Starting preprocessing of the model file ...
Found 22 equation(s).
Evaluating expressions...done
Computing static model derivatives (order 1).
Computing dynamic model derivatives (order 2).
Processing outputs ...
done
Preprocessing completed.
Residuals of the static equations:
Equation number 1 : 0 : Euler equation
Equation number 2 : 0 : Labor FOC
Equation number 3 : 0 : Law of motion capital
Equation number 4 : 0 : resource constraint
Equation number 5 : 0 : production function
Equation number 6 : 0 : real wage/firm FOC labor
Equation number 7 : 0 : annualized real interst rate/firm FOC capital
Equation number 8 : 0 : exogenous TFP process
Equation number 9 : 0 : government spending process
Equation number 10 : 0 : capital tax process
Equation number 11 : 0 : labor tax process
Equation number 12 : 0 : Definition log output
Equation number 13 : 0 : Definition log capital
Equation number 14 : 0 : Definition log consumption
Equation number 15 : 0 : Definition log hours
Equation number 16 : 0 : Definition log wage
Equation number 17 : 0 : Definition log investment
Equation number 18 : 0 : Output growth
Equation number 19 : 0 : Consumption growth
Equation number 20 : 0 : Gov. consumption growth
Equation number 21 : 0 : Detrended labor taxes
Equation number 22 : 0 : Detrended capital taxes
STEADY-STATE RESULTS:
y 1.04578
c 0.571206
k 10.8761
l 0.33
z 0
ghat 0
r 0.126923
w 2.12325
invest 0.261445
log_y 0.0447641
log_k 2.38657
log_c -0.560006
log_l -1.10866
log_w 0.752949
log_invest -1.34153
tau_n 0.207
tau_k 0.387
c_obs 0
g_obs 0
y_obs 0
tau_n_obs 0
tau_k_obs 0
EIGENVALUES:
Modulus Real Imaginary
0 -0 0
2.127e-16 -2.127e-16 0
0.93 0.93 0
0.93 0.93 0
0.9694 0.9694 0
0.97 0.97 0
0.989 0.989 0
1.049 1.049 0
1.77e+16 -1.77e+16 0
7.273e+16 -7.273e+16 0
1.59e+17 -1.59e+17 0
There are 4 eigenvalue(s) larger than 1 in modulus
for 4 forward-looking variable(s)
The rank condition is verified.
You did not declare endogenous variables after the estimation/calib_smoother command.
Posterior moments will be computed for the 22 endogenous variables
of your model, this can take a long time ....
Choose one of the following options:
[1] Consider all the endogenous variables.
[2] Consider all the observed endogenous variables.
[3] Stop Dynare and change the mod file.
options [default is 1] = 3
PARAMETER INITIALIZATION: Some measurement errors of the calibrated model are 0 and violate the
PARAMETER INITIALIZATION: inverse gamma prior. They will instead be initialized with the prior mean.
Initial value of the log posterior (or likelihood): 2956.2452
Gradient norm 510045.4227
Minimum Hessian eigenvalue 23320.5827
Maximum Hessian eigenvalue 17629221232.2833
Iteration 1
Predicted improvement: 53.601607704
lambda = 1; f = -2956.2451401
lambda = 0.33333; f = -2982.5951270
lambda = 0.64439; f = -2967.4997138
lambda = 0.4339; f = -2984.5274353
Norm of dx 0.03697
Predicted improvement: 130073166592.242889404
lambda = 1; f = 32880122.5920346
lambda = 0.33333; f = 3649829.1357774
lambda = 0.11111; f = 402612.9845729
lambda = 0.037037; f = 42009.2676027
lambda = 0.012346; f = 2008.2138087
lambda = 0.0041152; f = -2414.3391008
lambda = 0.0013717; f = -2898.5359528
lambda = 0.00045725; f = -2950.1950803
lambda = 0.00015242; f = -2955.5813545
lambda = 5.0805e-05; f = -2956.1742115
lambda = 1.6935e-05; f = -2956.2382119
lambda = 5.645e-06; f = -2956.2446989
lambda = 1.8817e-06; f = -2956.2452116
lambda = 6.2723e-07; f = -2543.7843134
lambda = 2.0908e-07; f = -2893.5358737
lambda = 6.9692e-08; f = -3097.1972320
lambda = 2.3231e-08; f = -3263.4097161
lambda = 7.7435e-09; f = -3351.9938789
lambda = 2.5812e-09; f = -3287.9931063
Norm of dx 5.1005e+05
Gradient step!!
