Merge branch 'master' into remove-dynDate-class
Conflicts: preprocessor/DynareBison.yytime-shift
Stéphane Adjemian (Penelope)
commit
0c00151092
|
|
@ -827,12 +827,14 @@ Allows Dynare to issue a warning and continue processing when
|
|||
@outputhead
|
||||
|
||||
Depending on the computing tasks requested in the @file{.mod} file,
|
||||
executing command @code{dynare} will leave in the workspace variables
|
||||
containing results available for further processing. More details are
|
||||
given under the relevant computing tasks.
|
||||
executing the @code{dynare} command will leave variables containing
|
||||
results in the workspace available for further processing. More
|
||||
details are given under the relevant computing tasks.
|
||||
|
||||
The @code{M_}, @code{oo_} and @code{options_} structures are also saved
|
||||
in a file called @file{@var{FILENAME}_results.mat}.
|
||||
The @code{M_}, @code{oo_}, and @code{options_} structures are saved in
|
||||
a file called @file{@var{FILENAME}_results.mat}. If they exist,
|
||||
@code{estim_params_}, @code{bayestopt_}, @code{dataset_}, and
|
||||
@code{estimation_info} are saved in the same file.
|
||||
|
||||
@examplehead
|
||||
|
||||
|
|
@ -3358,6 +3360,10 @@ The exogenous variables for which to compute IRFs. Default: all.
|
|||
Requests the computation of normalized IRFs in percentage of the
|
||||
standard error of each shock.
|
||||
|
||||
@item irf_plot_threshold = @var{DOUBLE}
|
||||
@anchor{irf_plot_threshold}
|
||||
Threshold size for plotting IRFs. All IRFs for a particular variable with a maximum absolute deviation from the steady state smaller than this value are not displayed. Default: @code{1e-10}.
|
||||
|
||||
@item nocorr
|
||||
Don't print the correlation matrix (printing them is the default).
|
||||
|
||||
|
|
@ -4201,9 +4207,10 @@ end;
|
|||
@end deffn
|
||||
|
||||
@deffn Block estimated_params_init ;
|
||||
@deffnx Block estimated_params_init (@var{OPTIONS}@dots{});
|
||||
|
||||
This block declares numerical initial values for the optimizer when
|
||||
these ones are different from the prior mean.
|
||||
these ones are different from the prior mean. It should be specified after the @code{estimated_params}-block as otherwise the specified starting values are overwritten by the latter.
|
||||
|
||||
Each line has the following syntax:
|
||||
|
||||
|
|
@ -4212,6 +4219,14 @@ stderr VARIABLE_NAME | corr VARIABLE_NAME_1, VARIABLE_NAME_2 | PARAMETER_NAME
|
|||
, INITIAL_VALUE;
|
||||
@end example
|
||||
|
||||
@optionshead
|
||||
|
||||
@table @code
|
||||
|
||||
@item use_calibration
|
||||
For not specifically intialized parameters, use the deep parameters and the elements of the covariance matrix specified in the @code{shocks}-block from calibration as starting values for estimation. For components of the @code{shocks}-block that were not explicitly specified during calibration or which violate the prior, the prior mean is used.
|
||||
@end table
|
||||
|
||||
@xref{estimated_params}, for the meaning and syntax of the various components.
|
||||
|
||||
@end deffn
|
||||
|
|
@ -4896,6 +4911,9 @@ using a standard Kalman filter.
|
|||
@xref{irf_shocks}. Only used if @ref{bayesian_irf} is passed. Cannot be used
|
||||
with @ref{dsge_var}.
|
||||
|
||||
@item irf_plot_threshold = @var{DOUBLE}
|
||||
@xref{irf_plot_threshold}. Only used if @ref{bayesian_irf} is passed.
|
||||
|
||||
@item aim_solver
|
||||
@xref{aim_solver}.
