(a) What is the interpretation of the female coecient? (Do not rely on approxima
ID: 3315408 • Letter: #
Question
(a) What is the interpretation of the female coecient? (Do not rely on approximations)
(b) What is the predicted wage (in dollars) for a married man with a high school education (12 years)? and two years experience?
(c) What is the predicted wage (in dollars) for a married woman with a college education (16 years)? and three years experience?
(d) Suppose we had just included education, experience and the married dummy as explanatory variables. How might we go about testing whether there is a dierence for men and women?
1. (30pts) Consider the log-wage regression below. Here the explanatory variables are years of education (educ), years of experience (exper) and the following dummy variables: the respon dent is a woman (female), the respondent is married (married), and a dummy for married men (marrMale) 526 67.00 - 0.0000 - 0.3918 Adj R-squared - 0.3860 41652 Source I df MS Number of obs F(5, 520) Model I 58. 1171642 Residual 90.2125872 5 11.6234328 Prob> F 520 .173485745 R-squared Total | 148.329751 525 28253286 Root MSE lwage I Coef. Std. Err. [95% Conf. Interval] educ 0865838 .0070179 12.34 0.000 4.86 0.000 072797 0043493 female I1106716 0589208 1.88 0.0612264238 married .0300028 0540163 -0.56 0.579 .1361197 2048046 . 1502971 . 1003706 0102554 0050805 0761142 5017559 5622647 exper0073023 .0015032 marrMale 3532803 .0755779 cons 3562809 1048511 4.67 0.000 3.40 0.001Explanation / Answer
a) For females, there is 0.1106716 units less log wage as compared to males
b) logwage= 0.3562809+12*0.865838+2*0.0073023-.0300028+.3532803 = 11.08422
wage= e^11.08422 = $65135.11
c) logwage =0.3562809+16*0.865838+3*0.0073023-0.1106716-.0300028 = 14.0909214
wage = e^14.0909214 = $1317072
d) coefficient of women = beta
->log wage for women is beta less/more than that of men
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