Predicted improvement: 14.869448378
lambda = 1; f = -3370.9891604
Norm of dx 0.00080144
Done for param eps_z = 0.0055
Predicted improvement: 0.265329731
lambda = 1; f = -3371.2671904
Norm of dx 0.00035726
Done for param eps_g = 0.0107
Predicted improvement: 1.969970289
lambda = 1; f = -3372.6243882
Norm of dx 0.0010306
Done for param eps_tk = 0.0078
Predicted improvement: 0.015594571
lambda = 1; f = -3372.6554393
lambda = 1.9332; f = -3372.6841658
lambda = 3.7372; f = -3372.7390112
lambda = 7.2247; f = -3372.8424382
lambda = 13.967; f = -3373.0324688
lambda = 27; f = -3373.3612947
lambda = 52.196; f = -3373.8414549
lambda = 100.9; f = -3374.0940130
Norm of dx 5.856e-06
Done for param eps_tn = 0.0056
Predicted improvement: 8.290856929
lambda = 1; f = -3385.0851968
Norm of dx 0.0012473
Done for param y_obs = 0.0108
Predicted improvement: 2.886625703
lambda = 1; f = -3390.5546829
lambda = 1.9332; f = -3395.0863800
lambda = 3.7372; f = -3402.0962702
lambda = 7.2247; f = -2956.2452101
lambda = 4.8647; f = -3405.0757215
lambda = 6.1676; f = -2956.2452171
lambda = 5.3491; f = -3405.9302410
Norm of dx 0.0018889
Done for param rhoz = 0.9953
Predicted improvement: 465157662519618.187500000
lambda = 1; f = 930315325037534368497664.0000000
lambda = 0.33333; f = 103368369448236741558272.0000000
lambda = 0.11111; f = 11485374383011349397504.0000000
lambda = 0.037037; f = 1276152709181462282240.0000000
lambda = 0.012346; f = 141794745450599694336.0000000
lambda = 0.0041152; f = 15754971712064256000.0000000
lambda = 0.0013717; f = 1750552410895233280.0000000
lambda = 0.00045725; f = 194505822914018304.0000000
lambda = 0.00015242; f = 21611757928627380.0000000
lambda = 5.0805e-05; f = 2401306378868999.0000000
lambda = 1.6935e-05; f = 266811800657529.9375000
lambda = 5.645e-06; f = 29645749221261.9726563
lambda = 1.8817e-06; f = 3293969998160.2353516
lambda = 6.2723e-07; f = 365995952199.0137329
lambda = 2.0908e-07; f = 40665977071.8688431
lambda = 6.9692e-08; f = 4518360199.1089678
lambda = 2.3231e-08; f = 502011038.1469810
lambda = 7.7435e-09; f = 55767591.5253527
lambda = 2.5812e-09; f = 6190843.4328507
lambda =
-6.2723e-07
lambda = -6.2723e-07; f = 365997006016.7311401
lambda = -2.0908e-07; f = 40666328343.9224930
lambda = -6.9692e-08; f = 4518477289.2747173
lambda = -2.3231e-08; f = 502050067.6834316
lambda = -7.7435e-09; f = 55780600.8520375
lambda = -2.5812e-09; f = 6195179.3562803
Norm of dx 9.6453e+11
Done for param rhog = 0.9848
Predicted improvement: 0.337345624
lambda = 1; f = -3406.6012432
lambda = 1.9332; f = -3407.2207375
lambda = 3.7372; f = -3408.3999643
lambda = 7.2247; f = -3410.6102473
lambda = 13.967; f = -3414.6172001
lambda = 27; f = -3421.2937375
lambda = 52.196; f = -3428.7378085
Norm of dx 0.00094013
Done for param rho_n = 0.9785
Predicted improvement: 0.035849770
lambda = 1; f = -3428.7895037
lambda = 1.9332; f = -3428.8029082
Norm of dx 0.001881
Done for param rho_k = 0.9286
Sequence of univariate steps!!