|
||||
|
||||
|
|
@ -7058,11 +7076,14 @@ The total number of draws is equal to
|
|||
Tuning period for Metropolis-Hasting draws. Default: @code{30,000}
|
||||
|
||||
@item save_draws
|
||||
Save all elements of @math{A^0}, @math{A^+}, @math{\xi}, and the
|
||||
transition matrix to a file named @code{draws_<<file_tag>>.out} with
|
||||
each draw on a separate line. A file that describes how these matrices
|
||||
are laid out is contained in
|
||||
@code{draws_header_<<file_tag>>.out}. Default: @code{off}
|
||||
Save all elements of @math{A^0}, @math{A^+}, @math{Q}, and
|
||||
@math{\zeta}, to a file named @code{draws_<<file_tag>>.out} with each
|
||||
draw on a separate line. A file that describes how these matrices are
|
||||
laid out is contained in @code{draws_header_<<file_tag>>.out}. A file
|
||||
called @code{load_flat_file.m} is provided to simplify loading the
|
||||
saved files into the corresponding variables @code{A0}, @code{Aplus},
|
||||
@code{Q}, and @code{Zeta} in your MATLAB/Octave workspace. Default:
|
||||
@code{off}
|
||||
|
||||
@end table
|
||||
@end deffn
|
||||
|
|
|
|||
|
|
@ -404,7 +404,7 @@ if options_.TeX
|
|||
TEXNAMES = [];
|
||||
|
||||
for j=1:nvar
|
||||
if max(abs(MeanIRF(:,j,i))) > 10^(-6)
|
||||
if max(abs(MeanIRF(:,j,i))) > options_.impulse_responses.plot_threshold
|
||||
|
||||
name = deblank(varlist(j,:));
|
||||
texname = deblank(varlist_TeX(j,:));
|
||||
|
|
|
|||
|
|
@ -1,6 +1,7 @@
|
|||
function myoutput=PosteriorIRF_core1(myinputs,fpar,B,whoiam, ThisMatlab)
|
||||
% Generates and stores Posterior IRFs
|
||||
% PARALLEL CONTEXT
|
||||
% This function perfom in parallel a portion of PosteriorIRF.m code.
|
||||
% This function perfoms in parallel execution a portion of the PosteriorIRF.m code.
|
||||
% This is a special kind of parallel function. Unlike of other parallel functions,
|
||||
% that running in parallel a 'for' cycle, this function run in parallel a
|
||||
% 'while' loop! The parallelization of 'while' loop (when possible) is a more
|
||||
|
|
|
|||
|
|
@ -1,6 +1,8 @@
|
|||
function myoutput=PosteriorIRF_core2(myinputs,fpar,npar,whoiam, ThisMatlab)
|
||||
% Generates the Posterior IRFs plot from the IRFs generated in
|
||||
% PosteriorIRF_core1
|
||||
% PARALLEL CONTEXT
|
||||
% Perfome in parallel a portion of PosteriorIRF.m code.
|
||||
% Perform in parallel execution a portion of the PosteriorIRF.m code.
|
||||
% See also the comment in random_walk_metropolis_hastings_core.m funtion.
|
||||
%
|
||||
% INPUTS
|
||||
|
|
@ -17,7 +19,7 @@ function myoutput=PosteriorIRF_core2(myinputs,fpar,npar,whoiam, ThisMatlab)
|
|||
% SPECIAL REQUIREMENTS.
|
||||
% None.
|
||||
%
|
||||
% Copyright (C) 2006-2012 Dynare Team
|
||||
% Copyright (C) 2006-2013 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
|
|
@ -87,7 +89,7 @@ for i=fpar:npar,
|
|||
figunumber = 0;
|
||||
|
||||
for j=1:nvar
|
||||
if max(abs(MeanIRF(:,j,i))) > 10^(-6)
|
||||
if max(abs(MeanIRF(:,j,i))) > options_.impulse_responses.plot_threshold
|
||||
subplotnum = subplotnum+1;
|
||||
if subplotnum == 1 && options_.relative_irf
|
||||
hh = dyn_figure(options_,'Name',['Relative response to orthogonalized shock to ' tit(i,:)]);
|
||||
|
|
@ -131,6 +133,10 @@ for i=fpar:npar,
|
|||
end
|
||||
name = deblank(varlist(j,:));
|
||||
title(name,'Interpreter','none')
|
||||
else
|
||||
if options_.debug
|
||||
fprintf('POSTERIOR_IRF: The IRF of %s to %s is smaller than the irf_plot_threshold of %4.3f and will not be displayed.\n',deblank(varlist(j,:)),tit(i,:),options_.impulse_responses.plot_threshold)
|
||||
end
|
||||
end
|
||||
|
||||
if subplotnum == MaxNumberOfPlotPerFigure || (j == nvar && subplotnum> 0)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,51 @@
|
|||
function check_prior_bounds(xparam1,bounds,M_,estim_params_,options_,bayestopt_)
|
||||
% function check_prior_bounds(xparam1,bounds,M_,estim_params_,options_)
|
||||
% checks the parameter vector of violations of the prior bounds
|
||||
% Inputs:
|
||||
% -xparam1 [double] vector of parameters to be estimated (initial values)
|
||||
% -bounds [vector] vector containing the lower and upper
|
||||
% bounds
|
||||
% -M_ [structure] characterizing the model.
