and qualified age to collect pension), which was measured using a 5-point Likert scale ranging from 1 (representing “not at all”) to 5 (representing “very much”). Government trust was assessed by an individual’s confidence in the government’s capacity to provide elderly care and ensure the sustainable development of the PPSURR, which was measured using a 4-point Likert scale ranging from 1 (representing “not at all”) to 4 (representing “very much”).

Statistical methods

We first performed descriptive analyses to demonstrate the demographic characteristics across China and summarize the characteristics of our sampled individuals in Donglan county in 2021. Considering that about 68% participants selected the PPSURR (among which about 79% chose the low contribution level), we examined variances in choices using the Chi-square test (for gender, residential location, age, health conditions, education, marital status, number of off-spring, and income). Then we performed the correlation analysis (for policy perception and government trust). Since we used binary variables to measure residents’ decision to participate in the PPSURR and to select the associated contribution level, we constructed two binary logit regression models to examine the impacts of factors proposed above: as shown in Eq. (1), logit(P) represents the logarithm of the odds P/(1-P), where P represents a probability. The Multicollinearity Diagnosis was conducted by a subject technique of inspecting the magnitude of the standard error of each predictor variable [21]. The Omnibus Tests were performed to examine whether all the coefficients are jointly significant. The Hosmer and Lemeshow test were performed to report the goodness-of-fit of the regression models. All the analyses were conducted using the SPSS 12 software.

$$\begin{aligned}&\:\left(1\right)\:\text{l}\text{o}\text{g}\text{i}\text{t}\left(\text{P}\right)=\:\text{ln}\frac{p}{1-p}\cr&={{\beta}}_{0}+{{\beta}}_{1}\text{g}\text{e}\text{n}\text{d}\text{e}\text{r}+{{\beta}}_{2}\text{a}\text{g}\text{e}+{{\beta}}_{3}\text{m}\text{a}\text{r}\text{r}\text{i}\text{a}\text{g}\text{e}+{{\beta}}_{4}\text{o}\text{f}\text{f}-\text{s}\text{p}\text{r}\text{i}\text{n}\text{g}+{{\beta}}_{5}\text{h}\text{e}\text{a}\text{l}\text{t}\text{h}\\&+{{\beta}}_{6}\text{i}\text{n}\text{c}\text{o}\text{m}\text{e}+{{\beta}}_{7}\text{e}\text{d}\text{u}\text{c}\text{a}\text{t}\text{i}\text{o}\text{n}+{{\beta}}_{8}\text{p}\text{o}\text{l}\text{i}\text{c}\text{y}\:\text{p}\text{e}\text{r}\text{c}\text{e}\text{p}\text{t}\text{i}\text{o}\text{n}+{{\beta}}_{9}\text{g}\text{o}\text{v}\text{e}\text{r}\text{n}\text{m}\text{e}\text{n}\text{t}\:\text{t}\text{r}\text{u}\text{s}\text{t}+\text{e}\text{r}\text{r}\text{o}\text{r}\end{aligned}$$

Results

Descriptive results

Table 2 reports the descriptive statistics of our research samples from the Chinese General Social Survey and those from Donglan county. The distributions of gender, residential location, education, health conditions, marital status, number of off-spring, and monthly household income per capita among the sampled individuals in Donglan county closely resemble those reported in the CGSS. In both the CGSS (n = 7,671) and the survey conducted in Donglan county (n = 321), the majority of sampled individuals were female, from rural areas, married, had completed high school education, had two or more off-spring, reported average monthly household income per capita, and were in good health. It’s worth mentioning that a higher proportion of individuals in our sample reported a monthly household income per capita below the national average compared to the overall population in China.

The statistics for Donglan County revealed that 84 participants (p = 26%), 86 participants (p = 27%), and 80 participants (p = 25%) reported limited knowledge about the contribution levels, financial subsidies, and qualification criteria for benefits under the PPSURR, respectively. Meanwhile, 139 participants (p = 43%) and 160 participants (p = 50%) expressed trust in the government and the PPSURR, respectively.

Table 2 Descriptive statistics for the sampled individuals

Chi-square test results

Table 3 reports the variations in choices on the PPSURR participation in China. We found that statistically significant variations in choices on the PPSURR participation across different groups by gender, residential location, age, health conditions, education, marital status and number of off-spring and income level.