Actual dxnorm 0.055007
FVAL -3428.8029
Improvement 472.5577
Ftol 1e-05
Htol 1e-05
Gradient norm 6701.2995
Minimum Hessian eigenvalue 7362.4741
Maximum Hessian eigenvalue 59607619.2422
Elapsed time for iteration 1.1036 s.
Iteration 2
Predicted improvement: 28.824532748
lambda = 1; f = -3428.8027042
lambda = 0.33333; f = -3428.8028902
lambda = 0.11111; f = -3428.8029074
lambda = 0.037037; f = -3430.8036042
lambda = 0.071599; f = -3428.8029081
lambda = 0.048211; f = -3431.3539881
lambda = 0.061123; f = -3428.8029081
lambda = 0.053011; f = -3428.8029082
lambda = 0.048671; f = -3431.3760998
lambda = 0.05123; f = -3431.4984185
lambda = 0.053925; f = -3428.8029082
lambda = 0.052292; f = -3428.8029082
lambda = 0.051336; f = -3431.5034145
lambda = 0.051907; f = -3431.5305318
lambda = 0.052485; f = -3428.8029082
Norm of dx 0.04885
Predicted improvement: 22453707.810454942
lambda = 1; f = 40727696.3879433
lambda = 0.33333; f = 4521854.9713691
lambda = 0.11111; f = 499248.6966373
lambda = 0.037037; f = 52380.7751481
lambda = 0.012346; f = 2758.2276245
lambda = 0.0041152; f = -2745.5741827
lambda = 0.0013717; f = -3353.8361887
lambda = 0.00045725; f = -3420.5185776
lambda = 0.00015242; f = -3427.8896917
lambda = 5.0805e-05; f = -3428.7037963
lambda = 1.6935e-05; f = -3428.7926163
lambda = 5.645e-06; f = -3428.8019579
lambda = 1.8817e-06; f = -3428.8028541
lambda = 6.2723e-07; f = -3428.8029080
lambda = 2.0908e-07; f = -3428.8029081
lambda = 6.9692e-08; f = -3428.8029082
lambda = 2.3231e-08; f = -3428.8029082
lambda = 7.7435e-09; f = -3428.8029082
lambda = 2.5812e-09; f = -3428.8029082
lambda =
-6.2723e-07
lambda = -6.2723e-07; f = -3367.8902439
lambda = -2.0908e-07; f = -3415.9289605
lambda = -6.9692e-08; f = -3427.5759743
lambda = -2.3231e-08; f = -3430.3988322
lambda = -7.7435e-09; f = -3431.1763833
lambda = -2.5812e-09; f = -3431.4151441
Norm of dx 6701.3
Predicted improvement: 0.021429235
lambda = 1; f = -3431.5523118
Norm of dx 5.4162e-05
Done for param eps_z = 0.0054
Predicted improvement: 0.009600015
lambda = 1; f = -3431.5620157
Norm of dx 7.294e-05
Done for param eps_g = 0.0108
Predicted improvement: 0.190593864
lambda = 1; f = -3431.7667557
Norm of dx 0.00022569
Done for param eps_tk = 0.0080
Predicted improvement: 1.157651484
lambda = 1; f = -3433.3174405
Norm of dx 0.00037342
Done for param eps_tn = 0.0052
Predicted improvement: 0.163753291
lambda = 1; f = -3433.4709400
Norm of dx 0.00031904
Done for param y_obs = 0.0104
Predicted improvement: 0.301861688
lambda = 1; f = -3428.8029069
lambda = 0.33333; f = -3428.8029080
lambda = 0.11111; f = -3428.8029081
lambda = 0.037037; f = -3428.8029082
lambda = 0.012346; f = -3428.8029082
lambda = 0.0041152; f = -3428.8029082
lambda = 0.0013717; f = -3428.8029082
lambda = 0.00045725; f = -3433.4712159
lambda = 0.00088394; f = -3433.4714734
lambda = 0.0017088; f = -3428.8029082
lambda = 0.0011506; f = -3433.4716342
lambda = 0.0014588; f = -3428.8029082
lambda = 0.0012652; f = -3433.4717033
lambda = 0.001378; f = -3428.8029082
lambda = 0.0013092; f = -3433.4717298
lambda = 0.0013501; f = -3433.4717544
lambda = 0.0013922; f = -3428.8029082
lambda = 0.0013668; f = -3428.8029082
lambda = 0.0013517; f = -3433.4717554
Norm of dx 0.0011423
Done for param rhoz = 0.9960
Predicted improvement: 11.203367769
lambda = 1; f = -3445.3021184
Norm of dx 0.025955
Done for param rhog = 0.9564
Predicted improvement: 0.261968302
lambda = 1; f = -3445.5345251
Norm of dx 0.00421
Done for param rho_n = 0.9826
Predicted improvement: 0.004648236
lambda = 1; f = -3445.5392153
Norm of dx 0.00095028
Done for param rho_k = 0.9276
Sequence of univariate steps!!
