Dear Colleagues:

After running the identification procedure on the linearized code of my DSGE model, I have de following results:

==== Identification analysis ====

Testing prior mean

Evaluating simulated moment uncertainty … please wait

Doing 8289 replicas of length 300 periods.

Simulated moment uncertainty … done!

All parameters are identified in the model (rank of H).

All parameters are identified by J moments (rank of J)

==== Identification analysis completed ====

59.6% of the prior support gives unique saddle-path solution.

40.4% of the prior support gives explosive dynamics.

Smirnov statistics in driving acceptable behaviour

phi_y d-stat = 0.927 p-value = 0.000

Smirnov statistics in driving instability

phi_y d-stat = 0.553 p-value = 0.000

Starting bivariate analysis:

Correlation analysis for prior_stable

[Omega_H,rho_zRP]: corrcoef = -0.233

[Omega_NT,phi_inf]: corrcoef = -0.186

[w_T,rho_muM]: corrcoef = -0.118

Correlation analysis for prior_unacceptable

[Omega_H,rho_zRP]: corrcoef = 0.334

[Omega_NT,phi_inf]: corrcoef = 0.269

[Omega_NT,phi_y]: corrcoef = -0.192

[w_T,rho_muM]: corrcoef = 0.169

[phi_inf,phi_y]: corrcoef = 0.193

Correlation analysis for prior_unstable

[Omega_H,rho_zRP]: corrcoef = 0.334

[Omega_NT,phi_inf]: corrcoef = 0.269

[Omega_NT,phi_y]: corrcoef = -0.192

[w_T,rho_muM]: corrcoef = 0.169

[phi_inf,phi_y]: corrcoef = 0.193

Computing theoretical moments …

Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND = 1.953907e-16.

In lyapunov_symm at 145

In th_autocovariances at 114

In th_moments at 38

In mc_moments at 36

In map_ident_ at 58

In dynare_sensitivity at 239

In mmt at 2290

In dynare at 180

My concern lies in the computation of theoretical moments because eventhough my model’s parameters are identified, but it is unable to compute the theoretical moments. How can I solve this problem?

Thank you,

Jesus