|
||||
% -estim_params_ [structure] characterizing parameters to be estimated
|
||||
% -options_ [structure] characterizing the options
|
||||
% -bayestopt_ [structure] characterizing priors
|
||||
|
||||
% Copyright (C) 2013 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
% Dynare is free software: you can redistribute it and/or modify
|
||||
% it under the terms of the GNU General Public License as published by
|
||||
% the Free Software Foundation, either version 3 of the License, or
|
||||
% (at your option) any later version.
|
||||
%
|
||||
% Dynare is distributed in the hope that it will be useful,
|
||||
% but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
% GNU General Public License for more details.
|
||||
%
|
||||
% You should have received a copy of the GNU General Public License
|
||||
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
outside_bound_pars=find(xparam1 < bounds(:,1) | xparam1 > bounds(:,2));
|
||||
if ~isempty(outside_bound_pars)
|
||||
for ii=1:length(outside_bound_pars)
|
||||
outside_bound_par_names{ii,1}=get_the_name(outside_bound_pars(ii),0,M_,estim_params_,options_);
|
||||
end
|
||||
disp_string=[outside_bound_par_names{1,:}];
|
||||
for ii=2:size(outside_bound_par_names,1)
|
||||
disp_string=[disp_string,', ',outside_bound_par_names{ii,:}];
|
||||
end
|
||||
error(['Initial value(s) of ', disp_string ,' are outside parameter bounds. Potentially, you should set prior_trunc=0. If you used the mode_file-option, check whether your mode-file is consistent with the priors.'])
|
||||
end
|
||||
inadmissible_inverse_gamma_values=find(bayestopt_.pshape==4 & xparam1 == 0);
|
||||
if ~isempty(inadmissible_inverse_gamma_values)
|
||||
for ii=1:length(inadmissible_inverse_gamma_values)
|
||||
inadmissible_inverse_gamma_par_names{ii,1}=get_the_name(inadmissible_inverse_gamma_values(ii),0,M_,estim_params_,options_);
|
||||
end
|
||||
disp_string=[inadmissible_inverse_gamma_par_names{1,:}];
|
||||
for ii=2:size(inadmissible_inverse_gamma_par_names,1)
|
||||
disp_string=[disp_string,', ',inadmissible_inverse_gamma_par_names{ii,:}];
|
||||
end
|
||||
error(['Initial value(s) of ', disp_string ,' is zero. This is not allowed when using an inverse gamma prior.\n'])
|
||||
end
|
||||
|
|
@ -0,0 +1,143 @@
|
|||
function [xparam1,estim_params_,xparam1_explicitly_initialized,xparam1_properly_calibrated]=do_parameter_initialization(estim_params_,xparam1_calib,xparam1_NaN_set_to_prior_mean)
|
||||
% function [xparam1,estim_params_]=get_initialized_parameters(estim_params_,xparam1_calib)
|
||||
% gets explicitly initialized variables and properly calibrated parameters
|
||||
%
|
||||
% INPUTS
|
||||
% o estim_params_ [structure] characterizing parameters to be estimated.
|
||||
% o xparam1_calib [double] vector of parameters to be estimated, with parameters
|
||||
% initialized from calibration using get_all_parameters
|
||||
%
|
||||
% o xparam1_NaN_set_to_prior_mean [double] vector of parameters to be estimated, with parameters
|
||||
% initialized using dynare_estimation_init; not explicitly initialized
|
||||
% parameters are at prior mean
|
||||
% OUTPUTS
|
||||
% o xparam1 [double] vector of initialized parameters; uses the hierarchy: 1) explicitly initialized parameters,
|
||||
% 2) calibrated parameters, 3) prior mean
|
||||
% o estim_params_ [structure] characterizing parameters to be estimated; it is
|
||||
% updated here to reflect calibrated parameters
|
||||
% o xparam1_explicitly_initialized [double] vector of parameters to be estimated that
|
||||
% were explicitly initialized
|
||||
% o xparam1_properly_calibrated [double] vector of parameters to be estimated that
|
||||
% were properly calibrated
|
||||
%
|
||||
% SPECIAL REQUIREMENTS
|
||||
% None
|
||||
|
||||
% Copyright (C) 2013 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
% Dynare is free software: you can redistribute it and/or modify
|
||||
% it under the terms of the GNU General Public License as published by
|
||||
% the Free Software Foundation, either version 3 of the License, or
|
||||
% (at your option) any later version.
