* EconS 512 HW 2
* Jiehong Qiu
* 10 Nov. 2016


cd "C:\Users\qjhws\Desktop\Classes\512TA\HW2"
import delimited C:\Users\qjhws\Desktop\Classes\512TA\HW2\time_var.txt,clear

preserve
import delimited C:\Users\qjhws\Desktop\Classes\512TA\HW2\time_invar.txt,clear
save "C:\Users\qjhws\Desktop\Classes\512TA\HW2\invar.dta",replace
restore 
merge m:1 personid using invar.dta, nogen


* Model 1
reg logwage education experience timetrend
est store m1

* Model 2
reg logwage education experience timetrend ability mothereducation ///
     fathereducation brokenhome numbersiblings
est store m2

* Model 3
xtset personid
xtreg logwage education experience timetrend,fe
xtreg logwage education experience timetrend ability mothereducation ///
     fathereducation brokenhome numbersiblings,fe
est store m3

* Model 4
xtreg logwage education experience timetrend ability mothereducation ///
     fathereducation brokenhome numbersiblings,re
est store m4

* Model 5

egen IV1 = mean(experience),by(personid)
gen IV2 = experience - IV1
ivregress 2sls logwage brokenhome numbersiblings timetrend  mothereducation fathereducation (education ability = IV1 IV2)
predict res, residual

*number of panel
egen tag_id = tag(personid)

count if personid != 0  // total observation
scalar total_obs = r(N)
count if tag_id == 1   // number of panel
scalar num_ind = r(N)


* we calculate the variance using Baltagi and Chang(2000)
gen res_2 = res^2
sum res_2  // we will use r(sum)


scalar sigma_v = r(sum)/(total_obs-num_ind)
scalar sigma_vSq = sigma_v^2

egen groupMean_res = mean(res), by(personid)
gen groupMean_resSqr = groupMean_res^2
gen sigma_v2 = sigma_v^2


sum groupMean_resSqr  

scalar sigma_u = (r(sum)-num_ind*(sigma_v2))/total_obs
scalar sigma_uSq = sigma_u^2	 

* re-weight all variables	 
egen num_period = count(personid),by(personid)
gen w_i = num_period* sigma_uSq + sigma_vSq
gen theta = 1-1/sqrt(sigma_vSq/w_i)


global varList "logwage brokenhome numbersiblings timetrend  mothereducation fathereducation education ability IV1 IV2"
foreach var	of global varList{
egen `var'_mean = mean(`var'),by(personid)
gen demean_`var' = `var' - theta*`var'_mean
}
**********************************************************************************
cap drop *_mean


ivregress 2sls demean_logwage demean_brokenhome demean_numbersiblings demean_timetrend ///
          demean_mothereducation demean_fathereducation (demean_education demean_ability = demean_IV1 demean_IV2)
est store m5


* Model 6 
mixed logwage experience timetrend ability mothereducation fathereducation brokenhome numbersiblings || personid : education 

est store m6

esttab m* using result.csv, replace ///
compress nogap b(%6.3f) se pr2 ///
star(* 0.1  ** 0.05  *** 0.01)