Actual dxnorm 0.028681
FVAL -3445.5392
Improvement 16.7363
Ftol 1e-05
Htol 1e-05
Gradient norm 3201.6045
Minimum Hessian eigenvalue 6841.1297
Maximum Hessian eigenvalue 84918383.7806
Elapsed time for iteration 0.9942 s.
Iteration 3
Predicted improvement: 4.150645759
lambda = 1; f = -3445.5392022
lambda = 0.33333; f = -3445.5392138
lambda = 0.11111; f = -3445.5392151
lambda = 0.037037; f = -3445.5392152
lambda = 0.012346; f = -3445.5392153
lambda = 0.0041152; f = -3445.5392153
lambda = 0.0013717; f = -3445.5392153
lambda = 0.00045725; f = -3445.5392153
lambda = 0.00015242; f = -3445.5392153
lambda = 5.0805e-05; f = -3445.5392153
lambda = 1.6935e-05; f = -3445.5392153
lambda = 5.645e-06; f = -3445.5392153
lambda = 1.8817e-06; f = -3445.5392153
lambda = 6.2723e-07; f = -3445.5392153
lambda = 2.0908e-07; f = -3445.5392170
lambda = 4.0418e-07; f = -3445.5392153
lambda = 2.7215e-07; f = -3445.5392175
lambda = 3.4504e-07; f = -3445.5392153
lambda = 2.9925e-07; f = -3445.5392177
lambda = 3.2594e-07; f = -3445.5392153
lambda = 3.0965e-07; f = -3445.5392178
lambda = 3.1932e-07; f = -3445.5392153
lambda = 3.1349e-07; f = -3445.5392153
lambda = 3.1003e-07; f = -3445.5392153
Norm of dx 0.030265
Predicted improvement: 0.175010210
lambda = 1; f = -3445.7049258
Norm of dx 0.00016583
Done for param eps_z = 0.0052
Predicted improvement: 0.024194765
lambda = 1; f = -3445.7294542
Norm of dx 0.00011609
Done for param eps_g = 0.0109
Predicted improvement: 0.002979942
lambda = 1; f = -3445.7324525
Norm of dx 3.0716e-05
Done for param eps_tk = 0.0081
Predicted improvement: 0.174604886
lambda = 1; f = -3445.8960849
Norm of dx 0.00016018
Done for param eps_tn = 0.0050
Predicted improvement: 0.111865776
lambda = 1; f = -3446.0021044
Norm of dx 0.00025391
Done for param y_obs = 0.0101
Predicted improvement: 0.057861053
lambda = 1; f = -3446.0021043
lambda = 0.33333; f = -3446.0021044
lambda = 0.11111; f = -3446.0021044
lambda = 0.037037; f = -3446.0021044
lambda = 0.012346; f = -3446.0021044
lambda = 0.0041152; f = -3446.0021044
lambda = 0.0013717; f = -3446.0021044
lambda = 0.00045725; f = -3446.0021044
lambda = 0.00015242; f = -3446.0021044
lambda = 5.0805e-05; f = -3446.0021044
lambda = 1.6935e-05; f = -3446.0021044
lambda = 5.645e-06; f = -3446.0021044
lambda = 1.8817e-06; f = -3446.0021044
lambda = 6.2723e-07; f = -3446.0021044
lambda = 2.0908e-07; f = -3446.0021044
lambda = 6.9692e-08; f = -3446.0021044
lambda = 2.3231e-08; f = -3446.0021044
lambda = 7.7435e-09; f = -3446.0021044
lambda = 2.5812e-09; f = -3446.0021044
Norm of dx 2.8028e-10
Done for param rhoz = 0.9960
Predicted improvement: 0.986930551
lambda = 1; f = -3447.1964174
Norm of dx 0.010235
Done for param rhog = 0.9462
Predicted improvement: 0.001212997
lambda = 1; f = -3447.1976380
Norm of dx 0.00024022
Done for param rho_n = 0.9823
Predicted improvement: 0.003508858
lambda = 1; f = -3447.2011742
Norm of dx 0.00082239
Done for param rho_k = 0.9268
Sequence of univariate steps!!
