I’m estimating a DSGE modell with maximum likelihood and everything seems to be working fine but I don’t obtain the “results from maximum likelihood” in the command window, what is wrong? I can see the results in the “modefilename”_mode.mat file, but is something wrong when it doesn’t appear in the command window?

What I do obtain in the command window is this:

Configuring Dynare …

[mex] Generalized QZ.

[mex] Sylvester equation solution.

[mex] Kronecker products.

[mex] Sparse kronecker products.

[mex] Bytecode evaluation.

[mex] k-order perturbation solver.

[mex] k-order solution simulation.

Starting Dynare (version 4.2.4).

Starting preprocessing of the model file …

Found 33 equation(s).

Evaluating expressions…done

Computing static model derivatives:

- order 1

Computing dynamic model derivatives: - order 1
- order 2

Processing outputs …done

Preprocessing completed.

Starting MATLAB/Octave computing.

STEADY-STATE RESULTS:

y 0

C 0

CH 0

CF 0

CH_f 0

C_f 0

r 0

rf 0

bf 0

z_y 0

z_u 0

z_r 0

z_b 0

pi 0

pih 0

pif 0

pif_f 0

ph 0

pf 0

pf_f 0

w 0

Q 0

N 0

S 0

vepsHhat 0

vepsFhat 0

G 0

dQSA_PCPIJAEI 0

dQSA_PCPIJAEIMP 0

logQUA_QI44 0

dQSA_YMN 0

QUA_RN3M 0

dAUA_WILMN_PCT_Qr 0

EIGENVALUES:

Modulus Real Imaginary

```
0 -0 0
2.665e-017 -2.665e-017 0
3.272e-017 -3.272e-017 0
7.733e-017 7.733e-017 0
2.603e-016 -2.603e-016 0
0.5 0.5 0
0.5 0.5 0
0.5 0.5 0
0.5 0.5 0
0.5 0.5 0
0.5 0.5 0
0.5 0.5 0
0.5 0.5 0
0.5 0.5 0
0.5 0.5 0
0.5308 0.5308 0.004166
0.5308 0.5308 -0.004166
0.6929 0.691 0.05055
0.6929 0.691 -0.05055
0.8093 0.8093 0
0.9956 0.9956 0
1.011 1.011 0
1.115 1.111 0.08865
1.115 1.111 -0.08865
1.234 1.234 0
Inf Inf 0
Inf Inf 0
Inf Inf 0
```

There are 7 eigenvalue(s) larger than 1 in modulus

for 7 forward-looking variable(s)

The rank condition is verified.

You did not declare endogenous variables after the estimation command.

This version of Dynare cannot estimate non linearized models!

Set “order” equal to 1.

Loading 86 observations from dataestMaster.mat

## Initial value of the log posterior (or likelihood): -131244.7525

## f at the beginning of new iteration, 131244.7524955067

Predicted improvement: 27844144.636007495

lambda = 1; f = 135381.2377843

lambda = 0.33333; f = 131567.7394517

lambda = 0.11111; f = 131251.1227987

lambda = 0.037037; f = 112270.5132989

lambda = 0.012346; f = 110250.1983141

lambda = 0.0041152; f = 110499.3208517

lambda = 0.0013717; f = 114608.5533166

lambda = 0.00045725; f = 124540.0040492

lambda = 0.00015242; f = 129972.6898258

lambda = 5.0805e-005; f = 131038.5122775

lambda = 1.6935e-005; f = 131212.9681548

lambda = 5.645e-006; f = 131237.5096398

lambda = 1.8817e-006; f = 131243.0246336

lambda = 6.2723e-007; f = 131244.1233473

lambda = 2.0908e-007; f = 131244.7373170

lambda = 6.9692e-008; f = 131244.7127804

lambda = 2.3231e-008; f = 131244.1696518

Norm of dx 74.625

Improvement on iteration 1 = 20994.554181403

## lambda = -6.2723e-007; f = 104908.3234125

lambda = -2.0908e-007; f = 104910.0841204

lambda = -6.9692e-008; f = 104909.3684936

lambda = -2.3231e-008; f = 104905.0974726

lambda = -7.7435e-009; f = 104913.1629732

lambda = -2.5812e-009; f = 104903.1424713

Norm of dx 3.6968

Improvement on iteration 12 = 0.000000000

improvement < crit termination

smallest step still improving too slow, reversed gradient

Objective function at mode: 104901.946025

Objective function at mode: 104901.946025

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!

In dynare_estimation_1 at 436

In dynare_estimation at 62

In master at 375

In dynare at 120

MODE CHECK

Fval obtained by the minimization routine: 104901.946025

Total computing time : 0h00m17s

master.mod (5.51 KB)