|
||||
%
|
||||
% Dynare is distributed in the hope that it will be useful,
|
||||
% but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
% GNU General Public License for more details.
|
||||
%
|
||||
% You should have received a copy of the GNU General Public License
|
||||
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
nvx = size(estim_params_.var_exo,1);
|
||||
nvn = size(estim_params_.var_endo,1);
|
||||
ncx = size(estim_params_.corrx,1);
|
||||
ncn = size(estim_params_.corrn,1);
|
||||
np = size(estim_params_.param_vals,1);
|
||||
|
||||
estim_params_.nvx = nvx; %exogenous shock variances
|
||||
estim_params_.nvn = nvn; %endogenous variances, i.e. measurement error
|
||||
estim_params_.ncx = ncx; %exogenous shock correlations
|
||||
estim_params_.ncn = ncn; % correlation between endogenous variables, i.e. measurement error.
|
||||
estim_params_.np = np; % other parameters of the model
|
||||
|
||||
xparam1_explicitly_initialized = NaN(nvx+nvn+ncx+ncn+np,1);
|
||||
xparam1_properly_calibrated = NaN(nvx+nvn+ncx+ncn+np,1);
|
||||
|
||||
offset=0;
|
||||
if nvx
|
||||
initialized_par_index=find(~isnan(estim_params_.var_exo(:,2)));
|
||||
calibrated_par_index=find(isnan(estim_params_.var_exo(:,2)) & ~isnan(xparam1_calib(offset+1:offset+nvx,1)));
|
||||
uninitialized_par_index=find(isnan(estim_params_.var_exo(:,2)) & isnan(xparam1_calib(offset+1:offset+nvx,1)));
|
||||
xparam1_explicitly_initialized(offset+initialized_par_index,1) = estim_params_.var_exo(initialized_par_index,2);
|
||||
%update estim_params_ with calibrated starting values
|
||||
estim_params_.var_exo(calibrated_par_index,2)=xparam1_calib(offset+calibrated_par_index,1);
|
||||
%find parameters that are calibrated and do not violate inverse gamma prior
|
||||
xparam1_properly_calibrated(offset+calibrated_par_index,1) = xparam1_calib(offset+calibrated_par_index,1);
|
||||
inv_gamma_violation=find(estim_params_.var_exo(calibrated_par_index,2)==0 & estim_params_.var_exo(calibrated_par_index,4)==0);
|
||||
if inv_gamma_violation
|
||||
estim_params_.var_exo(calibrated_par_index(inv_gamma_violation),2)=NaN;
|
||||
xparam1_properly_calibrated(offset+calibrated_par_index(inv_gamma_violation),1)=NaN;
|
||||
fprintf('PARAMETER INITIALIZATION: Some standard deviations of shocks of the calibrated model are 0 and\n')
|
||||
fprintf('PARAMETER INITIALIZATION: violate the inverse gamma prior. They will instead be initialized with the prior mean.\n')
|
||||
end
|
||||
if uninitialized_par_index
|
||||
fprintf('PARAMETER INITIALIZATION: Warning, some estimated standard deviations of shocks are not\n')
|
||||
fprintf('PARAMETER INITIALIZATION: initialized. They will be initialized with the prior mean.\n')
|
||||
end
|
||||
end
|
||||
offset=offset+nvx;
|
||||
if nvn
|
||||
initialized_par_index=find(~isnan(estim_params_.var_endo(:,2)));
|
||||
calibrated_par_index=find(isnan(estim_params_.var_endo(:,2)) & ~isnan(xparam1_calib(offset+1:offset+nvn,1)));
|
||||
uninitialized_par_index=find(isnan(estim_params_.var_endo(:,2)) & isnan(xparam1_calib(offset+1:offset+nvn,1)));
|
||||
xparam1_explicitly_initialized(offset+initialized_par_index,1) = estim_params_.var_endo(initialized_par_index,2);
|
||||
estim_params_.var_endo(calibrated_par_index,2)=xparam1_calib(offset+calibrated_par_index,1);
|
||||
%find parameters that are calibrated and do not violate inverse gamma prior
|
||||
xparam1_properly_calibrated(offset+calibrated_par_index,1) = xparam1_calib(offset+calibrated_par_index,1);
|
||||
inv_gamma_violation=find(estim_params_.var_endo(calibrated_par_index,2)==0 & estim_params_.var_endo(calibrated_par_index,5)==4);
|
||||
if inv_gamma_violation
|
||||
estim_params_.var_endo(calibrated_par_index(inv_gamma_violation),2)=NaN;