Actual dxnorm 0.010277
FVAL -3447.2012
Improvement 1.662
Ftol 1e-05
Htol 1e-05
Gradient norm 8309794419.1946
Minimum Hessian eigenvalue -8611611.9069
Maximum Hessian eigenvalue 6.50475376212391e+22
Elapsed time for iteration 0.93573 s.
Iteration 4
Correct for low angle: 8.0171e-09
Predicted improvement: 196809.501126433
lambda = 1; f = -3446.9966807
lambda = 0.33333; f = -3447.2976899
lambda = 0.11111; f = -3447.2528323
lambda = 0.037037; f = -3447.2206062
lambda = 0.012346; f = -3447.2078992
lambda = 0.0041152; f = -3447.2034434
lambda = 0.0013717; f = -3447.2019337
lambda = 0.00045725; f = -3447.2014277
lambda = 0.00015242; f = -3447.2012587
lambda = 5.0805e-05; f = -3447.2012024
lambda = 1.6935e-05; f = -3447.2011836
lambda = 5.645e-06; f = -3447.2011773
lambda = 1.8817e-06; f = -3447.2011752
lambda = 6.2723e-07; f = -3447.2011745
lambda = 2.0908e-07; f = -3447.2011743
lambda = 6.9692e-08; f = -3447.2011742
lambda = 2.3231e-08; f = -3447.2011742
lambda = 7.7435e-09; f = -3447.2011742
lambda = 2.5812e-09; f = -3447.2011742
Norm of dx 0.0094737
Predicted improvement: 0.008329139
lambda = 1; f = -3447.3059205
Norm of dx 3.3887e-05
Done for param eps_z = 0.0052
Predicted improvement: 0.002447118
lambda = 1; f = -3447.3083875
Norm of dx 3.7986e-05
Done for param eps_g = 0.0110
Predicted improvement: 0.006247078
lambda = 1; f = -3447.3145756
Norm of dx 4.5565e-05
Done for param eps_tk = 0.0081
Predicted improvement: 0.002388636
lambda = 1; f = -3447.3169504
Norm of dx 1.7511e-05
Done for param eps_tn = 0.0051
Predicted improvement: 0.013305197
lambda = 1; f = -3447.3300675
Norm of dx 8.351e-05
Done for param y_obs = 0.0101
Predicted improvement: 0.000292278
lambda = 1; f = -3447.3306515
lambda = 1.9332; f = -3447.3311955
lambda = 3.7372; f = -3447.3322447
lambda = 7.2247; f = -3447.3342631
lambda = 13.967; f = -3447.2011742
lambda = 9.4043; f = -3447.3355180
lambda = 11.923; f = -3447.2011742
lambda = 10.341; f = -3447.3360556
lambda = 11.263; f = -3447.2011742
lambda = 10.7; f = -3447.3362617
lambda = 11.034; f = -3447.2011742
lambda = 10.833; f = -3447.2011742
lambda = 10.713; f = -3447.3362692
Norm of dx 1.4637e-06
Done for param rhoz = 0.9960
Predicted improvement: 0.011328610
lambda = 1; f = -3447.3476090
Norm of dx 0.0013846
Done for param rhog = 0.9417
Predicted improvement: 0.000032832
lambda = 1; f = -3447.3476418
Norm of dx 4.0096e-05
Done for param rho_n = 0.9822
Predicted improvement: 0.000138719
lambda = 1; f = -3447.3477803
Norm of dx 0.00016575
Done for param rho_k = 0.9266
Sequence of univariate steps!!
