ERROR! The steadystate values returned

[ajk77]

Hello?
First of all, Please find attached files.
I'm using the steadystate.m file. but I'm not sure I'm doing properly.
All steady-state values are calculated by hand. I checked it by making another m file. To my knowledge, that's no problem.
But, I couldn't find where I got stuck.
Please have look my codes. I would greatly appreciate it.

The error is as follows;
Residual for equation number 1 is equal to 0.14353
Residual for equation number 2 is equal to -25.236
Residual for equation number 3 is equal to -0.006006
...
...
...
Residual for equation number 41 is equal to 0.056

??? Error using ==> steady_ at 89
The steadystate values returned by smallopen_steadystate.m don't solve the static model!
Error in ==> steady at 52
steady_;
Error in ==> smallopen at 543
steady;
Error in ==> dynare at 132
evalin('base',fname) ;

[ajk77]

Plz find the reduced mod file. As the sm.mod file looks a bit lagre.
It contains 16 equations, CES production function. Calvo equation.
The errors are as follows. just one residual does not converge.

esidual for equation number 1 is equal to 0
...
Residual for equation number 9 is equal to -0.50058
...
Residual for equation number 16 is equal to 0

??? Error using ==> steady_ at 132
STEADY: convergence problems
Error in ==> steady at 52
steady_;
Error in ==> ce at 276
steady;
Error in ==> dynare at 132
evalin('base',fname) ;

[AssiaEzzeroug]

Hi,

Your model is not linear since you have powers in some of your equations (e.g the ones defining y_d, mc_d). Besides you may need to specify initial values for certain variables. As far as I understood, that's what you tried to do below the block parameters through the equations y_d_ss,..right? Then you have to use this information directly into the block initval (y_d=y_d_ss,..). Note that the guess value for each variable is set to 0 by default when you don't specify one inside 'initval'.

Hope this helps

[ajk77]

Fortunately, I found my error.
In the NKPC equation, I put a mark-up variable as constant. It makes an error.
altenatively, the AR(1) process mark-up variable sort my error out.
anyway, thank you for your help.

I had a question.
my model is obviously linear. y_d_ss, mc_d_ss are constant as I employ the CES function.
If I put constant values which are larger than 1in the log-linearized equations, (ex: wage_ss/MC_ss or Y_ss/C_ss)
does it make problem?