268 lines
19 KiB
Matlab
268 lines
19 KiB
Matlab
function options_mom_ = default_option_mom_values(options_mom_, options_, dname, doBayesianEstimation)
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% function options_mom_ = default_option_mom_values(options_mom_, options_, dname, doBayesianEstimation)
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% Returns structure containing the options for method_of_moments command
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% options_mom_ is local and contains default and user-specified values for
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% all settings needed for the method of moments estimation. Some options,
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% though, are set by the preprocessor into options_ and we copy these over.
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% The idea is to be independent of options_ and have full control of the
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% estimation instead of possibly having to deal with options chosen somewhere
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% else in the mod file.
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% =========================================================================
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% INPUTS
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% o options_mom_: [structure] information about all (user-specified and updated) settings used in estimation (options_mom_)
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% o options_: [structure] information on global options
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% o dname: [string] name of directory to store results
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% o doBayesianEstimation [boolean] indicator whether we do Bayesian estimation
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% -------------------------------------------------------------------------
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% OUTPUTS
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% o oo_: [structure] storage for results (oo_)
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% o options_mom_: [structure] information about all (user-specified and updated) settings used in estimation (options_mom_)
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% -------------------------------------------------------------------------
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% This function is called by
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% o mom.run
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% -------------------------------------------------------------------------
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% This function calls
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% o set_default_option
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% o user_has_matlab_license
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% o user_has_octave_forge_package
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% -------------------------------------------------------------------------
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% Copyright © 2023 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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mom_method = options_mom_.mom.mom_method; % this is a required option
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% -------------------------------------------------------------------------
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% LIMITATIONS
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% -------------------------------------------------------------------------
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if options_.logged_steady_state || options_.loglinear
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error('method_of_moments: The loglinear option is not supported. Please append the required logged variables as auxiliary equations.')
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else
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options_mom_.logged_steady_state = 0;
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options_mom_.loglinear = false;
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end
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options_mom_.hessian.use_penalized_objective = false; % penalized objective not yet
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% options related to variable declarations
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if isfield(options_,'trend_coeffs')
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error('method_of_moments: %s does not allow for trend in data',mom_method)
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end
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% options related to endogenous prior restrictions are not supported
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if ~isempty(options_.endogenous_prior_restrictions.irf) && ~isempty(options_.endogenous_prior_restrictions.moment)
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fprintf('method_of_moments: Endogenous prior restrictions are not supported yet and will be skipped.\n')
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end
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options_mom_.endogenous_prior_restrictions.irf = {};
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options_mom_.endogenous_prior_restrictions.moment = {};
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options_mom_.mom.analytic_jacobian_optimizers = [1, 3, 4, 13, 101]; % these are currently supported optimizers that are able to use the analytical_jacobian option
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% -------------------------------------------------------------------------
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% OPTIONS POSSIBLY SET BY THE USER
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% -------------------------------------------------------------------------
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% common settings
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options_mom_ = set_default_option(options_mom_,'dirname',dname); % specify directory in which to store estimation output
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options_mom_ = set_default_option(options_mom_,'graph_format','eps'); % specify the file format(s) for graphs saved to disk
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options_mom_ = set_default_option(options_mom_,'nodisplay',false); % do not display the graphs, but still save them to disk
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options_mom_ = set_default_option(options_mom_,'nograph',false); % do not create graphs (which implies that they are not saved to the disk nor displayed)
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options_mom_ = set_default_option(options_mom_,'noprint',false); % do not print output to console
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options_mom_ = set_default_option(options_mom_,'TeX',false); % print TeX tables and graphics
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options_mom_.mom = set_default_option(options_mom_.mom,'verbose',false); % display and store intermediate estimation results
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%options_mom_ = set_default_option(options_mom_,'verbosity',false); %
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if doBayesianEstimation
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options_mom_ = set_default_option(options_mom_,'plot_priors',true); % control plotting of priors
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options_mom_ = set_default_option(options_mom_,'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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end
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% specific method_of_moments settings
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if strcmp(mom_method,'GMM') || strcmp(mom_method,'SMM')
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options_mom_.mom = set_default_option(options_mom_.mom,'bartlett_kernel_lag',20); % bandwith in optimal weighting matrix
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options_mom_.mom = set_default_option(options_mom_.mom,'penalized_estimator',false); % include deviation from prior mean as additional moment restriction and use prior precision as weights
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options_mom_.mom = set_default_option(options_mom_.mom,'se_tolx',1e-5); % step size for numerical computation of standard errors
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options_mom_.mom = set_default_option(options_mom_.mom,'weighting_matrix_scaling_factor',1); % scaling of weighting matrix in objective function
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options_mom_.mom = set_default_option(options_mom_.mom,'weighting_matrix',{'DIAGONAL'; 'OPTIMAL'}); % weighting matrix in moments distance objective function at each iteration of estimation;
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% possible values are 'OPTIMAL', 'IDENTITY_MATRIX' ,'DIAGONAL' or a filename. Size of cell determines stages in iterated estimation.
