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Hi all. Is anyone have the STATA result for William Greene – Econometric Analysis 8th. Chapter 6, Application for 1 and 3.
Example.
In application 1 in chapter 3 and application 1 in chapter 5, we examined Koop and tobias’s data on wages, education, ability, and so on. We continue the analysis here. (the source, location and configuration of the data are given in the earlier application.) We consider the model
ln Wage = b1 + b2 Educ + b3 Ability + b4 Experience
+ b5 Mother’s education + b6 Father’s education + b7 Broken home + b8 Siblings + e.
Col = 1 if Educ 7 12 and Educ … 16, 0 otherwise
Grad = 1 if Educ 7 16, 0 otherwise.
replace Educ in the model with (Col, Grad), making high school (HS) the base category, and recompute the model. report all results. how do the results change? Based on your results, what is the marginal value of a college degree? What is the marginal impact on ln Wage of a graduate degree?
c. the aggregation in part b actually loses quite a bit of information. another way to introduce nonlinearity in education is through the function itself. add Educ2 to the equation in part a and recompute the model. again, report all results. What changes are suggested? test the hypothesis that the quadratic term in the equation is not needed—that is, that its coefficient is zero. Based on your results, sketch a profile of log wages as a function of education.
d. onemightsuspectthatthevalueofeducationisenhancedbygreaterability.We could examine this effect by introducing an interaction of the two variables in the equation. add the variable
Educ_Ability = Educ * Ability
to the base model in part a. now, what is the marginal value of an additional year of education? the sample mean value of ability is 0.052374. compute a confidence interval for the marginal impact on ln Wage of an additional year of education for a person of average ability.
e. combine the models in c and d. add both Educ2 and Educ_Ability to the base model in part a and reestimate. as before, report all results and describe your findings. if we define low ability as less than the mean and high ability as greater than the mean, the sample averages are -0.798563 for the 7,864 low-ability individuals in the sample and + 0.717891 for the 10,055 high-ability individuals in the sample. using the formulation in part c, with this new functional form, sketch, describe, and compare the log wage profiles for low- and high-ability individuals.
in solow’s classic (1957) study of technical change in the u.s. economy, he suggests the following aggregate production function: q(t) = A(t) f [k(t)], where q(t) is aggregate output per work hour, k(t) is the aggregate capital labor ratio, and A(t) is the technology index. solow considered four static models,
q/A = a + b ln k, q/A = a – b/k, ln(q/A) = a + b ln k,andln(q/A) = a + b/k. solow’s data for the years 1909 to 1949 are listed in appendix table F6.4.
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