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| 文件名: An Estimated New Keynesian DSGE Model_Turkey.pdf | |
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有没有同学在进行DSGE运算时,dynare的运算结果是这样?怎么样解决,不知道问题出在哪里了
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 gi at 643 In dynare at 132 Warning: Matrix is singular to working precision. > In dynare_estimation_1 at 450 In dynare_estimation at 62 In gi at 643 In dynare at 132 RESULTS FROM POSTERIOR MAXIMIZATION parameters prior mean mode s.d. t-stat prior pstdev gamma 0.870 0.8700 Inf 0.0000 gamm 0.5000 kappa 1.100 1.1000 Inf 0.0000 gamm 0.5000 h 0.700 0.7000 Inf 0.0000 beta 0.2000 s 5.000 5.0000 Inf 0.0000 gamm 0.2500 delta_2 0.700 0.7000 Inf 0.0000 gamm 0.5000 rho_b 0.500 0.5000 Inf 0.0000 beta 0.2000 rho_l 0.500 0.5000 Inf 0.0000 beta 0.2000 rho_a 0.500 0.5000 Inf 0.0000 beta 0.2000 rho_i 0.500 0.5000 Inf 0.0000 beta 0.2000 rho_z 0.500 0.5000 Inf 0.0000 beta 0.2000 rho_tl 0.500 0.5000 Inf 0.0000 beta 0.2000 rho_tk 0.500 0.5000 Inf 0.0000 beta 0.2000 rho_tc 0.500 0.5000 Inf 0.0000 beta 0.2000 rho_g 0.500 0.5000 Inf 0.0000 beta 0.2000 rho_d 0.500 0.5000 Inf 0.0000 beta 0.2000 rho_A 0.500 0.5000 Inf 0.0000 beta 0.2000 sigma_b 1.000 1.0000 Inf 0.0000 invg 4.0000 sigma_l 1.000 1.0000 Inf 0.0000 invg 4.0000 sigma_a 1.000 1.0000 Inf 0.0000 invg 4.0000 sigma_i 1.000 1.0000 Inf 0.0000 invg 4.0000 sigma_z 1.000 1.0000 Inf 0.0000 invg 4.0000 sigma_tl 1.000 1.0000 Inf 0.0000 invg 4.0000 sigma_tk 1.000 1.0000 Inf 0.0000 invg 4.0000 sigma_tc 1.000 1.0000 Inf 0.0000 invg 4.0000 sigma_g 1.000 1.0000 Inf 0.0000 invg 4.0000 sigma_d 1.000 1.0000 Inf 0.0000 invg 4.0000 sigma_A 1.000 1.0000 Inf 0.0000 invg 4.0000 phi_z 0.200 0.2000 Inf 0.0000 gamm 0.1000 phi_tk 1.000 1.0000 Inf 0.0000 gamm 0.3000 phi_tl 0.500 0.5000 Inf 0.0000 gamm 0.2500 phi_g 0.070 0.0700 Inf 0.0000 gamm 0.3000 phi_kl 0.250 0.2500 Inf 0.0000 norm 0.1000 phi_kc 0.050 0.0500 Inf 0.0000 norm 0.1000 phi_lc 0.050 0.0500 Inf 0.0000 norm 0.1000 phi_d 0.050 0.0500 Inf 0.0000 norm 0.1000 gamma_z 0.150 0.1500 Inf 0.0000 gamm 0.2000 gamma_tk 0.150 0.1500 Inf 0.0000 gamm 0.2000 gamma_tl 0.150 0.1500 Inf 0.0000 gamm 0.2000 gamma_g 0.150 0.1500 Inf 0.0000 gamm 0.2000 gamma_d 0.150 0.1500 Inf 0.0000 gamm 0.2000 Log data density [Laplace approximation] is NaN. MH: Multiple chains mode. MH: Old _mh files successfully erased! MH: Searching for initial values... MH: I couldn't get a valid initial value in 100 trials. MH: You should Reduce mh_init_scale... MH: Parameter mh_init_scale is equal to 0.400000. MH: Enter a new value... |
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