|
||||
xparam1_properly_calibrated(offset+calibrated_par_index(inv_gamma_violation),1)=NaN;
|
||||
fprintf('PARAMETER INITIALIZATION: Some measurement errors of the calibrated model are 0 and violate the\n')
|
||||
fprintf('PARAMETER INITIALIZATION: inverse gamma prior. They will instead be initialized with the prior mean.\n')
|
||||
end
|
||||
if uninitialized_par_index
|
||||
fprintf('PARAMETER INITIALIZATION: Warning, some measurement errors are not initialized. They will be initialized\n')
|
||||
fprintf('PARAMETER INITIALIZATION: with the prior mean.\n')
|
||||
end
|
||||
end
|
||||
offset=offset+nvn;
|
||||
if ncx
|
||||
initialized_par_index=find(~isnan(estim_params_.corrx(:,3)));
|
||||
calibrated_par_index=find(isnan(estim_params_.corrx(:,3)) & ~isnan(xparam1_calib(offset+1:offset+ncx,1)));
|
||||
uninitialized_par_index=find(isnan(estim_params_.corrx(:,3)) & isnan(xparam1_calib(offset+1:offset+ncx,1)));
|
||||
xparam1_explicitly_initialized(offset+initialized_par_index,1) = estim_params_.corrx(initialized_par_index,3);
|
||||
estim_params_.corrx(calibrated_par_index,3)=xparam1_calib(offset+calibrated_par_index,1);
|
||||
xparam1_properly_calibrated(offset+calibrated_par_index,1) = xparam1_calib(offset+calibrated_par_index,1);
|
||||
if uninitialized_par_index
|
||||
fprintf('PARAMETER INITIALIZATION: Warning, some correlations between structural shocks are not initialized.\n')
|
||||
fprintf('PARAMETER INITIALIZATION: They will be initialized with the prior mean.\n')
|
||||
end
|
||||
end
|
||||
offset=offset+ncx;
|
||||
if ncn
|
||||
initialized_par_index=find(~isnan(estim_params_.corrn(:,3)));
|
||||
calibrated_par_index=find(isnan(estim_params_.corrn(:,3)) & ~isnan(xparam1_calib(offset+1:offset+ncn,1)));
|
||||
uninitialized_par_index=find(isnan(estim_params_.corrn(:,3)) & isnan(xparam1_calib(offset+1:offset+ncn,1)));
|
||||
xparam1_explicitly_initialized(offset+initialized_par_index,1) = estim_params_.corrn(initialized_par_index,3);
|
||||
estim_params_.corrn(calibrated_par_index,3)=xparam1_calib(offset+calibrated_par_index,1);
|
||||
xparam1_properly_calibrated(offset+calibrated_par_index,1) = xparam1_calib(offset+calibrated_par_index,1);
|
||||
if uninitialized_par_index
|
||||
fprintf('PARAMETER INITIALIZATION: Warning, some correlations between measurement errors are not initialized.\n')
|
||||
fprintf('PARAMETER INITIALIZATION: They will be initialized with the prior mean.\n')
|
||||
end
|
||||
end
|
||||
offset=offset+ncn;
|
||||
if np
|
||||
initialized_par_index=find(~isnan(estim_params_.param_vals(:,2)));
|
||||
calibrated_par_index=find(isnan(estim_params_.param_vals(:,2)) & ~isnan(xparam1_calib(offset+1:offset+np,1)));
|
||||
uninitialized_par_index=find(isnan(estim_params_.param_vals(:,2)) & isnan(xparam1_calib(offset+1:offset+np,1)));
|
||||
xparam1_explicitly_initialized(offset+initialized_par_index,1) = estim_params_.param_vals(initialized_par_index,2);
|
||||
estim_params_.param_vals(calibrated_par_index,2)=xparam1_calib(offset+calibrated_par_index,1);
|
||||
xparam1_properly_calibrated(offset+calibrated_par_index,1) = xparam1_calib(offset+calibrated_par_index,1);
|
||||
if uninitialized_par_index
|
||||
fprintf('PARAMETER INITIALIZATION: Warning, some deep parameters are not initialized. They will be\n')
|
||||
fprintf('PARAMETER INITIALIZATION: initialized with the prior mean.\n')
|
||||
end
|
||||
end
|
||||
xparam1=xparam1_explicitly_initialized;
|
||||
xparam1(isnan(xparam1))=xparam1_properly_calibrated(isnan(xparam1)); %set not explicitly initialized parameters that do not obviously violate prior distribution to calibrated parameter values
|
||||
