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