I have checked my file with a fully calibration version and it works, I also use command " identification", it says “All parameters are identified”.
but when I begin to estimate the model, I get:

POSTERIOR KERNEL OPTIMIZATION PROBLEM!
(minus) the hessian matrix at the “mode” is not positive definite!
=> posterior variance of the estimated parameters are not positive.
You should try to change the initial values of the parameters using
the estimated_params_init block, or use another optimization routine.
Warning: The results below are most likely wrong!

i.e. used an identity matrix instead of the Hessian. The resulting posterior shows a lot of persistence related to net exports. I am not sure your model is able to capture its dynamics.

net export NX appears in my model twice: GDP=C+I+G+NX, and an AR(1) SHOCK PROCESS：ln(NX)=pho_nx*NX(-1)+e_nx;
will it have a big impact on model behavior, and after I change the data source of NX, whics seems to be less persistent, it still does not work.