xparam1(isnan(xparam1))=xparam1_NaN_set_to_prior_mean(isnan(xparam1)); %set not yet initialized parameters to prior mean coming from dynare_estimation_init
|
||||
|
||||
|
|
@ -84,6 +84,25 @@ end
|
|||
if ~isempty(estim_params_)
|
||||
estim_params_=check_for_calibrated_covariances(xparam1,estim_params_,M_);
|
||||
end
|
||||
|
||||
%%read out calibration that was set in mod-file and can be used for initialization
|
||||
xparam1_calib=get_all_parameters(estim_params_,M_); %get calibrated parameters
|
||||
if ~any(isnan(xparam1_calib)) %all estimated parameters are calibrated
|
||||
full_calibration_detected=1;
|
||||
else
|
||||
full_calibration_detected=0;
|
||||
end
|
||||
if options_.use_calibration_initialization %set calibration as starting values
|
||||
[xparam1,estim_params_]=do_parameter_initialization(estim_params_,xparam1_calib,xparam1); %get explicitly initialized parameters that have precedence to calibrated values
|
||||
try
|
||||
check_prior_bounds(xparam1,[bayestopt_.lb bayestopt_.ub],M_,estim_params_,options_,bayestopt_); %check whether calibration satisfies prior bounds
|
||||
catch
|
||||
e = lasterror();
|
||||
fprintf('Cannot use parameter values from calibration as they violate the prior bounds.')
|
||||
rethrow(e);
|
||||
end
|
||||
end
|
||||
|
||||
% Set sigma_e_is_diagonal flag (needed if the shocks block is not declared in the mod file).
|
||||
M_.sigma_e_is_diagonal = 1;
|
||||
if estim_params_.ncx || any(nnz(tril(M_.Correlation_matrix,-1))) || isfield(estim_params_,'calibrated_covariances')
|
||||
|
|
@ -152,7 +171,21 @@ if options_.dsge_var
|
|||
end
|
||||
|
||||
|
||||
oo_ = initial_estimation_checks(objective_function,xparam1,dataset_,M_,estim_params_,options_,bayestopt_,oo_);
|
||||
%% perform initial estimation checks;
|
||||
try
|
||||
oo_ = initial_estimation_checks(objective_function,xparam1,dataset_,M_,estim_params_,options_,bayestopt_,oo_);
|
||||
catch % if check fails, provide info on using calibration if present
|
||||
e = lasterror();
|
||||
if full_calibration_detected %calibrated model present and no explicit starting values
|
||||
skipline(1);
|
||||
fprintf('ESTIMATION_CHECKS: There was an error in computing the likelihood for initial parameter values.\n')
|
||||
fprintf('ESTIMATION_CHECKS: You should try using the calibrated version of the model as starting values. To do\n')
|
||||
fprintf('ESTIMATION_CHECKS: this, add an empty estimated_params_init-block with use_calibration option immediately before the estimation\n')
|
||||
fprintf('ESTIMATION_CHECKS: command (and after the estimated_params-block so that it does not get overwritten):\n');
|
||||
skipline(2);
|
||||
end
|
||||
rethrow(e);
|
||||
end
|
||||
|
||||
if isequal(options_.mode_compute,0) && isempty(options_.mode_file) && options_.mh_posterior_mode_estimation==0
|
||||
if options_.smoother == 1
|
||||
|
|
|
|||
|
|
@ -242,28 +242,7 @@ if ~isempty(estim_params_)
|
|||
bounds(:,2) = ub;
|
||||
end
|
||||
% Test if initial values of the estimated parameters are all between the prior lower and upper bounds.
|
||||
outside_bound_pars=find(xparam1 < bounds(:,1) | xparam1 > bounds(:,2));
|
||||
if ~isempty(outside_bound_pars)
|
||||
for ii=1:length(outside_bound_pars)
|
||||
outside_bound_par_names{ii,1}=get_the_name(outside_bound_pars(ii),0,M_,estim_params_,options_);
|
||||
end
|
||||
disp_string=[outside_bound_par_names{1,:}];
|
||||
for ii=2:size(outside_bound_par_names,1)
|
||||
disp_string=[disp_string,', ',outside_bound_par_names{ii,:}];
|
||||
end
|
||||
error(['Initial value(s) of ', disp_string ,' are outside parameter bounds. Potentially, you should set prior_trunc=0. If you used the mode_file-option, check whether your mode-file is consistent with the priors.'])
