Starting Dynare (version 5.0).
Calling Dynare with arguments: none
Starting preprocessing of the model file ...
WARNING: simple_NK.mod:19.1-21.12: Symbol pi_bar declared twice.
Found 9 equation(s).
Evaluating expressions...done
Computing static model derivatives (order 1).
Computing dynamic model derivatives (order 1).
Processing outputs ...
done
Preprocessing completed.
You did not declare endogenous variables after the estimation/calib_smoother command.
[Warning: Some of the parameters have no value (NN, bar_pi) when using initial_estimation_checks. If these parameters are not initialized in a
steadystate file or a steady_state_model-block, Dynare may not be able to solve the model. Note that simul, perfect_foresight_setup, and
perfect_foresight_solver do not automatically call the steady state file.]
Initial value of the log posterior (or likelihood): -1984.1027
==========================================================
Change in the posterior covariance matrix = 4.
Change in the posterior mean = 0.12639.
Current mode = 1428.531
Mode improvement = 555.5717
New value of jscale = 0.00021292
==========================================================
==========================================================
Change in the posterior covariance matrix = 0.0033923.
Change in the posterior mean = 0.24722.
Current mode = 1272.672
Mode improvement = 155.859
New value of jscale = 0.6179
==========================================================
==========================================================
Change in the posterior covariance matrix = 0.032329.
Change in the posterior mean = 0.39981.
Current mode = 1384.1295
Mode improvement = 111.4575
New value of jscale = 0.13885
==========================================================
Optimal value of the scale parameter = 0.13885
Final value of minus the log posterior (or likelihood):1384.129491
RESULTS FROM POSTERIOR ESTIMATION
parameters
prior mean mode s.d. prior pstdev
theta 0.6000 0.4140 0.0624 beta 0.1500
sigma 2.5000 1.1000 0.0187 norm 0.2500
phi_pi 1.5000 3.0903 0.1890 norm 0.2500
phi_y 0.1250 0.1475 0.0384 gamm 0.1000
rho_i 0.5000 0.1326 0.0495 beta 0.1000
rho_a 0.5000 0.9956 0.0363 gamm 0.1000
rho_g 0.5000 0.5631 0.0146 gamm 0.1000
standard deviation of shocks
prior mean mode s.d. prior pstdev
e_a 0.0500 0.0168 0.0017 invg 2.0000
e_m 0.0500 0.0333 0.0006 invg 2.0000
e_g 0.0500 0.0059 0.0001 invg 2.0000
Log data density [Laplace approximation] is -1424.544363.
Estimation::mcmc: Multiple chains mode.
Estimation::mcmc: Old mh-files successfully erased!
Estimation::mcmc: Old metropolis.log file successfully erased!
Estimation::mcmc: Creation of a new metropolis.log file.
Estimation::mcmc: Searching for initial values...
Estimation::mcmc: Initial values found!
Estimation::mcmc: Write details about the MCMC... Ok!
Estimation::mcmc: Details about the MCMC are available in simple_NK/metropolis/simple_NK_mh_history_0.mat
Estimation::mcmc: Number of mh files: 1 per block.
Estimation::mcmc: Total number of generated files: 2.
Estimation::mcmc: Total number of iterations: 2000.
Estimation::mcmc: Current acceptance ratio per chain:
Chain 1: 31.2%
Chain 2: 35.3%
Estimation::mcmc: Total number of MH draws per chain: 2000.
Estimation::mcmc: Total number of generated MH files: 1.
Estimation::mcmc: I'll use mh-files 1 to 1.
Estimation::mcmc: In MH-file number 1 I'll start at line 1001.
Estimation::mcmc: Finally I keep 1000 draws per chain.
