Johansen cointegration test
Posted: Wed Mar 31, 2010 4:02 am
Dear all,
I've searched the forum and I haven't been able to find the answer as to how I can estimate (and automate) a VECM once I have found cointegration through the Johansen procedure. I'm currently using Eviews 6 and the code I have so far is:
group importprices
importprices.drop resid
importprices.drop time
importprices.drop series01
table cointegration
for !i=1 to importprices.@count
%name = importprices.@seriesname(!i)
group g1
g1.add {%name} logforeignproxy loggdp logneu
g1.coint(s,4)
freeze(table2) g1.coint(s,4)
cointegration(1,1)="name"
cointegration(1,!i+1)=%name
cointegration(2,1)="trace intercept no trend"
cointegration(2,!i+1)=table2(12,4)
cointegration(3,1)="max-eig intercept no trend"
cointegration(3,!i+1)=table2(13,4)
d g1
d table2
next
So I get the output for both the Trace-statistic and maximum eigenvalue. In half the cases the Johansen procedure shows no cointegration and for less than 10% is the cointegrating rank greater or equal to 2.
Suppose the cointegrating rank is one. Is the Engle-Granger framework a valid approach in this case, assuming weak exogeneity of the regressors? I know this isn't ideal, but I have over 300 regressions and I don't know how to programme a VECM, whereas the Engle-Granger framework is quite straightforward. Any help is much appreciated.
Many thanks,
Seb
I've searched the forum and I haven't been able to find the answer as to how I can estimate (and automate) a VECM once I have found cointegration through the Johansen procedure. I'm currently using Eviews 6 and the code I have so far is:
group importprices
importprices.drop resid
importprices.drop time
importprices.drop series01
table cointegration
for !i=1 to importprices.@count
%name = importprices.@seriesname(!i)
group g1
g1.add {%name} logforeignproxy loggdp logneu
g1.coint(s,4)
freeze(table2) g1.coint(s,4)
cointegration(1,1)="name"
cointegration(1,!i+1)=%name
cointegration(2,1)="trace intercept no trend"
cointegration(2,!i+1)=table2(12,4)
cointegration(3,1)="max-eig intercept no trend"
cointegration(3,!i+1)=table2(13,4)
d g1
d table2
next
So I get the output for both the Trace-statistic and maximum eigenvalue. In half the cases the Johansen procedure shows no cointegration and for less than 10% is the cointegrating rank greater or equal to 2.
Suppose the cointegrating rank is one. Is the Engle-Granger framework a valid approach in this case, assuming weak exogeneity of the regressors? I know this isn't ideal, but I have over 300 regressions and I don't know how to programme a VECM, whereas the Engle-Granger framework is quite straightforward. Any help is much appreciated.
Many thanks,
Seb