I) Akçomak and Kasnakolu (2002) estimated earning differentials in Ankara using
ID: 3314298 • Letter: I
Question
I) Akçomak and Kasnakolu (2002) estimated earning differentials in Ankara using a semi-logarithmic single equation models based on the basic human capital approach The following table is taken from their research where all variables on the right hand side are dummy variables having the value one for the designated category a) Interpret the results. (Remember the main question of the research is to explain the the relation between earnings and age, education and gender.) b) What is the average log hourly wage of an 20-year old illeterate woman? Dependent Variable: Logaritm of Hourly Earnings onstant 9.381 32.359 Age 18-29 Age 30-34 Age 35-39 0.629 6.205 0.172 .538 0.023 0.201) 40-44 1.054 0.010 0.083 Age 45.49 0.361 4.692 0.218 0.626 0.521 1.809 0.697 53 0.824 2.841 457 5,017 Male Lite rate Primar Second High Univers R. sqr 0.269 0.258 25.182 766 Note: The values in parentheses are t-values. The constant term represents a person who is older than 49; female illiterateExplanation / Answer
(a) Here these are the main takeaway from the regression results are:
(i) As the age of sample population increases, the coefficient for age with income goes from negative to positive, that shows that as age increases income tend to increase.
(ii) Here we can see that coefficient for male is positive, that shows that male tend to earn more income than female.
(iii) Here as we go higher in education, then the coefficient of education increases with the education level.
(iv) Here we see that t - values are more than +-1.96 (as n is very higher) for Age(18-29) and for male , for secondary and for university independent variable.
So, these are significant variable which put more effect on the income.
(b) averaeg log hourly wage for age 20 illeterate women = 9.381 - 0.629* age = 9.381 - 0.629 = 8.752