Wage Regression Analysis Using Stata: Exploring the Impact of Education, Experience, and Tenure

(1) Use the command 'summarize educ' to get the minimum and maximum education years in the sample and the number of people with those education levels.

(2) Use the command 'by gender: summarize educ' to get the average education years for male and female workers. Use the command 'ttest educ, by(gender)' to test if there is a significant difference in average education years between male and female workers.

(3) Use the command 'reg logwage educ exper tenure female' to estimate the model. Use the command 'test educ exper tenure female' to perform an F test on the overall significance of the model.

(4) Null hypothesis: β1 = 0 Alternative hypothesis: β1 > 0 Use the command 'reg wage educ' to estimate the model. Use the command 'test educ' to test the hypothesis. If the p-value is less than 0.05, reject the null hypothesis and conclude that education has a positive effect on wage.

(5) Use the command 'reg wage educ' to estimate the model. Look at the coefficient on educ to see the exact effect of education on wage.

(6) Null hypothesis: β2 = β3 Alternative hypothesis: β2 ≠ β3 Use the command 'reg wage educ exper tenure female' to estimate the model. Use the command 'test exper = tenure' to test the hypothesis. If the p-value is less than 0.05, reject the null hypothesis and conclude that exper and tenure have different effects on wage.

(7) Use the command 'reg logwage educ exper tenure female c.exper#c.exper' to estimate the model. Look at the coefficient on exper to calculate the effect of the first and fifth year of experience and the turning point.

(8) Null hypothesis: β6 = 0 Alternative hypothesis: β6 ≠ 0 Use the command 'reg logwage educ exper tenure female c.exper#c.educ' to estimate the model. Use the command 'test c.exper#c.educ' to test the hypothesis. If the p-value is less than 0.05, reject the null hypothesis and conclude that the return of experience depends on education received. Use the command 'margins, dydx(exper)' to calculate the average partial effect of experience.

(9) Use the command 'reg logwage educ exper tenure female c.exper#c.exper c.exper#c.educ' to estimate the model. Use the command 'test c.exper#c.exper = c.exper#c.educ = 0' to perform an F test and use the command 'estat lmtest' to perform an LM test. If both tests have p-values greater than 0.05, do not add both exper² and educ x exper into the model.

(10) Use the command 'reg logwage educ exper tenure female' to estimate model (1), 'reg wage educ' to estimate model (2), 'reg logwage educ exper tenure female c.exper#c.exper' to estimate model (3), and 'reg logwage educ exper tenure female c.exper#c.exper c.exper#c.educ' to estimate model (4). Use the command 'estimates table' to tabulate the results.