The Influence of Internet Usage on Gender Division of Labour Bias: Evidence from Chinese General Social Survey Data

Abstract

Based on data from 18,741 respondents in the 2010 and 2017 Chinese General Social Survey, this paper empirically analyzes the influence of Internet usage on gender division of labour bias by using the propensity score matching model and tests the sensitivity of the estimated results. The results show that firstly, a series of personal characteristics such as gender, age, years of education, ethnicity, political status, health status, marital status, household registration status, labour income, mother’s years of education, and family economic status will have a significant impact on whether they frequently use the Internet. Secondly, frequent internet usage can significantly reduce respondents’ agreement of gender division of labour bias, indicating that frequent internet usage can significantly improve respondents’ gender division of labour bias, and the results of Rosenbaum’s bound test and H-L confidence interval test both support the above conclusions. Thirdly, frequent internet usage can significantly reduce the recognition degree of women respondents and men respondents to gender division of labour bias, which indicates that frequent internet usage can not only strengthen women’s self-identity to a great extent but also improve men’s exclusion bias to a certain extent. Therefore, this paper puts forward some suggestions from two aspects: improving the accessibility of internet usage and guiding and controlling the content and behavior of various online media.