222 lines
11 KiB
Modula-2
222 lines
11 KiB
Modula-2
% =========================================================================
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% Copyright © 2020-2021 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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% =========================================================================
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% Define testscenario
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@#define orderApp = 1
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@#define estimParams = 0
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% Note that we will set the numerical optimization tolerance levels very large to speed up the testsuite
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@#define optimizer = 5
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@#include "RBC_MoM_common.inc"
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shocks;
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var u_a; stderr 0.0072;
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var n; stderr 0.01;
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end;
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varobs n c iv;
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@#if estimParams == 0
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estimated_params;
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DELTA, 0.025;
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BETTA, 0.984;
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B, 0.5;
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%ETAl, 1;
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ETAc, 1;
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ALFA, 0.667;
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RHOA, 0.979;
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stderr u_a, 0.0072;
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%THETA, 3.48;
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stderr n, 0.01;
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end;
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@#endif
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@#if estimParams == 1
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estimated_params;
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DELTA, 0.02, 0, 1;
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BETTA, 0.90, 0, 1;
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B, 0.40, 0, 1;
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%ETAl, 1, 0, 10;
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ETAc, 1.80, 0, 10;
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ALFA, 0.60, 0, 1;
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RHOA, 0.90, 0, 1;
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stderr u_a, 0.01, 0, 1;
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stderr n, 0.01, 0, 1;
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end;
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@#endif
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@#if estimParams == 2
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estimated_params;
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DELTA, 0.02, 0, 1, normal_pdf, 0.02, 0.5;
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BETTA, 0.90, 0, 1, beta_pdf, 0.90, 0.25;
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B, 0.40, 0, 1, normal_pdf, 0.40, 0.5;
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%ETAl, 1, 0, 10, normal_pdf, 0.25, 0.0.1;
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ETAc, 1.80, 0, 10, normal_pdf, 1.80, 0.5;
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ALFA, 0.60, 0, 1, normal_pdf, 0.60, 0.5;
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RHOA, 0.90, 0, 1, normal_pdf, 0.90, 0.5;
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stderr u_a, 0.01, 0, 1, normal_pdf, 0.01, 0.5;
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stderr n, 0.001, 0, 1, normal_pdf, 0.01, 0.5;
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end;
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@#endif
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% Simulate data
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stoch_simul(order=@{orderApp},pruning,nodisplay,nomoments,periods=250);
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save('RBC_MoM_data_@{orderApp}.mat', options_.varobs{:} );
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pause(1);
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%--------------------------------------------------------------------------
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% Method of Moments Estimation
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%--------------------------------------------------------------------------
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% matched_moments blocks : We don't have an interface yet
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matched_moments;
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c;
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n;
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iv;
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c*c;
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c*iv;
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c*n;
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iv*c;
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iv*iv;
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iv*n;
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n*n;
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c*c(-1);
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n*n(-1);
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iv*iv(-1);
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end;
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% get indices in declaration order
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ic = strmatch('c', M_.endo_names,'exact');
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iiv = strmatch('iv', M_.endo_names,'exact');
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in = strmatch('n', M_.endo_names,'exact');
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% first entry: number of variable in declaration order
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% second entry: lag
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% third entry: power
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matched_moments_ = {
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[ic ] [0 ], [1 ];
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[in ] [0 ], [1 ];
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[iiv ] [0 ], [1 ];
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[ic ic ] [0 0], [1 1];
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[ic iiv] [0 0], [1 1];
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[ic in ] [0 0], [1 1];
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[ic iiv] [0 0], [1 1];
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[iiv iiv] [0 0], [1 1];
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[in iiv] [0 0], [1 1];
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% [in ic ] [0 0], [1 1];
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% [in iiv] [0 0], [1 1];
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[in in ] [0 0], [1 1];
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[ic ic ] [0 -1], [1 1];
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[in in ] [0 -1], [1 1];
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[iiv iiv] [0 -1], [1 1];
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% [iiv iiv] [0 -1], [1 1];
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};
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if ~isequal(M_.matched_moments,matched_moments_)
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error('Translation to matched_moments-block failed')
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end
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@#for mommethod in ["SMM"]
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method_of_moments(
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% Necessary options
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mom_method = @{mommethod} % method of moments method; possible values: GMM|SMM
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, datafile = 'RBC_MoM_data_@{orderApp}.mat' % name of filename with data
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% Options for both GMM and SMM
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% , bartlett_kernel_lag = 20 % bandwith in optimal weighting matrix
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, order = @{orderApp} % order of Taylor approximation in perturbation