|
||||
end
|
||||
inadmissible_inverse_gamma_values=find(bayestopt_.pshape==4 & xparam1 == 0);
|
||||
if ~isempty(inadmissible_inverse_gamma_values)
|
||||
for ii=1:length(inadmissible_inverse_gamma_values)
|
||||
inadmissible_inverse_gamma_par_names{ii,1}=get_the_name(inadmissible_inverse_gamma_values(ii),0,M_,estim_params_,options_);
|
||||
end
|
||||
disp_string=[inadmissible_inverse_gamma_par_names{1,:}];
|
||||
for ii=2:size(inadmissible_inverse_gamma_par_names,1)
|
||||
disp_string=[disp_string,', ',inadmissible_inverse_gamma_par_names{ii,:}];
|
||||
end
|
||||
error(['Initial value(s) of ', disp_string ,' is zero. This is not allowed when using an inverse gamma prior.\n'])
|
||||
end
|
||||
check_prior_bounds(xparam1,bounds,M_,estim_params_,options_,bayestopt_)
|
||||
|
||||
lb = bounds(:,1);
|
||||
ub = bounds(:,2);
|
||||
|
|
|
|||
|
|
@ -0,0 +1,96 @@
|
|||
function xparam1=get_all_parameters(estim_params_,M_)
|
||||
|
||||
% function xparam1=get_parameters
|
||||
% gets parameters values from M_.params into xparam1 (inverse mapping to set_all_parameters)
|
||||
% This is called if a model was calibrated before estimation to back out
|
||||
% parameter values
|
||||
%
|
||||
% INPUTS
|
||||
% estim_params_: Dynare structure describing the estimated parameters.
|
||||
% M_: Dynare structure describing the model.
|
||||
%
|
||||
% OUTPUTS
|
||||
% xparam1: N*1 double vector of parameters from calibrated model that are to be estimated
|
||||
%
|
||||
% SPECIAL REQUIREMENTS
|
||||
% none
|
||||
|
||||
% Copyright (C) 2013 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
% Dynare is free software: you can redistribute it and/or modify
|
||||
% it under the terms of the GNU General Public License as published by
|
||||
% the Free Software Foundation, either version 3 of the License, or
|
||||
% (at your option) any later version.
|
||||
%
|
||||
% Dynare is distributed in the hope that it will be useful,
|
||||
% but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
% GNU General Public License for more details.
|
||||
%
|
||||
% You should have received a copy of the GNU General Public License
|
||||
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
nvx = estim_params_.nvx;
|
||||
ncx = estim_params_.ncx;
|
||||
nvn = estim_params_.nvn;
|
||||
ncn = estim_params_.ncn;
|
||||
np = estim_params_.np;
|
||||
Sigma_e = M_.Sigma_e;
|
||||
Correlation_matrix = M_.Correlation_matrix;
|
||||
H = M_.H;
|
||||
Correlation_matrix_ME = M_.Correlation_matrix_ME;
|
||||
|
||||
xparam1=NaN(nvx+ncx+nvn+ncn+np,1);
|
||||
% stderrs of the exogenous shocks
|
||||
if nvx
|
||||
var_exo = estim_params_.var_exo;
|
||||
for i=1:nvx
|
||||
k = var_exo(i,1);
|
||||
xparam1(i)=sqrt(Sigma_e(k,k));
|
||||
end
|
||||
end
|
||||
% update offset
|
||||
offset = nvx;
|
||||
|
||||
% setting measument error variance
|
||||
if nvn
|
||||
for i=1:nvn
|
||||
k = estim_params_.nvn_observable_correspondence(i,1);
|
||||
xparam1(offset+i)=sqrt(H(k,k));
|
||||
end
|
||||
end
|
||||
|
||||
% update offset
|
||||
offset = nvx+nvn;
|
||||
|
||||
% correlations among shocks (ncx)
|
||||
if ncx
|
||||
corrx = estim_params_.corrx;
|
||||
for i=1:ncx
|
||||
k1 = corrx(i,1);
|
||||
k2 = corrx(i,2);
|
||||
xparam1(i+offset)=Correlation_matrix(k1,k2);
|
||||
end
|
||||
end
|
||||
% update offset
|
||||
offset = nvx+nvn+ncx;
|
||||
|
||||
if ncn
|
||||
corrn_observable_correspondence = estim_params_.corrn_observable_correspondence;
