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

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.