Ramsey: The solution to the static first order conditions for optimal policy could not be found

Hi, I am quite new to Dynare and has a project to work. I had problem of solving a Ramsey optimal policy but I came across the warning message :
Ramsey: The solution to the static first order conditions for optimal policy could not be found. Either the model doesn’t have a steady state, there are an infinity of steady states, or the guess values are too far from the solution
My code is attached below, thank you in advance for any help! :grinning:
Baseline_Ramsey0719.mod (5.4 KB)
Plus: The steady state of tax effort is derived by the laffer curve simulation.
Laffer_curve0718.m (1.1 KB)

Is there a reason for not providing analytical steady state values conditional on the instrument? You seem to have those values.

Dear professor jpfeifer,
Thank you so much for the help, according to your suggestion, I complete the steady state values of the steady state values. Unfortunately, the waring message still pop up.“Ramsey: The solution to the static first order conditions for optimal policy could not be found. Either the model doesn’t have a steady state, there are an infinity
of steady states, or the guess values are too far from the solution”
the revised code is atteched below, in all probability, I misread your advice and had a wrong improvement. Once again thank you for the support!
Baseline_Ramsey0719.mod (5.6 KB)

I was saying you should use a steady_state_model-block. Something along the lines of

Baseline_Ramsey0719.mod (6.0 KB)

You can see there is a problem with the NKPC.

Dear professor jpfeifer,
Sorry to disturb you again. I tried to add a steady_state_model-bolck, and made some modification on NKPC, however, the error message altered to “Ramsey: The steady state file does not solve the static first order conditions conditional on the instruments.” and still can not derive the result. Thank you inadvance for the valuable support!
Baseline_Ramsey0722.mod (6.4 KB)

Please first make sure the model works with a Taylor rule.