Gender Pay Gap And Its Causes In Anhui Province Based On Kernel Density Estimation

Since China’s economy has achieved rapid growth since China adopted the reform and opening up policy. Personal gender income residents has been steadily improving. But personal income gap is widening. There are many reasons for this situation. Different sex and gender discrimination are the main cause of this situation. Gender factors had an impact on many industries. Research on the development of social gender pay a lot of sense. Anhui province is a typical province in central China. Reaching in Anhui province means a lot to the other provinces in central China.In this paper, we had a discuss in the gender income situation in Anhui. It may analyze the reasons for this phenomenon. We can make recommendations to solve the problem.In this paper, I used the CHIP data of1998,2002and2008. I chose the part of Anhui province. Then I achieved the distribution of income by kernel density distimation. We may find the increasing of personal income through the distribution of income. After that,1achieved the gender distribution of income. It is easy to find out that the income of men much higher than that of women. Obviously, there are many differences in gender income gap between different income levels. There is a huge gap among low-income groups. Sexism and physical condition are the main reasons of gender pay gap. We may get a new distribution of income if women and men in the same physical condition. There is a new gender pay gap without the same physical condition. We can find that sexism and physical condition are the main reason of gender by the new distribution by the new gender pay gap. It is a good way to make a deep study of the gender pay gap. We can achieve the person reasons of gender pay gap and we may use the model of Becker to analysis the sexism. At last, we can get the method according to the analysis to solve the sexism and gender pay ga.The paper does make a lot of sense by reaching on the gender pay gap. It helps us to study the change of gender pay gap and we can find new countermeasures for the difficult situation. It also helps to promote national stability.The date of this reach is the part of the CHIP data of1998,2002and2008. But the data which I chose is not very comprehensive. There may be errors because of the un comprehensive data.