I got a error message. How can I fix this?

I built a simple DSGE model while looking at the references.
During the estimation process, an error message appeared as follows.
How do I resolve the error message below?
Attach the mod file and data.bdg_data.xlsx (8.7 KB) SDSGE_code.mod (3.8 KB)

  • below error message in dynare -
    Error in computing likelihood for initial parameter values

ESTIMATION_CHECKS: There was an error in computing the likelihood for initial parameter values.
ESTIMATION_CHECKS: If this is not a problem with the setting of options (check the error message below),
ESTIMATION_CHECKS: you should try using the calibrated version of the model as starting values. To do
ESTIMATION_CHECKS: this, add an empty estimated_params_init-block with use_calibration option immediately before the estimation
ESTIMATION_CHECKS: command (and after the estimated_params-block so that it does not get overwritten):

print_info (line 32)
One of the eigenvalues is close to 0/0 (the absolute value of numerator and denominator is smaller than 0.0000!
If you believe that the model has a unique solution you can try to reduce the value of qz_zero_threshold.

print_info (line 32)

initial_estimation_checks (line 185)
print_info(info, DynareOptions.noprint, DynareOptions)

dynare_estimation_1 (line 164)
oo_ = initial_estimation_checks(objective_function,xparam1,dataset_,dataset_info,M_,estim_params_,options_,bayestopt_,bounds,oo_);

dynare_estimation (line 105)

SDSGE_code.driver (line 285)

dynare (line 293)
evalin(‘base’,[fname ‘.driver’]) ;

Are you sure the linearization is correct?

%4. Law of motion of capital
  k = (1-delta)*k(-1)+delta*i;

looks like a level equation.

Log-linearization was performed using the Uhlig method. The steady state of investment and capital was calculated as I_ss = delta*K_ss. So, the log-linearization of the law of motion of capital came out as above. Are there any mistakes?

Sorry, I missed that. You are right.


I tried the three things that the professor posted in the comments.

  1. stock_simul
  2. Using diffuse_filter
  3. The average of the data should be 0.

First of all, Number 1 was successful. Number 2 was occurred error. Number 3 is not 0. In the current model, the data is logarithmic. After removing the trend of raw data using HP filter, shall we try again with log difference?

Sorry, I am not following. The singularity reported above has nothing to do with the observation equations.

Thanks for the reply.