/* Examples of dummy independent variables 
Data " cps_msa2013 : 2013 Current population survey for 3 MSA
3 MSA : NY, LA, CHICAGO
*/  
clear all
use https://bigblue.depaul.edu/jlee141/econdata/cps_data/cps_msa2013

/* 1. Creating continuous education variable 
Number of Years of Education */

// tablulate the educ92 
tab educ92
// tablulate the educ92 without label 
tab educ92, nolabel 

gen educyr = 0 
replace educyr =  1 if educ92 == 1 
replace educyr =  4 if educ92 == 2 
replace educyr =  6 if educ92 == 3 
replace educyr =  8 if educ92 == 4 
replace educyr =  9 if educ92 == 5 
replace educyr =  10 if educ92 == 6 
replace educyr =  11 if educ92 == 7 
replace educyr =  12 if educ92 == 8  |  educ92 == 9  
replace educyr =  14 if educ92 == 10 | educ92 == 11 | educ92 == 12 
replace educyr =  16 if educ92 == 13 
replace educyr =  18 if educ92 == 14  
replace educyr =  20 if educ92 == 15 
replace educyr =  21 if educ92 == 16 

/* 2. Creating simple dummy variable 
Here are some examples to create simple dummy variables */

gen young = 0 
replace young = 1 if age < 25 

gen retired_age = age > 65 
gen retired_man = (age > 65 & female == 0 )

/*  3. Creating multiple dummy variables  
Here are some examples to create multiple dummy variables 
wbho (white, black, hispanic, others) 
-> generate four dummy variables (race1, race2, race3, race4) 
*/

tab wbho 
tab wbho, gen(race)
sum race1-race4

/* 4. Regression using dummy and factor varibles */
keep if hrwage < 1000
keep hrwage educ92 educyr female race1 race2 race3 race4 wbho
drop if (educ92 == . | wbho == . | female == .)


regr hrwage educyr female
eststo 
regr hrwage educyr female race2-race4
eststo 
regr hrwage educyr female i.wbho 
eststo 

esttab, r2 ar2