MCMC Inefficiency factors per block
Parameter Block 1 Block 2
SE_e_a 159.272 159.998
SE_e_m 165.358 50.459
SE_e_g 35.606 215.093
theta 101.115 169.469
sigma 131.701 30.499
phi_pi 26.291 21.258
phi_y 62.880 85.559
rho_i 213.731 172.997
rho_a 40.783 47.599
rho_g 107.554 247.548
[Warning: estimation:: MCMC convergence diagnostics are not computed because the total number of iterations is not bigger than 2000!]
[> In McMCDiagnostics (line 127)
In dynare_estimation_1 (line 490)
In dynare_estimation (line 118)
In simple_NK.driver (line 309)
In dynare (line 281)]
Estimation::marginal density: I'm computing the posterior mean and covariance... Done!
Estimation::marginal density: I'm computing the posterior log marginal density (modified harmonic mean)... Done!
ESTIMATION RESULTS
Log data density is -1429.618329.
parameters
prior mean post. mean 90% HPD interval prior pstdev
theta 0.600 0.4365 0.3708 0.5017 beta 0.1500
sigma 2.500 1.1159 1.1006 1.1287 norm 0.2500
phi_pi 1.500 3.0689 3.0384 3.0902 norm 0.2500
phi_y 0.125 0.1586 0.1383 0.1880 gamm 0.1000
rho_i 0.500 0.1451 0.0942 0.1813 beta 0.1000
rho_a 0.500 0.9889 0.9771 0.9999 gamm 0.1000
rho_g 0.500 0.5706 0.5392 0.5927 gamm 0.1000
standard deviation of shocks
prior mean post. mean 90% HPD interval prior pstdev
e_a 0.050 0.0168 0.0154 0.0180 invg 2.0000
e_m 0.050 0.0325 0.0318 0.0333 invg 2.0000
e_g 0.050 0.0060 0.0059 0.0062 invg 2.0000
[Warning: Some of the parameters have no value (NN, bar_pi) when using stoch_simul. If these parameters are not initialized in a steadystate file or a
steady_state_model-block, Dynare may not be able to solve the model. Note that simul, perfect_foresight_setup, and perfect_foresight_solver do not
automatically call the steady state file.]
MODEL SUMMARY
Number of variables: 9
Number of stochastic shocks: 3
Number of state variables: 5
Number of jumpers: 2
Number of static variables: 3
MATRIX OF COVARIANCE OF EXOGENOUS SHOCKS
Variables e_a e_g e_m
e_a 0.000282 0.000000 0.000000
e_g 0.000000 0.000036 0.000000
e_m 0.000000 0.000000 0.001055
POLICY AND TRANSITION FUNCTIONS
y pi
i(-1) -0.027060 -0.043188
g(-1) 0.091398 0.258172
a(-1) 0.465624 -0.040251
e_a 0.470868 -0.040705
e_g 0.160168 0.452425
e_m -0.186481 -0.297629
MOMENTS OF SIMULATED VARIABLES
VARIABLE MEAN STD. DEV. VARIANCE SKEWNESS KURTOSIS
y -0.050906 0.063683 0.004056 0.134031 -0.819302
pi 0.004012 0.010898 0.000119 -0.094061 0.050428
CORRELATION OF SIMULATED VARIABLES
VARIABLE y pi
y 1.0000 -0.3473
pi -0.3473 1.0000
AUTOCORRELATION OF SIMULATED VARIABLES
VARIABLE 1 2 3 4 5
y 0.9832 0.9745 0.9678 0.9603 0.9528
pi 0.2629 0.1980 0.1998 0.1841 0.1463
VARIANCE DECOMPOSITION SIMULATING ONE SHOCK AT A TIME (in percent)
e_a e_g e_m Tot. lin. contr.
y 98.35 0.03 0.85 99.23
pi 22.70 8.99 74.12 105.80
Note: numbers do not add up to 100 due to non-zero correlation of simulated shocks in small samples
Total computing time : 0h14m11s
Note: 1 warning(s) encountered in the preprocessor
Note: warning(s) encountered in MATLAB/Octave code