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Question 2 This question is on a study of the effects of location and education on wage outcomes. where the following equation was estimated: In(wage) = Qo+ajeduc + Q2south + azurban + Q4south * urban + u where, In-natural logs, wage-monthly wage, educ-years of education, south is a dummy equal to 1 if the respondent lives in the south and 0 otherwise (i.e., north). Similarly urban = 1 if living in a city and 0 otherwise (i.e., in a rural area). The estimation results are reported in th table: 3/5 Source 1 SS df MS Number of obs F 4, 930) = 42.17 Model 25.4347562 6.35868906 Prob > F 0.0000 Residual 140.221538 .150775847 R-squared 0.1535 Adj R-squared 0.1499 Total 1 165.656294 934 .177362199 Root MSE .3883 ... 4 930 lwage 1 Coef. Std. Err. t P>t! [95% Conf. Interval) ### ###### ## educ south 1 urban south_urban cons 1 .0552406 -.0819054 .1840049 ..0724756 5.946937 .0058354 .048621 .0362901 .0583629 .0853035 3 a) Write your interpretation of the coefficient on the interaction term. Then test its statistical significance at the 10% significance level. (6 marks) Question 2 = This question is on a study of the effects of location and education on wage outcomes. where the following equation was estimated: In(wage) = 40 + Q educ + a south + azurban + Q4south * urban + u where, In-natural logs, wage-monthly wage, educ-years of education, south is a dummy equal to 1 if the respondent lives in the south and 0 otherwise (i.e., north). Similarly urban = 1 if living in a city and 0 otherwise (i.e., in a rural area). The estimation results are reported in the following table: Source 1 SS df MS = Model 1 Residual 25.4347562 140.221538 4 930 6.35868906 .150775847 Number of obs = F 4, 930) Prob > F R-squared Adj R-squared Root MSE 935 42.17 0.0000 0.1535 0.1499 . 3883 Total ! 165.656294 934 .177362199 lwage 1 Coef. Std. Err. t P>It! (95% Conf. Interval] ### educ 1 south urban south_urban! cons 0552406 -.0819054 .1840049 -.0724756 5.946937 .0058354 .048621 .0362901 .0583629 .0853035 # # # 3