2.1 Data Sources

This study uses publicly available data from the China General Social Survey (CGSS) conducted between 2012 and 2021. The database is managed and released annually by the China Survey and Data Center (NSRC) at Renmin University of China. It is a representative longitudinal social survey in China, providing comprehensive and systematic descriptions and analyses of Chinese society through annual data, thus revealing the actual state of social changes in China.

2.2 Data Cleaning

According to the specific needs of this study, several data cleaning steps were applied to the CGSS data from 2012 to 2021:

Finally, the samples with educational attainment categorized as secondary vocational schools and technical schools were merged into the "High School" category, while samples from private schools, literacy classes, and elementary schools were merged into the "Elementary School" category. The final effective samples after cleaning were as follows: 6,008 samples in 2012, 5,651 samples in 2013, 4,909 samples in 2015, 5,525 samples in 2017, 5,393 samples in 2018, and 3,138 samples in 202111.

2.3 Variable Specification

2.4 Model Specification

In research on the relationship between educational attainment and fertility intentions, most models commonly adopt methods such as the Ordinary Least Squares (OLS) regression model and sample selection models [24]. However, considering the ordered and discrete nature of fertility intentions data, this study employs an Ordered Logistic Regression Model for quantitative analysis. The specific model is formulated as follows:

In this model, ${\text{fer}}_i$ represents the individual's fertility intention, ${\text{edu}}_i$ denotes the overall educational attainment of the population, and ${\text{control}}_i$ includes the set of control variables, namely gender, ethnicity, political affiliation, self-rated health, religious belief, hukou type, and marital status. The parameters $\alpha$, $\beta$, and $\gamma$ are to be estimated, and ${\epsilon }_i$ denotes the random error term.

3.1 Descriptive Statistics

3.2 Regression Results

This study employs an ordered logistics regression model to examine the impact of educational attainment on fertility intentions. In Model (1), control variables are not included, while Model (2) incorporates a set of control variables. The regression results are presented in Table 6.

From Table 6, it is evident that there is a negative correlation between educational attainment and fertility intentions over the past decade. Although the regression coefficients decrease after the inclusion of relevant control variables, they remain statistically significant at the 1% level. Examining the regression results year by year, it becomes clear that while the coefficients reflecting the relationship between overall educational attainment and fertility intentions among the Chinese population have shown a complex pattern—first decreasing, then increasing, and subsequently decreasing again—the coefficients are consistently negative. This supports the hypothesis of the study that educational attainment is negatively associated with fertility intentions. As for the control variables, religious belief, political affiliation, and gender exhibit a statistically significant positive influence on fertility intentions at the 1% level, while hukou type and ethnicity show a statistically significant negative influence on fertility intentions at the 1% level.

3.3 Robustness Check

To ensure the robustness and reliability of the model results, this study also employs an Ordered Probit Regression Model to re-estimate the data. A comparison of the regression results is presented in Table 7.

From Table 7, it can be observed that the statistical results obtained from the ordered probit regression model show some differences in coefficients compared to the ordered logistics regression model. However, both models are statistically significant and indicate a negative correlation between the overall educational attainment of the population and fertility intentions. Therefore, it can be concluded that the results derived from the model selected in this study are robust.

4.1 Discussion

First, based on the regression analysis and robustness tests, it is clear that, regardless of whether the relevant variables are controlled for, the overall effect of educational attainment on fertility intentions is significantly negative at the 1% level. This result aligns with the findings of Nie [3] and other scholars, indicating that in China, the higher the educational attainment, the lower the fertility intentions.

Second, analyzing the above results through the lens of the Theory of Planned Behavior reveals several reasons behind these findings. First, in terms of behavioral attitudes, as the educational attainment of Chinese people increases, they are likely to have higher demands and perspectives on personal freedom and value. Therefore, in pursuit of a freer lifestyle, they may reduce their fertility intentions. Second, regarding subjective norms, due to differences in educational attainment, individuals may be influenced by different groups. People with higher educational attainment are more likely to prioritize personal achievements and career development, which may reduce their willingness to have children in order to avoid disruptions to their personal growth. Lastly, in terms of perceived behavioral control, individuals with higher educational attainment may perceive childbearing as a significant drain on time and energy. Given that measures to reduce the burden of childbearing are still insufficient, this perception may lead to decreased fertility intentions.

Third, based on the regression results and cause analysis, it is evident that the negative impact of educational attainment on fertility intentions has gradually increased in recent years. This suggests that, under unchanged real-world conditions, fertility intentions may decline further in the coming years. This is an unfavorable trend for the country's development and requires national attention.

4.2 Recommendation

Based on the above discussions, this paper proposes the following recommendations:

First, optimize school education. Strengthening population education and integrating it into the compulsory education system can help establish correct views on population from an early age. It is also crucial to enhance education on national conditions related to population, helping young people understand the country's population needs, fostering a sense of responsibility, and thus increasing their fertility intentions. Improving the quality of education, whether through increased government investment, better teacher compensation, or enhanced ability to attract quality educators, essentially leads to better teaching quality in schools, making population education more accessible to students and ultimately achieving the goal of enhancing their fertility intentions. Attention should also be given to the physical and mental health of students. Schools could collaborate with government-linked health centers to provide regular physical and psychological check-ups to ensure that young people maintain good physical and mental well-being. Overall, schools should place greater emphasis on educating students about population issues, fostering a respect for life, and instilling a sense of responsibility for bringing new life into the world, thereby enhancing their fertility intentions.

Second, improve social education. Strengthen public opinion guidance. The government can use third-party media or its official websites for public education, actively promoting the concept of age-appropriate childbirth and advocating the importance of a warm family and healthy child development. This would help the relevant population increase their sense of fertility responsibility and transmit positive family responsibilities, thereby encouraging the appropriate timing of marriage and childbirth. Establish and improve marriage and fertility support institutions. As the government actively develops high-quality marriage and fertility counseling services, various organizations should also improve comprehensive, scientifically-based support systems and provide consultation services to help the relevant population access timely and accurate information, alleviate psychological pressure, and adopt scientific, culturally appropriate views on marriage and fertility, thus enhancing their fertility intentions. Enrich the cultural life of the community. Local communities can regularly organize diverse cultural activities to stimulate the public's spirit and enhance their quality of life, helping individuals feel the joy of life and indirectly boosting the fertility intentions of young people of childbearing age. In short, improving social education requires communities, organizations, and institutions to work together, continuously organizing cultural activities that meet the needs of the public, enriching their inner world, meeting their daily relaxation needs, increasing their sense of happiness, and enhancing their likelihood of willing to have children.

Third, strengthen government support. The government should continue to expand the reach of pro-fertility policies, reduce the substantial financial burdens associated with childbearing, and eliminate fertility concerns among people of childbearing age, thereby stimulating their fertility intentions. Safeguard the legal employment rights of women. The government should strengthen protections for the legal employment of pregnant women, enact relevant laws and regulations to prevent workplace discrimination against women, and create more equal employment opportunities for women in the new era. Stricter punishments should be enforced against companies that illegally dismiss pregnant women, and businesses should be encouraged to adopt family-friendly policies that allow female employees to receive reasonable fertility-related benefits. Improve child welfare protections by increasing investments in children's well-being and enhancing their quality of life, which will alleviate the burden of raising children and further promote fertility intentions. In summary, the government should take active measures to ensure that pro-fertility policies are deeply embedded in society, achieving the ultimate goal of increasing the fertility intentions of the population.