Consider the following regression of wages (w) on the mean years of schooling ofย
workers (s) and the female share in an occupation (p):
๐๐๐๐ค = 0.924 + 0.150๐ โ 0.003๐
ย (0.154) (0.011) (0.0001)
a) Interpret the regression coefficients carefully.
b) How much variations in wages can be explained by the two regressors?
c) Would you reject the hypothesis that workersโ mean years of schooling has noย
influences on wages across professions?
The Given regression equation is
"\ud835\udc59\ud835\udc5c\ud835\udc54\ud835\udc64 = 0.924 + 0.150\ud835\udc60 \u2212 0.003\ud835\udc5d"
(a) On comparing the given equation with the standard regression equation "Y=\\beta_0+\\beta_1x_1+\\beta_2x_2"
Regression coeffiecient are as follows.
We get "\\beta_1=0.15, \\beta_{2}=-0.003"
(b) As the coffiecient "\\beta_2" is very small So The wage "w" is not too much influenced and on changing other coeffecient. The wage w is increased rapidly.
(c) No. The mean year of schooling also affects the wage of the worker since It has a positive regression coefficient. On a small change in mean year of schooling can change the wages.
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