Entering the labor market or continuing education beyond a certain point is a very important individual level investment decision. An important determinant of the demand for education is its expected benefits. The benefits depend upon the value of an individual’s labour input, which in turn depends upon the level of education. Hence, the education-wage relationship can be used to measure the returns to schooling.
The rural and urban sectors differ widely in terms of the education and employment opportunities available to their residents. Rural areas widely, however not solely, depend on agriculture for livelihood while the range of jobs in urban areas is broader. These factors, such as different availability of jobs, lead to a different demand …show more content…
Specifically, this study will use the NSS rounds 55(1999), 61(2004), 64(2007), 66(2009), and 68(2011). The survey is nationally representative and covers almost every part of India excluding a few very remote and inaccessible areas. Each round of the NSS survey covers approximately 260,000 to 340,000 individuals. Over the five rounds, there are a total of about 1,650,000 observations. The numbers of observations are almost equal for both men (836,434) and women (813,542) and there are more observations for the rural sector (1,009,007) than the urban sector …show more content…
In this equation, β1, the coefficient on EducationLevel dummies, can be interpreted as the rate of return to the given level of schooling. The Exp variable in the equation captures the fact that an individual with higher experience in a job is likely to earn better. The Exp2 term encapsulates the likelihood of a non-linear relationship between earnings and experience.
This paper then attempts to use the Oaxaca Blinder (1973) decomposition to divide the differential returns to education in rural and urban India into two parts. The first part is the one that is explained by the differences in observable characteristics of the two sectors and the other is the residual part which stems from the differences in estimated coefficients. These two parts are also termed as the characteristic effect and the coefficient effect.
YU – YR = BU (XU- XR) + (BU + BR)
The rural and urban sectors differ widely in terms of the education and employment opportunities available to their residents. Rural areas widely, however not solely, depend on agriculture for livelihood while the range of jobs in urban areas is broader. These factors, such as different availability of jobs, lead to a different demand …show more content…
Specifically, this study will use the NSS rounds 55(1999), 61(2004), 64(2007), 66(2009), and 68(2011). The survey is nationally representative and covers almost every part of India excluding a few very remote and inaccessible areas. Each round of the NSS survey covers approximately 260,000 to 340,000 individuals. Over the five rounds, there are a total of about 1,650,000 observations. The numbers of observations are almost equal for both men (836,434) and women (813,542) and there are more observations for the rural sector (1,009,007) than the urban sector …show more content…
In this equation, β1, the coefficient on EducationLevel dummies, can be interpreted as the rate of return to the given level of schooling. The Exp variable in the equation captures the fact that an individual with higher experience in a job is likely to earn better. The Exp2 term encapsulates the likelihood of a non-linear relationship between earnings and experience.
This paper then attempts to use the Oaxaca Blinder (1973) decomposition to divide the differential returns to education in rural and urban India into two parts. The first part is the one that is explained by the differences in observable characteristics of the two sectors and the other is the residual part which stems from the differences in estimated coefficients. These two parts are also termed as the characteristic effect and the coefficient effect.
YU – YR = BU (XU- XR) + (BU + BR)