DIVIDERL ASSIGNMENT 30% QUESTION 1. a. Discus econometric problems (nature, cause, consequence and remedial for each problems b. What does mean series is stationary explain it? c. Explain random effect model and fixed effect model Question 2 We are estimating the relationship between graduating from high school and your congnitive ability. The two variables are GRAD and ASVBC. The GRAD variable is binary response which is 0 if your years of schooling is below 12 and 1 if the years of schooling is above and equal to 12. We run a probit function The output is given below probit GRAD ASVABC SM SE MALE Iteration 0: Iteration 1: Iteration 2: Iteration 3 : Iteration 4: log likelihood - -118.67769 log likelihood - -98.195303 log likelihood - -96.666096 log likelihood - -96.624979 log likelihood - -96.624926 Probit estimates Number of obs LR chi2 (4) Prob > chi2 Pseudo R2 540 44.11 0.0000 0.1858 Log 11 kelihood - -96.624926 GRAD Coef std. Err Z P>z! [95+ Conf. Interval) ASVABC1 .0648442 SM -.0081163 SPI .0056041 MALE .0630588 cons 1 -1.450787 0120378 0440399 0359557 . 1988279 5470608 5.39 -0.18 0.16 0.32 -2.65 0.000 0.854 0.876 0.751 0.008 .0412505 -.094433 -.0648677 -.3266368 -2.523006 .0884379 . 0782004 .0760759 .4527544 -.3785673 dp a. Derive the marginal effect dx b. Interpret the results making use of the additional information below. DIVIDERL ASSIGNMENT 30% QUESTION 1. a. Discus econometric problems (nature, cause, consequence and remedial for each problems b. What does mean series is stationary explain it? c. Explain random effect model and fixed effect model Question 2 We are estimating the relationship between graduating from high school and your congnitive ability. The two variables are GRAD and ASVBC. The GRAD variable is binary response which is 0 if your years of schooling is below 12 and 1 if the years of schooling is above and equal to 12. We run a probit function The output is given below probit GRAD ASVABC SM SE MALE Iteration 0: Iteration 1: Iteration 2: Iteration 3 : Iteration 4: log likelihood - -118.67769 log likelihood - -98.195303 log likelihood - -96.666096 log likelihood - -96.624979 log likelihood - -96.624926 Probit estimates Number of obs LR chi2 (4) Prob > chi2 Pseudo R2 540 44.11 0.0000 0.1858 Log 11 kelihood - -96.624926 GRAD Coef std. Err Z P>z! [95+ Conf. Interval) ASVABC1 .0648442 SM -.0081163 SPI .0056041 MALE .0630588 cons 1 -1.450787 0120378 0440399 0359557 . 1988279 5470608 5.39 -0.18 0.16 0.32 -2.65 0.000 0.854 0.876 0.751 0.008 .0412505 -.094433 -.0648677 -.3266368 -2.523006 .0884379 . 0782004 .0760759 .4527544 -.3785673 dp a. Derive the marginal effect dx b. Interpret the results making use of the additional information below