
Hi,
I'm struggling with the behavior of the forecast command after estimating a VAR.
In particular, the forecasts crucially depend on whether I estimate the VAR with or without constants,
even though all the VAR variables have zero mean.
The estimated constants (if included) of course slightly differ from zero, but this does not explain the difference in forecasts.
Is there any reason why the longterm forecasts of a VAR model should not converge to their unconditional mean, i.e. their estimated constant?
Please find below an example code replicating my issue.
PS: When I add the option 'deviation',true the forecasts of the VAR with constant are, as one would expect, identical to those of the VAR model without a constant.
x=randn(100,4);
x=xrepmat(mean(x,1),100,1); % subtract mean from sample
startHist = mm(2000,1); endHist = startHist+99; histRange = startHist : endHist;
varnames = {'var1','var2','var3','var4'}; M = array2db(x,histRange,varnames);
v1 = VAR(varnames);
[v1,vd1] = estimate(v1,M,Inf, ...
'order=',1,'const=',false);
fcast1= forecast(v1,M,endHist+1:endHist+48,'meanOnly=',true);
v2 = VAR(varnames);
[v2,vd2] = estimate(v2,M,Inf, ...
'order=',1,'const=',true);
fcast2 = forecast(v2,M,endHist+1:endHist+48,'meanOnly=',true);
v2const=get(v2,'K');
plot([fcast1.var1(:) fcast2.var1(:)]);
hold on;
plot([0 48],[0 0],'Color','black')
hold on;
plot([0 48],[v2const(1) v2const(1)],'Color','red')
legend('forecast 1','forecast 2','zero','uncond. mean')
% these forecasts differ substantially, i.e. while the first forecast (w/o constant) converges to zero, the second forecast (w/ constant) does not converge to its unconditional mean
v3 = VAR(varnames);
[v3,vd3] = estimate(v3,M,Inf, ...
'order=',1,'const=',true);
fcast3 = forecast(v3,M,endHist+1:endHist+48,'meanOnly=',true,'deviation',true);
plot([fcast1.var1 fcast3.var1])
% these forecasts yield identical results


Coordinator
Jul 1, 2015 at 1:21 PM

Hi Mark
You've made a mistake at this line:
v2const=get(v2,'K');
This command retrieves the estimated constant terms, not the unconditional mean of the VAR process. These two obviously differ from each other (unless the transition matrix is all zeros).
If you replace that command line with the following one
v2mean=mean(v2);
and change the v2const to v2mean in the plotting commands, you'll get the results you expect.
Best,
Jaromir



Hi Jaromir,
Thank you so much for the quick response, now I got it.
Kind regards,
Mark

