a) estimated returns on education as per 1st model is 0.118
as per 2nd model : 0.062
And as per 3rd model: 0.116
All are positive, hence education has positive effect
Model 1 and 3 are showing negative coefficient of meduc.educ, that means mother's education has negative effect.
B) null hypothesis
H0 : meduc = 0
Alternative hypothesis
H1 : meduc > 0
here t-statistic will be used
For model 1
meduc = 0.095
It is significant at 0.01 level, hence it will be significant at 0.05 level
For model 2
meduc = 0.094
It is also significant at 0.01 level, hence it will be significant at 0.05 level of significance.
Hence, as per both the models, mother's education has positive effect on wages.
C) increase in tenure period would have an impact on the earnings. An idiindivid would have gain a lot of knowledge in an additional year of tenure, which may help him to earn extra income in the subsequent years. Hence, variable tenure is important for the model.
D) coefficient of variable married.ten is negative in both the models but they are not statistically significant. Hence we cannot say anything bout effect of tenure on married worker and non-married worker.
0.024 .00 d5 002 0.009 0.0033(.005) Constant 100 .324) a What is the estimated ctr to eacandeely o setively on education? Explain. (2ps) b. Based on the estimated models (1)nd (...
II. (15pts) You are given the following three estimated models, with all the variables described as in question II Dependent variable: educ 0.118***0.062***0.116** (0.024) (0.006) (0.024) meduc 0.094* C0.029) 0.095*** (0.029) married 0.252*0.247** (0.071) (0.068) 0.025 0.026* 0.020** (0.011) (0.011) (0.009) meduc.educ -0.006 C0.002) 0.006* C0.002) marrted. ten 0.009 (0.000 C0.009) (0.009) 0.0002 -0.0003 0.0003 C0.001) (0.0005) (0.001) Constant 4.694*** 5.597*** 4.932 (0.325) (0.100) (0.324) observations 857 R2 857 857 0.152 0.175 *p<0.1; p<0.05; p<0.01 Note: a. Wha education? Explain....
asap i beg u IL. (15pts) You are given the following three estimated models, with all the variables described as in question II Dependent variable: log (wage) educ 0.056** 0.062* 0.049* 0.022) (0.006) (0.022) feduc 0.027 C0.027) 0.021 0.028) married 1.000 0.606 (0.518) (0.466) age 0.032 C0.114) (0.103) (0.116) 0.034 feduc. educ -0.001 (0.002) -0.0003 (0.002) married.age 0.037 0.025 C0.016) (0.014) 0.001 0.001 -0.00000 C0.002) C0.002) C0.002) agesq Constant 5.306**5.218* 5.090*** (1.923) C1.723) C1.932) observations 741 R2 741 0.151 741...