The aim of this paper is to provide a clear insight about the determinants of female employment rate in the European Union where we have used panel data analyses of 27 countries members of the European Union from 1995...The aim of this paper is to provide a clear insight about the determinants of female employment rate in the European Union where we have used panel data analyses of 27 countries members of the European Union from 1995 till 2009. Applying dynamic modeling, i.e, generalized method of moments （GMM） econometrics findings have driven us to system estimated model where the following institutional variables have been tested： maternity leave, child care facilities, college education, fertility rate, GDP growth, female unemployment rate and part-time employment. We expect these variables to have a positive impact on the female employment rate except for the female unemployment rate and maternity leave展开更多
Promoting women’s employment is not only the need of social and economic development,but also the historical mission of liberating women.This paper uses data from the 1%Population Sample Survey,taken in Guangdong Pro...Promoting women’s employment is not only the need of social and economic development,but also the historical mission of liberating women.This paper uses data from the 1%Population Sample Survey,taken in Guangdong Province in 2015,to explore how women’s marital status,education,and family environment affect the female non-agricultural employment rate(FNAER)on a county scale using a spatial-lag model.The results show that:1)The female non-agricultural employment rate in counties of Guangdong Province is low,with more than three-quarters of counties having female non-agricultural employment rate less than 50%.Moreover,the spatial distribution of FNAER is uneven,with the high-value areas concentrated in the southeast and the low-value areas mainly distributed in the central and western parts of Guangdong Province.2)From the perspective of industry,there are significant spatial differences among women.In the southeast,women are mainly engaged in the secondary industry,while in the central and western regions,women are mainly engaged in the tertiary industry.3)Women having better skills and more effective support from the elderly can improve the FNAER.Women having lower skills,smaller-scale families,a higher fertility rate,and households with two or more elderly members have a negative effect on the FNAER.4)Public policies suggest that improving women’s education and their family environment,building social welfare facilities,and repairing the family environment will increase the FNAER.展开更多
文摘The aim of this paper is to provide a clear insight about the determinants of female employment rate in the European Union where we have used panel data analyses of 27 countries members of the European Union from 1995 till 2009. Applying dynamic modeling, i.e, generalized method of moments （GMM） econometrics findings have driven us to system estimated model where the following institutional variables have been tested： maternity leave, child care facilities, college education, fertility rate, GDP growth, female unemployment rate and part-time employment. We expect these variables to have a positive impact on the female employment rate except for the female unemployment rate and maternity leave
基金Under the auspices of National Natural Science Foundation of China(No.41471111)。
文摘Promoting women’s employment is not only the need of social and economic development,but also the historical mission of liberating women.This paper uses data from the 1%Population Sample Survey,taken in Guangdong Province in 2015,to explore how women’s marital status,education,and family environment affect the female non-agricultural employment rate(FNAER)on a county scale using a spatial-lag model.The results show that:1)The female non-agricultural employment rate in counties of Guangdong Province is low,with more than three-quarters of counties having female non-agricultural employment rate less than 50%.Moreover,the spatial distribution of FNAER is uneven,with the high-value areas concentrated in the southeast and the low-value areas mainly distributed in the central and western parts of Guangdong Province.2)From the perspective of industry,there are significant spatial differences among women.In the southeast,women are mainly engaged in the secondary industry,while in the central and western regions,women are mainly engaged in the tertiary industry.3)Women having better skills and more effective support from the elderly can improve the FNAER.Women having lower skills,smaller-scale families,a higher fertility rate,and households with two or more elderly members have a negative effect on the FNAER.4)Public policies suggest that improving women’s education and their family environment,building social welfare facilities,and repairing the family environment will increase the FNAER.
