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MS-VAR with time varying probabilities
Posted: Tue Mar 06, 2012 5:19 am
by Aktar
Hi Tom,
I would like to identify common business cycle of a set of countries (as in krozlig 2001), and test the predictive power of leading indicators in the identification of this common cycle. The best approach may be a MS-VAR-TVTP model. Do the programm of filardo 1994 enjoy this feature? Because it use the MSVAR setup procedure.
Regards
Re: MS-VAR with time varying probabilities
Posted: Wed Mar 07, 2012 12:15 pm
by TomDoan
Filardo's paper was univariate, though the extension to a VAR is fairly straightforward. It could take a very long time to estimate though. Since I have no idea what paper Krolzig(2001) is (PLEASE take the time to give a real reference) I have no idea whether that would help.
Re: MS-VAR with time varying probabilities
Posted: Thu Mar 08, 2012 7:46 am
by Aktar
The paper is : "International Business Cycles: Regime Shifts in the Stochastic Process of Economic Growth"
and the standard code for ms-var seems to be:
Code: Select all
nonlin(parmset=varparms) mu phi sigmav
nonlin(parmset=msparms) theta
gset pt_t gstart gend = %zeros(nexpand,1)
gset pt_t1 gstart gend = %zeros(nexpand,1)
frml msvarf = log(%MSVARProb(t))
@msvarinitial gstart gend
@msvarsetup(lags=1,states=3,switch=mh)
# dusa djap dfrg duk dcan daus
@msvarinitial gstart gend
@msvarEMgeneralsetup
do emits=1,50
@msvaremstep gstart gend
disp "Iteration" emits "Log Likelihood" %logl
end do emits
set p1 gstart gend = (pstar=%msvarmarginal(emptsm(t),0)),pstar(1)
set p2 gstart gend = (pstar=%msvarmarginal(emptsm(t),0)),pstar(2)
set p3 gstart gend = (pstar=%msvarmarginal(emptsm(t),0)),pstar(3)
maximize(trace,parmset=varparms+msparms,start=%(p=%mslogisticp(theta),pstar=%MSVARInit()),$
reject=%minvalue(MSVARTransProbs)<0.0,method=bfgs,iters=400) msvarf gstart gend
Re: MS-VAR with time varying probabilities
Posted: Sun Mar 11, 2012 7:43 pm
by TomDoan
You could certainly try to combine the two ideas. However, it's very likely that you'll get a model with quite a few modes and it's possible that none will be easy to interpret.