An NK-DSGE model problemss

Hello, I’ve got a problem when solving an NK-DSGE model, and the error is presented below, and my mod file is
COVID.mod (5.4 KB)
I’m just stuck with this error for days, and cannot find a solution by myself, need help, thank you!!

There are 8 eigenvalue(s) larger than 1 in modulus
for 7 forward-looking variable(s)

The rank condition ISN’T verified!

Blanchard & Kahn conditions are not satisfied: no
stable equilibrium.

Have you tried whether a different parameterization works? It may have to do with your fiscal rules. Also B=0 is quite unusual. What happens if you omit this variable as it will drop out?

My parameters were calibrated by real economic data, in order to do a research on a simulation of the real economy. I have calculated the initial values by my self.

At the beginning, the residuals are quite big, so after several change of the initial values, and with the command(steady(maxit = 1000000,tolf = 3e-03,solve_algo = 1);)I can get the model working now.
Then I run the command(model_diagnostics), and it tells me the steady state cannot be computed, and I got the error stated above.

The B=0 is a try when I try to reduce the residuals of the former version (not this one).
And if I omit B=0, it works too.

Then the B=0 is most likely the problem.

I try to omit the B=0, change the model a little bit and still get the same error.

MODEL_DIAGNOSTICS: The steady state cannot be computed.
What should I check when it tells me the ss cannot be computed. Should I check the model equations? or other optional settings?

Thanks a lot for your reply!

You should put the model_diagnostics after your call to steady.

Sorry to bother you again
I’ve modified the model a little bit, and this is the new mod file:
COVID1.mod (4.6 KB)
But this time the error becomes:
Blanchard & Kahn conditions are not satisfied:
MODEL_DIAGNOSTICS: No obvious problems with this mod-file were detected.
What can I do to solve this problem?

Most often it’s a timing error, occasionally an issue with the parameters. These problems are usually hard to debug. The generic advice is: try to simplify the model to see where the problem comes from.

OK, thank you very much indeed!