Hi Iris team,
I’m trying to estimate a basic new keynesian model but I’m having some problems. If I have a new Keynesian model with 3 equations, I have 3 forward looking variables and 3 unstable roots, to solve the model. But, when I introduce the measurement variables that
is also a forward looking variable, this forward variable changes its nature and become backward looking. Then, when I try to estimate the model’s parameters the rank condition is not satisfied and I get the attached error message. When I estimate this using
Dynare I have no problem. Can you explain me how to deal with this?
Is there any option I can use to attach the codes?
Thanks in advance for your kind attention.
Camila Londoño
??? Error using ==> getstack at 12
IRIS Toolbox Error :: model.
*** The model failed to updated new parameters.
Type x = model.failed(); to get the model object that failed to solve.
IRIS Toolbox Error :: model.
*** Solution not available. NaN in derivatives of this equation in #1: 'x=(x{1})-(1/sigma)*(i-(pi{1}))+dem;'.
Error in ==> error at 37
stack = utils.getstack();
Error in ==> model.failed at 55
utils.error('model',[...
Error in ==> model.myupdatemodel at 130
model.failed(This,sstateOk,chkSstateOk,sstateErrList, ...
Error in ==> model.objfunc at 31
[This,UpdateOk] = myupdatemodel(This,X,Pri,EstOpt,throwErr);
Error in ==> nlconst at 805
f = feval(funfcn{3},x,varargin{:});
Error in ==> fmincon at 758
[X,FVAL,LAMBDA,EXITFLAG,OUTPUT,GRAD,HESSIAN]=...
Error in ==> estimateobj.myestimate at 45
[PStar,ObjStar,~,~,LAMBDA,grad,Hess{1}] = ...
Error in ==> model.estimate at 395
[This,pStar,objStar,PCov,Hess] = myestimate(This,Data,pri,estOpt,likOpt);
Error in ==> estimate_3eq at 119
[est,pos,C,H,mest,v,~,~,delta,Pdelta] = ...