Question

1II. (10 pts) You are given the following estimated equation In(wage)- 0.3688+0.0852educ + 0.05 teure-0.000994tenue 0.0908) (0.0069) (0.0068) (0.00025) R-0.3294 526 in which: logtwage) log of average hourly wage; educ is the number of years of schooling tenure is the number of years of tenure fenure tenure remure The plot of the residuals against the fitted values from the regression above, is provided below: 2.5 1.5 Fitted values .5 a. With a 1% significance level, are the explanatory variables individually significant? (3pts) b. Are they jointly significant (vith 1 % significance level)? ( 1 pt) c. From observing the residual plot above, which assumption from the classical linear regression analysis appears not to be satisfied? (1pt) d. What are the possible consequences for the OLS estimators, resulting from the assumption violated in found in question 'e"? (2pts) From an auxiliary regression of the squared residuals against the predicted values, and the squared predicted values, we obtained the following equation residuals -0.3944-0.3628 fittedvalues +0.1406 fittedvalues (0.0951) (0.2568) (0.3141) R2 = 0.0120 n=526

ONLY NEES A,B help please!!!

Answer 1

a) T cke.ck ure t- se(b) Tthe huul and airerare tpotaees eds Mesua .eng.NL (Ah C.쇼 ス·57 t value we clecl 2. we ant

Ч.OG 0 -12.3니 O006 S <o educahom is also goru. ,, Cant. for feru O. 00 6 2

for en 2. 3- 6 To chrck -13 R. O. 3294 1 0 3 52