Table 3 Chi-square test results across China

Table 4 reports the variations in choices on the participation of the PPSURR and the associated contribution level across different population groups in Donglan county. There were statistically significant variations in choices on the PPSURR participation across different groups by gender, age, education, marital status and number of off-spring, and county residents’ choices on the associated contribution level of the PPSURR was differed by their residential location and income level.

It was worth noting that the PPSURR participation across China has statistical differences in residential location, health conditions and income level, but in Donglan county, the statistical difference in the above three aspects was not found. The results showed tentative signs of effectiveness in reducing coverage gap between urban and rural residents in Donglan county, and highlighted the necessity to further conduct comparisons in Donglan county.

Also noteworthy is the statistically significant difference between urban and rural residents as well as their different income levels in Donglan county in terms of their PPSURR contribution level rather than the PPSURR participation.

Table 4 Chi-square test results for Donglan county

Correlation analysis results

Tables 5 and 6 report the results of the correlation analysis. Spearman correlation test indicates that both policy perception and governmental trust were correlated with residents’ decision to participate in the PPSURR in Donglan county, although these two variables were not significantly correlated with their choice of the contribution level. Meanwhile, Pearson test indicates that policy perception was correlated with government trust.

Table 5 The results of correlation analysis (1)

Table 6 The results of correlation analysis (2)

Regression analysis results

Demographic factors with the P value ≤ 0.2 in the Chi-square test (including gender, age, marital status, number of off-spring, monthly household income per capita, health conditions, and education) and policy perception and government trust were included as the independent variables of the choices of the PPSURR participation in the binary regression model. Meanwhile, residential location, age, marital status, health conditions, monthly household income per capita, education, policy perception and government trust were included as the determinants of the choices of the PPSURR contribution level in the binary regression model.

Figures 1 and 2 report the impacts of factors influencing the decision to participate in the PPSURR and to select the contrition level, respectively.

As presented in Fig. 1, the monthly household income per capita, education and policy perception have been found to substantially impact residents’ decision to participate in the PPSURR. Residents with higher policy perception level were more likely to enroll in the public pension scheme (OR: 1.78). Groups that received college diploma (OR: 0.37) and high school education (OR: 0.37) were less likely to participate in the PPSURR than those with bachelor’s degree and above. Additionally, we found that residents with the average monthly household income per capita had a significant higher chance of participating in the PPSURR than those with the monthly household income per capita below the average (OR: 2.21). We also found that residents whose monthly household income per capita were above the average had a higher probability of participating in the PPSURR (OR: 2.44), although such association was not statistically significant in this study. It was noted that number of cases ‘correctly predicted’ were 241 (75.1%).

As shown in Fig. 2, residential location and monthly household income per capita have been found to impact residents’ choice of the contribution level. Specifically, urban residents had a lower probability of choosing the low contribution level (OR: 0.41) compared with their rural counterparts. Residents with the monthly household income per capita above the average had a lower possibility of choosing the low contribution level in comparison with those whose monthly household income per capita were below the average (OR: 0.25). These results indicate that urban residents and the insured residents with better economic conditions were less likely to choose the low contribution level. It was noted that number of cases ‘correctly predicted’ were 180 (82.2%).

None of the predictor variables in the model had a standard error larger than 2.0, indicating no multicollinearity among predictors. The p-value of the Omnibus Tests for the two regression models was smaller than 0.05, rejecting the null hypothesis that all the regression coefficients were 0 simultaneously. The p-value of the Hosmer and Lemeshow test for the two regression models was 0.827 and 0.071, respectively, implying that the regression models were well-fitted.

Fig. 1

Factors impacting the PPSURR participation (N = 321)

Fig. 2

Factors impacting the choice of the contribution level (N = 219)

Discussion

We found the PPSURR effectiveness in reducing coverage gap between urban and rural residents in Donglan county rather than that across China, which was slightly different from previous study holding the view that there is a huge gap between urban and rural coverage and benefits [22] and indicating the PPSURR effectiveness of integrating the traditionally fragmented public pension systems and establishing universal pension coverage for both urban and rural residents in an impoverished county in China [7–8]. The key takeaway from this study is that, at the county level, it is indeed feasible to use administrative support and public policies (such as financial subsidies) to address the urban-rural disparity in pension coverage.