Actual dxnorm 0.0045188
FVAL -3447.3478
Improvement 0.14661
Ftol 1e-05
Htol 1e-05
Gradient norm 394.4323
Minimum Hessian eigenvalue 6333.1232
Maximum Hessian eigenvalue 99263759.0987
Elapsed time for iteration 1.1296 s.
Iteration 5
Predicted improvement: 0.207751735
lambda = 1; f = -3447.3477792
lambda = 0.33333; f = -3447.3477802
lambda = 0.11111; f = -3447.3477803
lambda = 0.037037; f = -3447.3477803
lambda = 0.012346; f = -3447.3477803
lambda = 0.0041152; f = -3447.3477803
lambda = 0.0013717; f = -3447.3477803
lambda = 0.00045725; f = -3447.3477803
lambda = 0.00015242; f = -3447.3477803
lambda = 5.0805e-05; f = -3447.3478014
lambda = 9.8216e-05; f = -3447.3478211
lambda = 0.00018987; f = -3447.3477803
lambda = 0.00012785; f = -3447.3477803
lambda = 0.00010084; f = -3447.3478222
lambda = 0.00011627; f = -3447.3477803
lambda = 0.00010675; f = -3447.3477803
lambda = 0.00010142; f = -3447.3478224
lambda = 0.00010458; f = -3447.3477803
lambda = 0.00010267; f = -3447.3478230
lambda = 0.00010381; f = -3447.3477803
Norm of dx 0.0056633
Predicted improvement: 0.000193505
lambda = 1; f = -3447.3480162
Norm of dx 5.0876e-06
Done for param eps_z = 0.0052
Predicted improvement: 0.000552074
lambda = 1; f = -3447.3485698
Norm of dx 1.8175e-05
Done for param eps_g = 0.0110
Predicted improvement: 0.000021773
lambda = 1; f = -3447.3485916
Norm of dx 3.3112e-06
Done for param y_obs = 0.0101
Predicted improvement: 0.000098015
lambda = 1; f = -3447.3485871
lambda = 0.33333; f = -3447.3485901
lambda = 0.11111; f = -3447.3485911
lambda = 0.037037; f = -3447.3485914
lambda = 0.012346; f = -3447.3485915
lambda = 0.0041152; f = -3447.3485916
lambda = 0.0013717; f = -3447.3485916
lambda = 0.00045725; f = -3447.3485916
lambda = 0.00015242; f = -3447.3485916
lambda = 5.0805e-05; f = -3447.3485916
lambda = 1.6935e-05; f = -3447.3485916
lambda = 5.645e-06; f = -3447.3485916
lambda = 1.8817e-06; f = -3447.3485916
lambda = 6.2723e-07; f = -3447.3485916
lambda = 2.0908e-07; f = -3447.3485916
lambda = 6.9692e-08; f = -3447.3485916
lambda = 2.3231e-08; f = -3447.3485916
lambda = 7.7435e-09; f = -3447.3485916
lambda = 2.5812e-09; f = -3447.3485916
Norm of dx 1.1516e-08
Done for param rhoz = 0.9960
Predicted improvement: 0.000052902
lambda = 1; f = -3447.3486445
Norm of dx 9.5516e-05
Done for param rhog = 0.9416
Sequence of univariate steps!!
Actual dxnorm 9.7807e-05
FVAL -3447.3486
Improvement 0.00086418
Ftol 1e-05
Htol 1e-05
Gradient norm 389.2664
Minimum Hessian eigenvalue 6306.205
Maximum Hessian eigenvalue 99264395.7911
Elapsed time for iteration 1.0403 s.
