wfcreate(wf=base, page=base) a 1999 2010 15
import E:\post\indicators.csv ftype=ascii rectype=crlf skip=0 fieldtype=delimited delim=comma colhead=1 eoltype=pad badfield=NA @freq A @id code @date(year) @smpl @all
importmat(name=combinations) E:\post\matriz.csv ftype=ascii rectype=crlf skip=0 fieldtype=delimited delim=comma colhead=0 eoltype=pad badfield=NA

'we create a matrix to store the coefficient and their t-statistics for the case of two units removal:
matrix(2,105) t_stats_and_coef_2


'We estimate without the removal of any unit
equation fmols_eq.cointreg(panmethod=grouped) salary inv

for !j =1 to 105
smpl 1999 2010 if @crossid<>combinations(!j,1) and @crossid<>combinations(!j,2)
equation recursive_na.cointreg(panmethod=grouped) salary inv
t_stats_and_coef_2(1,!j) = @tstat(1)
t_stats_and_coef_2(2,!j) = @coefs(1)
next
'In the first row of the matrix t_stats_and_coef_2 we store the t-statistics of the coefficient estimates when we remove two units
'In the second row of the matrix t_stats_and_coef_2 we store the coefficient estimates when we remove two units

t_stats_and_coef_2.sheet
'here we save the matrix for the removal of two units. Then you use this excel file to plot the coefficient estimates and their respective t-statistics.
t_stats_and_coef_2.write(t=xls, a1, t) e:\post\t_stats_and_coef_2.xls
close t_stats_and_coef_2

'we create a matrix to store the coefficient and their t-statistics for the case of only one unit removal:
matrix(2,15) t_stats_and_coef_1
for !j =1 to 15
smpl 1999 2010 if @crossid<>!j
equation recursive_na1.cointreg(panmethod=grouped) salary inv
t_stats_and_coef_1(1,!j) = @tstat(1)
t_stats_and_coef_1(2,!j) = @coefs(1)
next

'In the first row of the matrix t_stats_and_coef_1 we store the t-statistics of the coefficient estimates when we remove one unit
'In the second row of the matrix t_stats_and_coef_1 we store the coefficient estimates when we remove one unit
t_stats_and_coef_1.sheet
'here we save the matrix for the removal of one unit. Then you use this excel file to plot the coefficient estimates and their respective t-statistics.
t_stats_and_coef_1.write(t=xls, a1, t) e:\post\t_stats_and_coef_1.xls
close t_stats_and_coef_1

wfsave(2) E:\post\base.wf1