log using choice_binary_revised.log, replace
use choice_binary.dta
set more off
 
list  job age school gender

regress  job age school gender
predict p_lpm, xb

regress  job age school gender, robust

logit  job age school gender
predict p_logit, p
mfx compute
*dlogit2  job age school gender

logistic  job age school gender
predict p_logistic, p
mfx compute

probit  job age school gender
predict p_probit, p
mfx compute
*dprobit  job age school gender

list  p_lpm p_probit p_logit p_logistic

* WLS

gen sigi = sqrt(p_lpm*(1-p_lpm))
gen job1 = job/sigi 
gen age1 = age/sigi 
gen school1 = school/sigi
gen gender1 = gender/sigi 
gen sigi_inv = 1/sigi

regress  job1 age1 school1 gender1 sigi_inv, noconst

regress  job age school gender [aw = 1/sigi] 
wls0 job age school gender, wvar(sigi) type(abse) noconst graph
wls0 job age school gender, wvar(sigi) type(e2) noconst graph


/* WLS: example of Greene chapter 12 */

use http://www.ats.ucla.edu/stat/stata/examples/greene/TBL5-1, clear

rename x1 age
rename x2 income
rename x3 exp
rename x4 ownrent
rename x5 selfemp

generate incomesq = income^2
drop if exp==0
save chapter12, replace

/* summary check */

gen age1     = age  / income^0.5
gen income1  = income / income^0.5
gen exp1     = exp / income^0.5
gen ownrent1 = ownrent / income^0.5
gen selfemp1 = selfemp / income^0.5
gen incomesq1 = incomesq / income^0.5
gen const1 = 1 / income^0.5

wls0 exp age ownrent income incomesq , wvar(income) type(abse) noconst          /* 12.3a */
regress exp age ownrent income incomesq [aw = 1/income]
regress exp1 age1 ownrent1 income1 incomesq1 const1, noconstant
regress exp1 age1 ownrent1 income1 incomesq1

/* end of checkup */

log close