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% , penalized_estimator % include deviation from prior mean as additional moment restriction and use prior precision as weight
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, pruning % use pruned state space system at higher-order
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% , verbose % display and store intermediate estimation results
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, weighting_matrix = ['identity_matrix'] % weighting matrix in moments distance objective function; possible values: OPTIMAL|IDENTITY_MATRIX|DIAGONAL|filename. Size of cell determines stages in iterated estimation, e.g. two state with ['DIAGONAL','OPTIMAL']
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, weighting_matrix_scaling_factor=10 % scaling of weighting matrix in objective function
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% , se_tolx=1e-6 % step size for numerical computation of standard errors
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% Options for SMM
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, burnin=250 % number of periods dropped at beginning of simulation
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% , bounded_shock_support % trim shocks in simulation to +- 2 stdev
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% , seed = 24051986 % seed used in simulations
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% , simulation_multiple = 5 % multiple of the data length used for simulation
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% Options for GMM
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% , analytic_standard_errors % compute standard errors using analytical derivatives
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% General options
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% , dirname = 'MM' % directory in which to store estimation output
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% , graph_format = EPS % specify the file format(s) for graphs saved to disk
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% , nodisplay % do not display the graphs, but still save them to disk
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% , nograph % do not create graphs (which implies that they are not saved to the disk nor displayed)
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% , noprint % do not print stuff to console
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% , plot_priors = 1 % control plotting of priors
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% , prior_trunc = 1e-10 % probability of extreme values of the prior density that is ignored when computing bounds for the parameters
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% , TeX % print TeX tables and graphics
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% Data and model options
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% , first_obs = 501 % number of first observation
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% , logdata % if data is already in logs
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% , nobs = 250 % number of observations
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% , prefilter=0 % demean each data series by its empirical mean and use centered moments
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% , xls_sheet = data % name/number of sheet with data in Excel
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% , xls_range = B2:D200 % range of data in Excel sheet
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% Optimization options that can be set by the user in the mod file, otherwise default values are provided
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% , huge_number=1e7 % value for replacing the infinite bounds on parameters by finite numbers. Used by some optimizers for numerical reasons
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, mode_compute = @{optimizer} % specifies the optimizer for minimization of moments distance
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%, additional_optimizer_steps = [1 2 3 4] % vector of additional mode-finders run after mode_compute
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% optim: a list of NAME and VALUE pairs to set options for the optimization routines. Available options depend on mode_compute, some exemplary common options:
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% , optim = ('TolFun' , 1e-6 % termination tolerance on the function value, a positive scalar
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% ,'TolX' , 1e-6 % termination tolerance on x, a positive scalar
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% ,'MaxIter' , 3000 % maximum number of iterations allowed, a positive integer
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% ,'MaxFunEvals' , 1D6 % maximum number of function evaluations allowed, a positive integer
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% ,'UseParallel' , 1 % when true (and supported by optimizer) solver estimates gradients in parallel (using Matlab/Octave's parallel toolbox)
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% ,'Jacobian' , 'off' % when 'off' gradient-based solvers approximate Jacobian using finite differences; for GMM we can also pass the analytical Jacobian to gradient-based solvers by setting this 'on'
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% )
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, silent_optimizer % run minimization of moments distance silently without displaying results or saving files in between
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% Numerical algorithms options
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% , aim_solver % Use AIM algorithm to compute perturbation approximation
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% , k_order_solver % use k_order_solver in higher order perturbation approximations
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% , dr=default % method used to compute the decision rule; possible values are DEFAULT, CYCLE_REDUCTION, LOGARITHMIC_REDUCTION
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% , dr_cycle_reduction_tol = 1e-7 % convergence criterion used in the cycle reduction algorithm
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% , dr_logarithmic_reduction_tol = 1e-12 % convergence criterion used in the logarithmic reduction algorithm
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% , dr_logarithmic_reduction_maxiter = 100 % maximum number of iterations used in the logarithmic reduction algorithm
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% , lyapunov = DEFAULT % algorithm used to solve lyapunov equations; possible values are DEFAULT, FIXED_POINT, DOUBLING, SQUARE_ROOT_SOLVER
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% , lyapunov_complex_threshold = 1e-15 % complex block threshold for the upper triangular matrix in symmetric Lyapunov equation solver
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% , lyapunov_fixed_point_tol = 1e-10 % convergence criterion used in the fixed point Lyapunov solver
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% , lyapunov_doubling_tol = 1e-16 % convergence criterion used in the doubling algorithm
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% , sylvester = default % algorithm to solve Sylvester equation; possible values are DEFAULT, FIXED_POINT
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% , sylvester_fixed_point_tol = 1e-12 % convergence criterion used in the fixed point Sylvester solver
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% , qz_criterium = 0.999999 % value used to split stable from unstable eigenvalues in reordering the Generalized Schur decomposition used for solving first order problems
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% , qz_zero_threshold = 1e-6 % value used to test if a generalized eigenvalue is 0/0 in the generalized Schur decomposition
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% , schur_vec_tol=1e-11 % tolerance level used to find nonstationary variables in Schur decomposition of the transition matrix
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% , mode_check % plot the target function for values around the computed minimum for each estimated parameter in turn
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% , mode_check_neighbourhood_size = 5 % width of the window (expressed in percentage deviation) around the computed minimum to be displayed on the diagnostic plots
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% , mode_check_symmetric_plots=1 % ensure that the check plots are symmetric around the minimum
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% , mode_check_number_of_points = 20 % number of points around the minimum where the target function is evaluated (for each parameter)
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);
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@#endfor
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