Iteration 6
Predicted improvement: 0.201477980
lambda = 1; f = -3447.3486434
lambda = 0.33333; f = -3447.3486444
lambda = 0.11111; f = -3447.3486445
lambda = 0.037037; f = -3447.3486445
lambda = 0.012346; f = -3447.3486445
lambda = 0.0041152; f = -3447.3486445
lambda = 0.0013717; f = -3447.3486445
lambda = 0.00045725; f = -3447.3486445
lambda = 0.00015242; f = -3447.3486445
lambda = 5.0805e-05; f = -3447.3486445
lambda = 1.6935e-05; f = -3447.3486445
lambda = 5.645e-06; f = -3447.3486445
lambda = 1.8817e-06; f = -3447.3486445
lambda = 6.2723e-07; f = -3447.3486445
lambda = 2.0908e-07; f = -3447.3486446
lambda = 4.0418e-07; f = -3447.3486445
lambda = 2.7215e-07; f = -3447.3486446
lambda = 3.4504e-07; f = -3447.3486446
lambda = 4.3745e-07; f = -3447.3486445
lambda = 3.794e-07; f = -3447.3486445
lambda = 3.4833e-07; f = -3447.3486446
lambda = 3.6665e-07; f = -3447.3486445
lambda = 3.5555e-07; f = -3447.3486446
lambda = 3.6217e-07; f = -3447.3486445
lambda = 3.5818e-07; f = -3447.3486446
Norm of dx 0.0055509
Predicted improvement: 0.083791763
lambda = 1; f = -3447.3486443
lambda = 0.33333; f = -3447.3486445
lambda = 0.11111; f = -3447.3486445
lambda = 0.037037; f = -3447.3486445
lambda = 0.012346; f = -3447.3486445
lambda = 0.0041152; f = -3447.3486445
lambda = 0.0013717; f = -3447.3486445
lambda = 0.00045725; f = -3447.3486445
lambda = 0.00015242; f = -3447.3486445
lambda = 5.0805e-05; f = -3447.3486445
lambda = 1.6935e-05; f = -3447.3486445
lambda = 5.645e-06; f = -3447.3486445
lambda = 1.8817e-06; f = -3447.3486445
lambda = 6.2723e-07; f = -3447.3486445
lambda = 2.0908e-07; f = -3447.3486445
lambda = 6.9692e-08; f = -3447.3486445
lambda = 2.3231e-08; f = -3447.3486445
lambda = 7.7435e-09; f = -3447.3486445
lambda = 2.5812e-09; f = -3447.3486446
lambda = 4.9899e-09; f = -3447.3486445
lambda = 3.3599e-09; f = -3447.3486445
lambda = 2.6501e-09; f = -3447.3486446
lambda = 3.0556e-09; f = -3447.3486446
lambda = 3.5232e-09; f = -3447.3486445
lambda = 3.2347e-09; f = -3447.3486445
lambda = 3.0731e-09; f = -3447.3486446
lambda = 3.1691e-09; f = -3447.3486445
lambda = 3.1111e-09; f = -3447.3486446
lambda = 3.1458e-09; f = -3447.3486445
Norm of dx 0.0032607
Sequence of univariate steps!!
Try diagonal Hessian
Predicted improvement: 0.040416163
lambda = 1; f = -3447.3486445
lambda = 0.33333; f = -3447.3486445
lambda = 0.11111; f = -3447.3486445
lambda = 0.037037; f = -3447.3486445
lambda = 0.012346; f = -3447.3486445
lambda = 0.0041152; f = -3447.3486445
lambda = 0.0013717; f = -3447.3486445
lambda = 0.00045725; f = -3447.3486445
lambda = 0.00015242; f = -3447.3486445
lambda = 5.0805e-05; f = -3447.3486445
lambda = 1.6935e-05; f = -3447.3486445
lambda = 5.645e-06; f = -3447.3486445
lambda = 1.8817e-06; f = -3447.3486445
lambda = 6.2723e-07; f = -3447.3486445
lambda = 2.0908e-07; f = -3447.3486445
lambda = 6.9692e-08; f = -3447.3486445
lambda = 2.3231e-08; f = -3447.3486445
lambda = 7.7435e-09; f = -3447.3486445
lambda = 2.5812e-09; f = -3447.3486445
lambda =
-6.2723e-07
lambda = -6.2723e-07; f = -3447.3486446
lambda = -2.0908e-07; f = -3447.3486446
lambda = -6.9692e-08; f = -3447.3486446
lambda = -2.3231e-08; f = -3447.3486446
lambda = -7.7435e-09; f = -3447.3486446
lambda = -2.5812e-09; f = -3447.3486446
Norm of dx 0.00020771
Try gradient direction
Predicted improvement: 7.576415326
lambda = 1; f = -3447.3471297
lambda = 0.33333; f = -3447.3484762
lambda = 0.11111; f = -3447.3486258
lambda = 0.037037; f = -3447.3486424
lambda = 0.012346; f = -3447.3486443
lambda = 0.0041152; f = -3447.3486445
lambda = 0.0013717; f = -3447.3486445
lambda = 0.00045725; f = -3447.3486445
lambda = 0.00015242; f = -3447.3486445
lambda = 5.0805e-05; f = -3447.3486445
lambda = 1.6935e-05; f = -3447.3486445
lambda = 5.645e-06; f = -3447.3486445
lambda = 1.8817e-06; f = -3447.3486445
lambda = 6.2723e-07; f = -3447.3486445
lambda = 2.0908e-07; f = -3447.3486445
lambda = 6.9692e-08; f = -3447.3486445
lambda = 2.3231e-08; f = -3447.3486445
lambda = 7.7435e-09; f = -3447.3486445
lambda = 2.5812e-09; f = -3447.3486445
lambda =
-6.2723e-07
lambda = -6.2723e-07; f = -3447.3486351
lambda = -2.0908e-07; f = -3447.3486415
lambda = -6.9692e-08; f = -3447.3486436
lambda = -2.3231e-08; f = -3447.3486443
lambda = -7.7435e-09; f = -3447.3486445
lambda = -2.5812e-09; f = -3447.3486446
Norm of dx 0.038927
No further improvement is possible!
