For a MonteCarlo study, we would like to have some simulated data that follows the process that the command xtregar, fe identifies:
\[Y = X\beta + c_i + \epsilon_{i,t}\] with the ci individual fixed-effects
and with \[\epsilon_{i,t+1} = \rho \epsilon_{i,t} + \eta_{i,t}\] (where ηi,t are i.i.d. and follow a normal law.)
This should be simple but when we generate the data with some given parameters, and we analyse the simulated data, we do not get these parameters back with xtregar, fe ! (more exactly, results are significantly different from the initial parameters) What could go wrong ?
Here are the built data and code. Thanks in advance for any hint!
Additional note: the line
comes from the stationnarity of εi,t.
The reference for xtregar, fe can be found here: https://www.stata.com/manuals13/xtxtregar.pdf
\[Y = X\beta + c_i + \epsilon_{i,t}\] with the ci individual fixed-effects
and with \[\epsilon_{i,t+1} = \rho \epsilon_{i,t} + \eta_{i,t}\] (where ηi,t are i.i.d. and follow a normal law.)
This should be simple but when we generate the data with some given parameters, and we analyse the simulated data, we do not get these parameters back with xtregar, fe ! (more exactly, results are significantly different from the initial parameters) What could go wrong ?
Here are the built data and code. Thanks in advance for any hint!
Code:
clear all *to get easily a panel structure : nr year set obs 100 gen nr=_n expand 19 gen year = 2000 sort nr bysort nr: replace year=year[_n-1]+1 if _n!=1 sort nr year xtset nr year save initial0.dta, replace *We consider some arsbitrary parameters: use initial0.dta, clear scalar the_rho = 0.3 scalar the_sigma_epsilon = 2 scalar the_sigma_eta = the_sigma_epsilon * sqrt(1-the_rho*the_rho) scalar the_sigma_c_i = 0.9 matrix the_m = (0,0,0) matrix the_sd = (the_sigma_eta,the_sigma_epsilon,the_sigma_c_i) * We try to simulate 100 times the corresponding process set seed 89 gen rho_emp = 0 gen sigma_e_emp = 0 gen sigma_std_ci = 0 forvalues i = 1/100 { drawnorm eta epsilon0 c_i, means(the_m) sds(the_sd) bysort nr: gen epsilon= epsilon0 if _n==1 bysort nr: replace epsilon=eta + the_rho * epsilon[_n-1] if _n>1 bysort nr: replace c_i = c_i[1] gen y = 5 + c_i + epsilon xtregar y, fe replace rho_emp = e(rho_ar) if _n==`i' replace sigma_e_emp = e(sigma_e) if _n==`i' replace sigma_std_ci = e(sigma_u) if _n==`i' drop epsilon epsilon epsilon0 y eta c_i } //comparing the results keep if _n<=100 keep rho_emp sigma_e_emp sigma_std_ci gen constant=1 reg rho_emp constant test (_cons=0.3) reg sigma_e_emp constant test (_cons=2) reg sigma_std_ci constant test (_cons=0.9)
Code:
scalar the_sigma_eta = the_sigma_epsilon * sqrt(1-the_rho*the_rho)
The reference for xtregar, fe can be found here: https://www.stata.com/manuals13/xtxtregar.pdf