Suppose we are interested in measuring the relationship between log wages (variable /wage), and an individual's...

  

Transcribed Image Text:

Suppose we are interested in measuring the relationship between log wages (variable /wage), and an individual's education level (variable educ, measured in years) and years of labor market experience (variable exper, measured in years). We estimate the following equation in STATA : Iwage=yo+yeduc+12 exper+u and get the regression output below. . reg wage educ exper Source SS df MS Number of obs = 526 F( 2, 523)= 86.86 Model Residual 111.344712 523 Total 2 18.4925198 .212896199 148.329751 525 .28253286 Prob F 0.0000 R-squared Adj R-squared = Root MSE .46141 1wage Coef. Std. Err. t P>|t| [95% Conf. Interval] educ .0979356 exper _cons .0103469 .2168544 .0076224 .0015551 .108595 12.85 6.65 0.000 0.000 .0829613 .1129099 .0072919 2.00 0.046 .0035183 .013402 .4301904 a.) Interpret the coefficient estimate on education. b.) What is the predicted difference in wage for a college graduate (i.e. years of education=16) versus a high school graduate (i.e. years of education=12) with the same level of experience? c.) Compute the explained sum of squares and R. Be sure to write out the formulas you use for your calculations. Suppose we are interested in measuring the relationship between log wages (variable /wage), and an individual's education level (variable educ, measured in years) and years of labor market experience (variable exper, measured in years). We estimate the following equation in STATA : Iwage=yo+yeduc+12 exper+u and get the regression output below. . reg wage educ exper Source SS df MS Number of obs = 526 F( 2, 523)= 86.86 Model Residual 111.344712 523 Total 2 18.4925198 .212896199 148.329751 525 .28253286 Prob F 0.0000 R-squared Adj R-squared = Root MSE .46141 1wage Coef. Std. Err. t P>|t| [95% Conf. Interval] educ .0979356 exper _cons .0103469 .2168544 .0076224 .0015551 .108595 12.85 6.65 0.000 0.000 .0829613 .1129099 .0072919 2.00 0.046 .0035183 .013402 .4301904 a.) Interpret the coefficient estimate on education. b.) What is the predicted difference in wage for a college graduate (i.e. years of education=16) versus a high school graduate (i.e. years of education=12) with the same level of experience? c.) Compute the explained sum of squares and R. Be sure to write out the formulas you use for your calculations.