Dynare forums

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

Anyone have a clue?

Have you tried Dynare 4.2.5? In some earlier versions, output was suppressed if the Hessian was not positive definite.

This solved the problem. Thanks