I am using a mincerian wage equation to estimate the returns to education. I came across two ways to include the education dummies.
i) Using the normal dummy variable command by i.education and regressing log wage on that after including other controls. The base category is taken as illiterates
ii) In the other method, I have used the sequential dummies. For instance, a for a graduate, the dummies for education levels below graduation takes the value 1 and for higher than graduation degree it takes value zero
I am a bit confused on which method to use to calculate the returns to education for each education level. Any suggestion on this would be extremely helpful.
i) Using the normal dummy variable command by i.education and regressing log wage on that after including other controls. The base category is taken as illiterates
ii) In the other method, I have used the sequential dummies. For instance, a for a graduate, the dummies for education levels below graduation takes the value 1 and for higher than graduation degree it takes value zero
Code:
gen educ=. replace educ=1 if General_edulevel<=4 & General_edulevel>=1 replace educ=2 if General_edulevel==5 replace educ=3 if General_edulevel==6 replace educ=4 if General_edulevel==7 replace educ=5 if General_edulevel==8 replace educ=6 if General_edulevel==10|General_edulevel==11 replace educ=7 if General_edulevel==12|General_edulevel==13 label define levedu 1 "Not Literate" 2 "Below Primary" 3 "Primary" 4 "middle" 5 "secondary" 6 "Higher Secondary" 7 "Graduate & above" label values educ levedu qui tab educ, gen (ed) levelsof educ, local(levs) foreach l of local levs{ replace ed`l'=1 if educ>=`l' }
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