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end
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if strcmp(mom_method,'SMM')
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options_mom_.mom = set_default_option(options_mom_.mom,'burnin',500); % number of periods dropped at beginning of simulation
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options_mom_.mom = set_default_option(options_mom_.mom,'bounded_shock_support',false); % trim shocks in simulation to +- 2 stdev
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options_mom_.mom = set_default_option(options_mom_.mom,'seed',24051986); % seed used in simulations
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options_mom_.mom = set_default_option(options_mom_.mom,'simulation_multiple',7); % multiple of the data length used for simulation
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end
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if strcmp(mom_method,'GMM')
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options_mom_.mom = set_default_option(options_mom_.mom,'analytic_standard_errors',false); % compute standard errors numerically (0) or analytically (1). Analytical derivatives are only available for GMM.
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end
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% data related options
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if strcmp(mom_method,'GMM') || strcmp(mom_method,'SMM')
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options_mom_ = set_default_option(options_mom_,'first_obs',1); % number of first observation
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options_mom_ = set_default_option(options_mom_,'logdata',false); % if data is already in logs
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options_mom_ = set_default_option(options_mom_,'nobs',NaN); % number of observations
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options_mom_ = set_default_option(options_mom_,'prefilter',false); % demean each data series by its empirical mean and use centered moments
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options_mom_ = set_default_option(options_mom_,'xls_sheet',1); % name of sheet with data in Excel, Octave does not support the empty string, rather use first sheet
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options_mom_ = set_default_option(options_mom_,'xls_range',''); % range of data in Excel sheet
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end
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% optimization related
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if (isoctave && user_has_octave_forge_package('optim')) || (~isoctave && user_has_matlab_license('optimization_toolbox'))
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if strcmp(mom_method,'GMM') || strcmp(mom_method,'SMM')
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options_mom_ = set_default_option(options_mom_,'mode_compute',13); % specifies lsqnonlin as default optimizer for minimization
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end
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else
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options_mom_ = set_default_option(options_mom_,'mode_compute',4); % specifies csminwel as fallback default option for minimization
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end
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options_mom_ = set_default_option(options_mom_,'additional_optimizer_steps',[]); % vector of additional mode-finders run after mode_compute
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options_mom_ = set_default_option(options_mom_,'optim_opt',[]); % a list of NAME and VALUE pairs to set options for the optimization routines. Available options depend on mode_compute
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options_mom_ = set_default_option(options_mom_,'silent_optimizer',false); % run minimization of moments distance silently without displaying results or saving files in between
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options_mom_ = set_default_option(options_mom_,'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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options_mom_.mom = set_default_option(options_mom_.mom,'analytic_jacobian',false); % use analytic Jacobian in optimization, only available for GMM and gradient-based optimizers
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options_mom_.optimizer_vec = [options_mom_.mode_compute;num2cell(options_mom_.additional_optimizer_steps)];
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% perturbation related
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options_mom_ = set_default_option(options_mom_,'order',1); % order of Taylor approximation in perturbation
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options_mom_ = set_default_option(options_mom_,'pruning',false); % use pruned state space system at order>1
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options_mom_ = set_default_option(options_mom_,'aim_solver',false); % use AIM algorithm to compute perturbation approximation instead of mjdgges
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options_mom_ = set_default_option(options_mom_,'k_order_solver',false); % use k_order_perturbation instead of mjdgges
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options_mom_ = set_default_option(options_mom_,'dr_cycle_reduction',false); % use cycle reduction algorithm to solve the polynomial equation for retrieving the coefficients associated to the endogenous variables in the decision rule
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options_mom_ = set_default_option(options_mom_,'dr_cycle_reduction_tol',1e-7); % convergence criterion used in the cycle reduction algorithm
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options_mom_ = set_default_option(options_mom_,'dr_logarithmic_reduction',false); % use logarithmic reduction algorithm to solve the polynomial equation for retrieving the coefficients associated to the endogenous variables in the decision rule
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options_mom_ = set_default_option(options_mom_,'dr_logarithmic_reduction_maxiter',100); % maximum number of iterations used in the logarithmic reduction algorithm
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options_mom_ = set_default_option(options_mom_,'dr_logarithmic_reduction_tol',1e-12); % convergence criterion used in the cycle reduction algorithm
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options_mom_ = set_default_option(options_mom_,'qz_criterium',1-1e-6); % value used to split stable from unstable eigenvalues in reordering the Generalized Schur decomposition used for solving first order problems
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% if there are no unit roots one can use 1.0 (or slightly below) which we set as default; if they are possible, you may have have multiple unit roots and the accuracy decreases when computing the eigenvalues in lyapunov_symm
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% Note that unit roots are only possible at first-order, at higher order we set it to 1 in pruned_state_space_system and focus only on stationary observables.
