Eigenvalues problem!

Hi everyone!
I have the following issue when running my Dynare code:

There are 18 eigenvalue(s) larger than 1 in modulus
for 21 forward-looking variable(s)

The rank condition ISN’T verified!

Error using print_info (line 32)
Blanchard & Kahn conditions are not satisfied:
Error in stoch_simul (line 107)
print_info(info, options_.noprint, options_);
Error in tesis_simple.driver (line 831)
[info, oo_, options_, M_] = stoch_simul(M_,
options_, oo_, var_list_);
Error in dynare (line 293)
evalin(‘base’,[fname ‘.driver’]) ;

Afterwards, I ran the model_diagnostics command and obtained the following:

MODEL_DIAGNOSTICS: No obvious problems with this mod-file were detected.

I’ve checked the timing of the model several times and found nothing wrong, at least in my opinion.

The code is attached below.

Thanks in advance for any help!

tesis_simple.mod (8.6 KB)

Hi, some of the residuals of the the static equations are non zero. Start by checking your steady-state computations.

How can c_E be negative in steady state? More generally, try to simplify the model.

Thanks for the reply!

I tried to simplify the model, but the error is the same. Even though now c_E (which I renamed c_R) is positive, I still have the eigenvalues issue.

I attach the new file below

tesis_simple2.mod (6.6 KB)

Are you sure steady states like

Delta      		 258335
Theta      		 258325

are correct?

Theta and Delta are auxiliary variables which arise from the problem of a firm which faces Calvo pricing decisions. That is : Theta/Delta = pt^*/P_t.
I’m not really sure if the SS values of these variables are relevant for the question I’m trying to answer (commodity shocks impact in labour market outcomes). Nevertheless, I’ve been trying with alternative parameterizations in order to have Theta and Delta to be lower, and it is possible, in fact in my last attempt I had Theta and Delta with values near 22, but despite of the latter I have the same issue and Dynare cannot give me an output

I see. I was worried about the differences in magnitude maybe inducing numerical issues. It sounds as if the only way out is to further simplify your model to see what causes the problem.