Dependent Variable: LNWAGE Method: Least Squares Date: 09/28/15 Time: 13:53 Samp

Question

Dependent Variable: LNWAGE Method: Least Squares Date: 09/28/15 Time: 13:53 Sample: 1 1000 Included observations: 1000 EDUC=No of years of education; EXPER= No of years of experience and HSRWK=Hours worked per week. Write down the estimated equation and interpret all the regression coefficients in terms their magnitude and statistical significance at 5% level. Test the hypothesis that an extra year of education does not have any significant effect on the rate of changing of their wages. Test the hypothesis that an extra year of education has a significant positive effect on the rate of changing of their wages.

Explanation / Answer

(a) LNWAGE = 1.100540 + 0.090306EDUC + 0.005776EXPER + 0.008941HRSWK
A unit increase in education positively impacts Wage by a change of $0.09.
A unit increase in experience positively impacts Wage by a change of  $0.005
A unit increase in hours worked per week positively impacts Wage by a change of  $0.009.

P-value of all the variables is 0. That is, p-value is less than the significance level of 5%. Hence, all the coefficient are statistically significant.

(b) and (c) An extra year increase in education positively impacts Wage by $0.09. Hence, an extra year of education does have a significant effect on rate of change of wages. In fact that effect is positive.

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