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options_mom_ = set_default_option(options_mom_,'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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options_mom_ = set_default_option(options_mom_,'schur_vec_tol',1e-11); % tolerance level used to find nonstationary variables in Schur decomposition of the transition matrix.
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% numerical algorithms
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options_mom_ = set_default_option(options_mom_,'lyapunov_db',false); % doubling algorithm (disclyap_fast) to solve Lyapunov equation to compute variance-covariance matrix of state variables
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options_mom_ = set_default_option(options_mom_,'lyapunov_fp',false); % fixed-point algorithm to solve Lyapunov equation to compute variance-covariance matrix of state variables
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options_mom_ = set_default_option(options_mom_,'lyapunov_srs',false); % square-root-solver (dlyapchol) algorithm to solve Lyapunov equation to compute variance-covariance matrix of state variables
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options_mom_ = set_default_option(options_mom_,'lyapunov_complex_threshold',1e-15); % complex block threshold for the upper triangular matrix in symmetric Lyapunov equation solver
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options_mom_ = set_default_option(options_mom_,'lyapunov_fixed_point_tol',1e-10); % convergence criterion used in the fixed point Lyapunov solver
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options_mom_ = set_default_option(options_mom_,'lyapunov_doubling_tol',1e-16); % convergence criterion used in the doubling algorithm
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% mode check plot
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options_mom_.mode_check.nolik = false; % we don't do likelihood (also this initializes mode_check substructure)
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options_mom_.mode_check = set_default_option(options_mom_.mode_check,'status',false); % plot the target function for values around the computed minimum for each estimated parameter in turn. This is helpful to diagnose problems with the optimizer.
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options_mom_.mode_check = set_default_option(options_mom_.mode_check,'neighbourhood_size',.5); % width of the window around the computed minimum to be displayed on the diagnostic plots. This width is expressed in percentage deviation. The Inf value is allowed, and will trigger a plot over the entire domain
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options_mom_.mode_check = set_default_option(options_mom_.mode_check,'symmetric_plots',true); % ensure that the check plots are symmetric around the minimum. A value of 0 allows to have asymmetric plots, which can be useful if the minimum is close to a domain boundary, or in conjunction with neighbourhood_size = Inf when the domain is not the entire real line
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options_mom_.mode_check = set_default_option(options_mom_.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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% OPTIONS THAT NEED TO BE CARRIED OVER (E.G. SET BY THE PREPROCESSOR)
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% -------------------------------------------------------------------------
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% related to VAROBS block
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options_mom_.varobs = options_.varobs; % observable variables in order they are declared in varobs
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options_mom_.varobs_id = options_.varobs_id; % index for observable variables in M_.endo_names
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options_mom_.obs_nbr = length(options_mom_.varobs); % number of observed variables
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% related to call of dynare
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options_mom_.console_mode = options_.console_mode;
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options_mom_.parallel = options_.parallel;
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options_mom_.parallel_info = options_.parallel_info;
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% related to estimated_params and estimated_params_init blocks
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options_mom_.use_calibration_initialization = options_.use_calibration_initialization;
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% related to model block
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options_mom_.linear = options_.linear;
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options_mom_.use_dll = options_.use_dll;
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options_mom_.block = options_.block;
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options_mom_.bytecode = options_.bytecode;
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% related to steady-state computations
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options_mom_.homotopy_force_continue = options_.homotopy_force_continue;
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options_mom_.homotopy_mode = options_.homotopy_mode;
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options_mom_.homotopy_steps = options_.homotopy_steps;
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options_mom_.markowitz = options_.markowitz;
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options_mom_.solve_algo = options_.solve_algo;
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options_mom_.solve_tolf = options_.solve_tolf;
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options_mom_.solve_tolx = options_.solve_tolx;
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options_mom_.steady = options_.steady;
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options_mom_.steadystate = options_.steadystate;
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options_mom_.steadystate_flag = options_.steadystate_flag;
