A research on determinants of floating women's income with Bayesian Networks

Abstract

Based on the survey of floating women in Jiangsu province, the article establishes a directed acyclic graph of factors influence income of floating women by using Bayesian Networks. The result indicates that not all the individual characteristics have a direct effect on income. The relationships between income and individual characteristics are complicated. Age has a direct impact on education level and marital status. Domicile has a direct impact on education level. Educational level and marital status influence floating women's job. And different jobs offer different salary. So age, domicile, education level, and marital status have indirect influence on income through the job of floating women.