Background:
In your role as an economic analyst you have been asked the following question:
• How much does education affect wage rates?
The Excel data file (wage) contains 100 observations for each of the following variables:
| Variable |
Label |
| wage |
Earning per hour |
| In_wage |
The log of earning per hour |
| educ |
Years of education |
| educ2 |
Years of education squared |
Instructions:
Conduct a simple linear regression analysis to examine the relationship between 'education' (the independent variable) and 'wage' (the dependent variable). Using the Excel data file, prepare a 2000 word report using the following structure:
• Purpose
• Background
• Method
• Results
• Discussion
• Recommendations
In preparing your report you must address the following questions:
(a) Obtain summary statistics and histograms for the variables WAGE and EDUC. Discuss the data characteristics.
(b) Estimate the linear regression WAGE: β1 + β2EDUC + ε and interpret the slope.
(c) Calculate the residuals and plot them against EDUC. Are any patterns evident and, if so, what does this mean?
(d) Estimate the quadratic regression WAGE = α1 + α2EDUC2 + ε and interpret the results. Estimate the marginal effect of another year of education on wage for a person with 12 years of education, and for a person with 14 years of education. Compare these values to the estimated marginal effect of education from the linear regression in part (b).
(e) Construct a histogram of ln(WAGE). Compare the shape of this histogram to that for WAGE from part (a). Which appears to be more symmetric and bell-shaped?
(f) Estimate the log-linear regression ln(WAGE) = γ1 + γ2EDUC + ε and interpret the slope. Estimate the marginal effect of another year of education on wage for a person with 12 years of education, and for a person with 14 years of education. Compare these values to the estimated marginal effects of education from the linear regression i n part (b) and quadratic in part (d).
Attachment:- wage.xlsx