Hello jpfeifer ,

I have performed the identification analysis of my DSGE model and the results are as follows:

==== Identification analysis ====

Testing prior mean

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

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

Monte Carlo Testing

Testing MC sample

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

WARNING !!!

The rank of J (moments) is deficient for 2 out of 677 MC runs!

**However what concerns me are the following messages which appeared prior to this which report:**

SOLVE: maxit has been reached

SOLVE: maxit has been reached

33.1% of the prior support gives unique saddle-path solution.

30.7% of the prior support gives explosive dynamics.

For 36.279% of the prior support dynare could not find a solution.

```
For 36.279\% Cannot find the steady state.
```

Smirnov statistics in driving acceptable behaviour

H d-stat = 0.327 p-value = 0.000

GAMMA_K d-stat = 0.490 p-value = 0.000

GAMMA_L d-stat = 0.121 p-value = 0.000

EPSI_K d-stat = 0.183 p-value = 0.000

Smirnov statistics in driving instability

H d-stat = 0.287 p-value = 0.000

GAMMA_G d-stat = 0.133 p-value = 0.000

GAMMA_L d-stat = 0.136 p-value = 0.000

GAMMA_Z d-stat = 0.240 p-value = 0.000

Smirnov statistics in driving no solution

GAMMA_G d-stat = 0.100 p-value = 0.000

GAMMA_K d-stat = 0.249 p-value = 0.000

GAMMA_Z d-stat = 0.198 p-value = 0.000

EPSI_K d-stat = 0.153 p-value = 0.000

Starting bivariate analysis:

Correlation analysis for prior_stable

[GAMMA,H]: corrcoef = -0.179

[H,GAMMA_G]: corrcoef = -0.195

[H,GAMMA_K]: corrcoef = -0.213

[H,GAMMA_Z]: corrcoef = -0.279

[RHO_A,EPSI_L]: corrcoef = 0.233

[RHO_TK,RHO_TL]: corrcoef = 0.119

[GAMMA_K,EPSI_K]: corrcoef = 0.286

[GAMMA_L,GAMMA_Z]: corrcoef = -0.133

[EPSI_L,PHI_KL]: corrcoef = 0.140

[EPSI_Z,PHI_LC]: corrcoef = 0.147

Correlation analysis for prior_unacceptable

[H,GAMMA_K]: corrcoef = -0.195

[H,GAMMA_Z]: corrcoef = 0.099

[H,EPSI_K]: corrcoef = 0.112

[RHO_A,EPSI_L]: corrcoef = -0.115

Correlation analysis for prior_unstable

[KAPPA,H]: corrcoef = -0.160

[H,GAMMA_G]: corrcoef = -0.156

[H,GAMMA_K]: corrcoef = -0.154

[H,GAMMA_L]: corrcoef = -0.239

[H,GAMMA_Z]: corrcoef = -0.241

[RHO_TK,RHO_TL]: corrcoef = -0.140

[GAMMA_K,EPSI_K]: corrcoef = 0.173

[EPSI_L,PHI_KL]: corrcoef = -0.182

[EPSI_Z,PHI_LC]: corrcoef = -0.186

Correlation analysis for prior_wrong

[GAMMA,H]: corrcoef = 0.127

[H,GAMMA_K]: corrcoef = -0.119

[H,EPSI_K]: corrcoef = 0.133

[RHO_A,EPSI_L]: corrcoef = -0.194

[GAMMA_G,GAMMA_Z]: corrcoef = -0.143

[GAMMA_K,GAMMA_Z]: corrcoef = 0.134

[GAMMA_Z,EPSI_K]: corrcoef = -0.177

Computing theoretical moments …

… done !

==== Identification analysis ====

Testing prior mean

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

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

Monte Carlo Testing

Testing MC sample

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

WARNING !!!

The rank of J (moments) is deficient for 2 out of 677 MC runs!

Am I to take away that my parameters are identified or are there identification problems that I need to fix prior to my estimation?

Many Thanks,