Estimating married women labor supply model based on the latest statistical methods can effectively elucidate the effect of married women labor supply on tax and welfare changes. Married women labor supply model,in families in which both couples have jobs and non-labor incomes, has been estimated in the present study viaemploying Neoclassic Model framework. The research data were collected viainformation related to family income and costs during the year 1392. The estimation wasdone through eliminating selection bias and based on Generalized Method of Moments (GMM). The findings reveal that married women labor supply is standard and the personal wage elasticity is positive and significant. Thus welfare and tax-related plans have significant effects on decrease or increase in working hours of this group. The socio-cultural transformation study shows that there is a positive relationship between married women working hours and increase in their husbands’ income; along with matchmaking in marriage. Accordingly, it could be concluded that policies concerning increasing family non-labor income did not have significant effects on decreasing working hours of married women of the studied group.
Za’faranchi, L. S., Taee, H., Mohammadi, T., & Abdullah Milani, M. (2017). Eliminating Sample Selection Bias and Wage Variable Endogeneity in Estimating Married Women Labor Supply. Women Studies, 7(17), 95-115.
MLA
Leila Sadat Za’faranchi; Hassan Taee; Teimur Mohammadi; Mahnoosh Abdullah Milani. "Eliminating Sample Selection Bias and Wage Variable Endogeneity in Estimating Married Women Labor Supply". Women Studies, 7, 17, 2017, 95-115.
HARVARD
Za’faranchi, L. S., Taee, H., Mohammadi, T., Abdullah Milani, M. (2017). 'Eliminating Sample Selection Bias and Wage Variable Endogeneity in Estimating Married Women Labor Supply', Women Studies, 7(17), pp. 95-115.
VANCOUVER
Za’faranchi, L. S., Taee, H., Mohammadi, T., Abdullah Milani, M. Eliminating Sample Selection Bias and Wage Variable Endogeneity in Estimating Married Women Labor Supply. Women Studies, 2017; 7(17): 95-115.
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