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options_mom_.threads = options_.threads; % needed by resol
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options_mom_.debug = options_.debug; % debug option needed by some functions, e.g. check_plot
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% random numbers
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options_mom_.DynareRandomStreams.seed = options_.DynareRandomStreams.seed;
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options_mom_.DynareRandomStreams.algo = options_.DynareRandomStreams.algo;
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% dataset_ related
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options_mom_.dataset = options_.dataset;
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options_mom_.initial_period = options_.initial_period;
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% optimization related
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if any(cellfun(@(x) isnumeric(x) && any(x == 2), options_mom_.optimizer_vec)) % simulated annealing (mode_compute=2)
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options_mom_.saopt = options_.saopt;
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end
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if any(cellfun(@(x) isnumeric(x) && any(x == 4), options_mom_.optimizer_vec)) % csminwel (mode_compute=4)
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options_mom_.csminwel = options_.csminwel;
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end
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if any(cellfun(@(x) isnumeric(x) && any(x == 5), options_mom_.optimizer_vec)) % newrat (mode_compute=5)
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options_mom_.newrat = options_.newrat;
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end
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if any(cellfun(@(x) isnumeric(x) && any(x == 6), options_mom_.optimizer_vec)) % gmhmaxlik (mode_compute=6)
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options_mom_.gmhmaxlik = options_.gmhmaxlik;
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options_mom_.mh_jscale = options_.mh_jscale;
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end
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if any(cellfun(@(x) isnumeric(x) && any(x == 8), options_mom_.optimizer_vec)) % simplex variation on Nelder Mead algorithm (mode_compute=8)
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options_mom_.simplex = options_.simplex;
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end
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if any(cellfun(@(x) isnumeric(x) && any(x == 9), options_mom_.optimizer_vec)) % cmaes (mode_compute=9)
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options_mom_.cmaes = options_.cmaes;
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end
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if any(cellfun(@(x) isnumeric(x) && any(x == 10), options_mom_.optimizer_vec)) % simpsa (mode_compute=10)
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options_mom_.simpsa = options_.simpsa;
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end
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if any(cellfun(@(x) isnumeric(x) && any(x == 12), options_mom_.optimizer_vec)) % particleswarm (mode_compute=12)
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options_mom_.particleswarm = options_.particleswarm;
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end
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if any(cellfun(@(x) isnumeric(x) && any(x == 101), options_mom_.optimizer_vec)) % solveopt (mode_compute=101)
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options_mom_.solveopt = options_.solveopt;
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end
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if any(cellfun(@(x) isnumeric(x) && (any(x == 4) || any(x == 5)), options_mom_.optimizer_vec)) % used by csminwel and newrat
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options_mom_.gradient_method = options_.gradient_method;
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options_mom_.gradient_epsilon = options_.gradient_epsilon;
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end
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options_mom_.gstep = options_.gstep; % needed by hessian.m
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options_mom_.trust_region_initial_step_bound_factor = options_.trust_region_initial_step_bound_factor; % used in dynare_solve for trust_region
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% other
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options_mom_.MaxNumberOfBytes = options_.MaxNumberOfBytes;
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%options_mom_.MaximumNumberOfMegaBytes = options_.MaximumNumberOfMegaBytes;
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% -------------------------------------------------------------------------
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% DEFAULT VALUES
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% -------------------------------------------------------------------------
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options_mom_.analytic_derivation = 0;
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options_mom_.analytic_derivation_mode = 0; % needed by get_perturbation_params_derivs.m, ie use efficient sylvester equation method to compute analytical derivatives as in Ratto & Iskrev (2012)
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options_mom_.initialize_estimated_parameters_with_the_prior_mode = 0; % needed by set_prior.m
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options_mom_.figures = options_.figures; % needed by plot_priors.m
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options_mom_.ramsey_policy = false; % needed by evaluate_steady_state
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options_mom_.risky_steadystate = false; % needed by resol
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options_mom_.jacobian_flag = true; % needed by dynare_solve |