*cap log cl
*log using "C:\Users\royj\Dropbox\eco5720\emlr3.log", replace

************************************************
*** Example: SLR Simulation - 500 reps; n=10 ***
************************************************

clear

* Generating a variable with missing values to store estimated values of beta hat from the simulation *
set obs 500
g data_bx=.

* Simulating data and storing regression estimates of beta hat *
forval i=1/500 {

	preserve
	clear
	set obs 10
	g x = rnormal()
	g u = rnormal()
	g y = 1 + x + u
	reg y x
	local xcoef =_b[x]
	restore

	replace data_bx=`xcoef' in `i'

}

* Summary and histogram of beta hat values *
su data_bx
hist data_bx

**************************************************
*** Example: SLR Simulation - 500 reps; n=1000 ***
**************************************************

clear

* Generating a variable with missing values to store estimated values of beta hat from the simulation *
set obs 500
g data_bx=.

* Simulating data and storing regression estimates of beta hat *
forval i=1/500 {

	preserve
	clear
	set obs 1000
	g x = rnormal()
	g u = rnormal()
	g y = 1 + x + u
	reg y x
	local xcoef =_b[x]
	restore

	replace data_bx=`xcoef' in `i'

}

* Summary and histogram of beta hat values *
su data_bx
hist data_bx

*********************************************************************************
*** Example: SLR Simulation - 500 reps; n=10 ; SSR/n biased for sigma-squared ***
*********************************************************************************

clear

* Generating a variable with missing values to store estimated values of beta hat from the simulation *
set obs 500
g data_sig=.

* Simulating data and storing regression estimates of SSR/n *
forval i=1/500 {

	preserve
	clear
	set obs 10
	g x = rnormal()
	g u = rnormal()
	g y = 1 + x + u
	reg y x
	predict uhat, resid
	su uhat, d
	loc mvar = `r(Var)'*(`r(N)'-1)/`r(N)'
	restore

	replace data_sig=`mvar' in `i'

}

* Summary and histogram of SSR/n values *
su data_sig
hist data_sig

***************************************************************************************
*** Example: SLR Simulation - 500 reps; n=1000 ; SSR/n consistent for sigma-squared ***
***************************************************************************************

clear

* Generating a variable with missing values to store estimated values of beta hat from the simulation *
set obs 500
g data_sig=.

* Simulating data and storing regression estimates of beta hat *
forval i=1/500 {

	preserve
	clear
	set obs 1000
	g x = rnormal()
	g u = rnormal()
	g y = 1 + x + u
	reg y x
	predict uhat, resid
	su uhat, d
	loc mvar = `r(Var)'*(`r(N)'-1)/`r(N)'
	restore

	replace data_sig=`mvar' in `i'

}

* Summary and histogram of SSR/n values *
su data_sig
hist data_sig

************************************************
*** Example: MLR Simulation - 500 reps; n=10 ***
************************************************

clear

* Generating a variable with missing values to store estimated values of beta hat from the simulation *
set obs 500
g data_bx=.

* Simulating data and storing regression estimates of beta hat *
forval i=1/500 {

	preserve
	clear
	set obs 10
	g x = rchi2(1)
	g u = rchi2(1) - 1
	g y = 1 + x + u
	reg y x
	local xcoef =_b[x]
	restore

	replace data_bx=`xcoef' in `i'

}

* Summary and histogram of beta hat values *
su data_bx
hist data_bx

**************************************************
*** Example: MLR Simulation - 500 reps; n=1000 ***
**************************************************

clear

* Generating a variable with missing values to store estimated values of beta hat from the simulation *
set obs 500
g data_bx=.

* Simulating data and storing regression estimates of beta hat *
forval i=1/500 {

	preserve
	clear
	set obs 1000
	g x = rchi2(1)
	g u = rchi2(1) - 1
	g y = 1 + x + u
	reg y x
	local xcoef =_b[x]
	restore

	replace data_bx=`xcoef' in `i'

}

* Summary and histogram of beta hat values *
su data_bx
hist data_bx

*log cl