The parents' internet use and children's extracurricular tutoring class participation.

The educational burden from extracurricular tutoring class has become a pressing social issue in China. This study used data from the China family panel studies (CFPS) in 2014, 2016, and 2018 to empirically analyze the impact of Internet usage on children's participation in extracurricular tutoring class. There are many factors that influence parents' decisions to enroll their children in extracurricular tutoring class. These factors include family income status, the level of importance parents place on their children's education, the marginal returns on educational investment, academic pressure, etc. However, in today's digitalized society, the widespread use of the internet will also become an important influencing factor in parents' decisions regarding educational investment. The study finds that, parents by using the Internet significantly increase the probability of enrolling their children in extracurricular tutoring class. Through mechanism regression analysis, it is concluded that internet usage has a positive influence on parents enrolling their children in extracurricular tutoring class by increasing the frequency of social interaction and raising parents' educational expectations for their children. Based on the empirical results, the following policy suggestions were proposed: 1. Schools should establish a more comprehensive after-school education service system to improve the engagement of students in compulsory education; 2. The government can enhance the accessibility and optimization of educational resources by increasing investment in education, improving the quality of in-school education, and optimizing the management and supervision of extracurricular tutoring class. This ensures that students can access high-quality educational services.

Impact of the internet use on informal workers' wages: Evidence from China.

Based on the data from the China Family Panel Studies (CFPS) in 2018, the relationship between internet use and informal workers' wages and its internal mechanism were empirically discussed using the ordinary least squares and endogenous switching regression(ESR) model. The study found that internet use could significantly raise the level of wages of informal workers, and this conclusion still holds after the endogenous problem was solved through the endogenous switching regression model. Further research found that the influences of the internet use on informal workers' wages was heterogeneous. In other words, internet use has a more obvious impact on the wages of informal workers aged 31 to 40, 41 to 50, and 51 to 60 with the educational level of university and above in cities and towns, while it has a significant negative impact on wages of informal workers aged 16 to 20.

Differences between returns to education in Urban and rural China and its evolution from 1989 to 2019.

The income gap between urban and rural residents has long been a predicament for China. The differences between returns to education in urban and rural China are one of the important factors affecting the income gap. Using a combination of data from CHNS, CHIP, CGSS, CFPS, CHFS, and CSS, the differences in returns to education and its evolution in China from 1989 to 2019 were estimated. Results show that returns to education in urban China have been consistently higher than that in rural China. Returns to education in urban China show a trend of progressive increase, then a rapid rise, before turning into a slow decline and gradually leveling off; returns to education in rural China exhibit a slowly increasing trend before gradually leveling off; the differences between returns to education in urban and rural China show an evolution of first growing larger, then smaller, before gradually leveling off. The spouse's education was considered the instrumental variable of individuals' education. The robustness test was done with an estimation through a two-stage least squares (2SLS) method. Results indicate that the empirical conclusion has good robustness. The evolution of returns to education in China was explained in terms of the marketization of labor forces, the relative supply and demand of labor forces, the reform of the household registration system, and the evolution of the quality of education.