Then, our study explored factors affected residents’ decision to participate in the PPSURR and their choice on the contribution level in Donglan county. This article demonstrated that residents with better economic conditions, higher level of education, better understanding of the PPSURR policies were more likely to participate in the system, and we also found that urban residents and the insured residents with better economic conditions were more likely to select the high contribution level of the PPSURR. In details, the rich individuals were more likely to participate and select the higher contribution level of the PPSURR than those whose monthly household incomes per capita were below the average (the monthly minimum wage in Donglan county was CNY 1580), which is consistent with previous works pointing out that income had significant impacts on the decision to select a contribution level [15]. In line with some prior studies [14–15], we also found that residents with higher education attainment were more likely to participate in the PPSURR, although education had no statistically significant impact on individual’ choice of the contribution level. One possible explanation was that although the educated residents had more chances to participate in various pension schemes (as the public pension schemes for employees and residents in China are separate) [3, 22], they chose to enroll in the PPSURR due to the straightforward process of transitioning from the PPSURR to the employee public pension schemes. Besides, we found that individuals with a deeper understanding of the PPSURR policy were more likely to participate in the pension program. This finding aligns with previous research indicating that top-down social mobilization tends to have a more substantial impact on enhancing pension participation given that comprehension and acceptance of new pension systems are often limited among county residents in developing regions [16]. Unexpectedly, even though the annual per capita pension benefits for county residents in Donglan exceed the suggested national average, residents’ understanding of the PPSURR policy had no statistically significant impact on their decisions regarding pension contribution levels, which contradicts prior studies [14, 17]. This could be attributed to the socioeconomic conditions of Donglan county’s residents, which limited their capacity to select appropriate pension contribution levels, as well as to the inherent lack of appeal of the public pension system.

A set of policy suggestions are derived from this study: (1) The influence of socioeconomic conditions on the PPSURR participation and contribution levels has received increased attention, particularly regarding the economic conditions in Donglan county. Policy makers are suggested to be aware of the challenges faced by rural and low-income residents living in counties like Donglan. Some financial assistance programs are suggested to be developed to continuously support these vulnerable groups to participate in the PPSURR and more importantly, enable them to select a higher contribution level; (2) The influence from policy perception not only highlighted the need to enhance public understanding of the PPSURR but also compelled the improvement of pension policies. For one hand, there is a need to promote public’s understanding of policies related to the PPSURR (including policies associated with the financial subsidy offered by the government, the relations between PPSURR and the public pension scheme for employees) to encourage residents to participate in the PPSURR. For the other hand, specific measures could include securing greater financial support from the central and local governments, as well as redesigning the pension scheme through adjusting the contribution years for individuals from less advantaged backgrounds. Besides, policymakers should boost the pension reformation by narrowing the gap through perfecting the management of funds for the public pension scheme for residents in consideration of the regional disparities in pension benefits (see Table 1).

Several limitations of this study should be recognized. Limited by data accessibility, we used a relatively small research sample, which can threaten the generalizability of our research findings. Nevertheless, our research was still useful in predicting determinants of the pension program enrollment and associated contribution level among residents in impoverished regions. Regions in China have introduced varying contribution levels of the PPSURR, and we believe our study can offer some suggestions to guide future policy design in these regions. Second, only a small percentage of our sampled participants (p = 21%) selected the high contribution level defined in this study. A more solid conclusion cannot be given until a rich sample can be obtained in future days. Finally, considering there were various pension schemes in China, it would be helpful to systematically examine the role of these pension schemes in determining residents’ choices on the PPSURR.

Conclusion

This study finds the PPSURR effectiveness in reducing coverage gap between urban and rural residents in Donglan county rather than that across China, and demonstrates that residents with better economic conditions, higher level of education, better understanding of the PPSURR policies were more likely to participate in this system; urban residents and the insured residents with better economic conditions were more likely to select the higher contribution level. There is an urgent need for the government to gradually narrow the gap between urban and rural benefits, and now policy-makers are suggested to introduce a financial assistance program to offer necessary support for the vulnerable population living in low-income regions, promote the public’s understanding of a series of policies related to the PPSURR. The effectiveness of Donglan county’s approach could offer valuable insights for other impoverished counties in rural China, as well as in other developing countries. When introducing a new pension system, the responsible authorities should consider utilizing a variety of policy tools, including financial support, social mobilization, etc., to ensure its successful implementation. In the further research, the effectiveness and divergence of multiple pension schemes needs to be systematically examined to help understand the PPSURR effectiveness and determinants of the choice of the PPSURR.