Please explain the occupation and industry regressions in the gender wage gap accordingly: 1a)...

Question

Please explain the occupation and industry regressions in the gender wage gap accordingly:

1a) Using Fig. 1-5 (see attachment), draw or explain how occupational data would be derived and distributed on the scatter plot where the X-axis is the log wage and the Y-axis would be occupation (note: or is it segregation?); 1b) Using Fig. 9-7 (see attachment), draw or explain how the occupation regression equation would be distributed on the graph and its relationship to the x and y axis (note: what would be the Y-axis?).

2) Use the same graphs also explain the scatter plot and regression equation for industry as in question 1)

3) Is Duncan’s index necessary or used in calculating occupational and industry variables?

4) Please list any other studies that also estimate occupation and industry variables on the gender wage gap

Please address questions in detail. Full discussion please.

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Robert · Accepted Answer

Please explain the occupation and industry regressions in the gender wage gap accordingly: 
1a) Using Fig. 1-5 (see attachment), draw or explain how occupational data would be 
derived and distributed on the scatter plot where the X-axis is the log wage and the Y-axis 
would be occupation (note: or is it segregation?); 1b) Using Fig. 9-7 (see attachment), draw 
or explain how the occupation regression equation would be distributed on the graph and 
its relationship to the x and y axis (note: what would be the Y-axis?).
Income from employment refers to the payments basically in cash which are received by 
individual as a result of their involvement in paid or any self- employment job. Now for the 
measurement and definitional purpose we have distinguished income related to paid employment 
from the concept of direct employment. Income from employment is the direct wages and 
salaries in cash for the work done. It excludes the income from other source that is not related to 
direct employment like property income or social assistance. The wage primarily depends on two 
variables, years of schooling and work experience.  Higher the years of schooling, higher will be 
the wage for an individual. Similarly, longer the work experience, one would expect his or her 
earnings would be. 
The above graph is a scatter plot that shows the relation between the two variables: log wage and 
years of schooling.  The scatter plot of log-wages on the y-axes and education on the x-axis can 
be derived with the help of STATA.  The above scatter plot is consistent with a linear relation. It 
clearly shows that monthly average earnings tend to rise with an increase in years of schooling.
The above figure shows the earning differentials between men and women.  Major studies of 
labor economies confirmed that the average earnings of men in informal economy are more than 
average earnings of women in informal economy.  The average earnings of women are found to 
be lower than men across the occupations.  
Mincer model considers the wage differential between men and women can be corrected by the 
difference in the educational attainment and the years of experience.  
Mincer earnings functions can be represented as 
w=β0+β1sex+β2 age +β3 age 2+ education I +ui 
w is the log wage ,

Please explain the occupation and industry regressions in the gender wage gap accordingly: 1a) Using Fig. 1-5 (see attachment), draw or explain how occupational data would be derived and distributed...

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