Actual dxnorm 1.9951e-09
FVAL -3447.3486
Improvement 1.4485e-07
Ftol 1e-05
Htol 1e-05
Gradient norm 389.2664
Minimum Hessian eigenvalue 6306.205
Maximum Hessian eigenvalue 99264395.7911
Estimation successful.
Final value of minus the log posterior (or likelihood):-3447.348645
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.
The following parameters are at the prior bound: rhoz
Some potential solutions are:
- Check your model for mistakes.
- Check whether model and data are consistent (correct observation equation).
- Shut off prior_trunc.
- Change the optimization bounds.
- Use a different mode_compute like 6 or 9.
- Check whether the parameters estimated are identified.
- Check prior shape (e.g. Inf density at bound(s)).
- Increase the informativeness of the prior.
[Warning: The results below are most likely wrong!]
[> In dynare_estimation_1 (line 324)
In dynare_estimation (line 105)
In RBC_tax_estimation.driver (line 375)
In dynare (line 293)]
MODE CHECK
Fval obtained by the minimization routine (minus the posterior/likelihood)): -3447.348645
[Warning: Matrix is singular, close to singular or badly scaled. Results may be inaccurate. RCOND = NaN.]
[> In dynare_estimation_1 (line 347)
In dynare_estimation (line 105)
In RBC_tax_estimation.driver (line 375)
In dynare (line 293)
]
RESULTS FROM POSTERIOR ESTIMATION
parameters
prior mean mode s.d. prior pstdev
rhoz 0.700 0.9960 NaN beta 0.1000
rhog 0.700 0.9416 NaN beta 0.1000
rho_n 0.700 0.9822 NaN beta 0.1000
rho_k 0.700 0.9266 NaN beta 0.1000
standard deviation of shocks
prior mean mode s.d. prior pstdev
eps_z 0.010 0.0052 NaN invg 0.1000
eps_g 0.010 0.0110 NaN invg 0.1000
eps_tk 0.010 0.0081 NaN invg 0.1000
eps_tn 0.010 0.0051 NaN invg 0.1000
standard deviation of measurement errors
prior mean mode s.d. prior pstdev
y_obs 0.010 0.0101 NaN invg 0.1000
Log data density [Laplace approximation] is NaN.
{Error using chol
Matrix must be positive definite.
Error in posterior_sampler_initialization (line 84)
d = chol(vv);
Error in posterior_sampler (line 60)
posterior_sampler_initialization(TargetFun, xparam1, vv,
mh_bounds,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,oo_);
Error in dynare_estimation_1 (line 474)
posterior_sampler(objective_function,posterior_sampler_options.proposal_distribution,xparam1,posterior_sampler_options,bounds,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,oo_);
Error in dynare_estimation (line 105)
dynare_estimation_1(var_list,dname);
Error in RBC_tax_estimation.driver (line 375)
oo_recursive_=dynare_estimation(var_list_);
Error in dynare (line 293)
evalin('base',[fname '.driver']) ;}