|
||||
for i=1:ncn
|
||||
k1 = corrn_observable_correspondence(i,1);
|
||||
k2 = corrn_observable_correspondence(i,2);
|
||||
xparam1(i+offset)=Correlation_matrix_ME(k1,k2);
|
||||
end
|
||||
end
|
||||
|
||||
% update offset
|
||||
offset = nvx+ncx+nvn+ncn;
|
||||
|
||||
|
||||
% structural parameters
|
||||
if np
|
||||
xparam1(offset+1:end)=M_.params(estim_params_.param_vals(:,1));
|
||||
end
|
||||
|
|
@ -140,6 +140,7 @@ end
|
|||
|
||||
% IRFs & other stoch_simul output
|
||||
options_.irf = 40;
|
||||
options_.impulse_responses.plot_threshold=1e-10;
|
||||
options_.relative_irf = 0;
|
||||
options_.ar = 5;
|
||||
options_.hp_filter = 0;
|
||||
|
|
@ -382,6 +383,7 @@ options_.mh_recover = 0;
|
|||
options_.mh_replic = 20000;
|
||||
options_.recursive_estimation_restart = 0;
|
||||
options_.MCMC_jumping_covariance='hessian';
|
||||
options_.use_calibration_initialization = 0;
|
||||
|
||||
options_.mode_compute = 4;
|
||||
options_.mode_file = '';
|
||||
|
|
|
|||
|
|
@ -263,7 +263,8 @@ if fload==0,
|
|||
if prepSA,
|
||||
try
|
||||
T=zeros(size(dr_.ghx,1),size(dr_.ghx,2)+size(dr_.ghu,2),Nsam);
|
||||
catch ME
|
||||
catch
|
||||
ME = lasterror();
|
||||
if strcmp('MATLAB:nomem',ME.identifier),
|
||||
prepSA=0;
|
||||
disp('The model is too large for storing state space matrices ...')
|
||||
|
|
|
|||
|
|
@ -146,8 +146,8 @@ for b=1:nb
|
|||
end
|
||||
end
|
||||
if singularity_problem
|
||||
fprint('The presence of a singularity problem typically indicates that there is one\n')
|
||||
fprint('redundant equation entered in the model block, while another non-redundant equation\n')
|
||||
fprint('is missing. The problem often derives from Walras Law.\n')
|
||||
fprintf('The presence of a singularity problem typically indicates that there is one\n')
|
||||
fprintf('redundant equation entered in the model block, while another non-redundant equation\n')
|
||||
fprintf('is missing. The problem often derives from Walras Law.\n')
|
||||
end
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,71 @@
|
|||
function [Q, A0, Aplus, Zeta] = load_flat_file(file_tag)
|
||||
%function [Q, A0, Aplus, Zeta] = load_flat_file(file_tag)
|
||||
% Loads file saved by save_draws option of ms_simulation.
|
||||
%
|
||||
% INPUTS
|
||||
% file_tag: the file tag used with ms_simulation
|
||||
%
|
||||
% OUTPUTS
|
||||
% Q: Q matrix
|
||||
% A0: A0 matrix
|
||||
% Aplus: A+ matrix
|
||||
% Zeta: Zeta matrx
|
||||
%
|
||||
% SPECIAL REQUIREMENTS
|
||||
% none
|
||||
|
||||
% Copyright (C) 2013 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
% Dynare is free software: you can redistribute it and/or modify
|
||||
% it under the terms of the GNU General Public License as published by
|
||||
% the Free Software Foundation, either version 3 of the License, or
|
||||
% (at your option) any later version.
|
||||
%
|
||||
% Dynare is distributed in the hope that it will be useful,
|
||||
% but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
% GNU General Public License for more details.
|
||||
%
|
||||
% You should have received a copy of the GNU General Public License
|
||||
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
Q = [];
|
||||
A0 = [];
|
||||
Aplus = [];
|
||||
Zeta = [];
|
||||
|
||||
try
|
||||
headerfid = fopen(['est_flat_header_' file_tag '.out'], 'r');
|
||||
catch
|
||||
error(['Can''t find est_flat_header_' file_tag '.out'])
|
||||
end
|
||||
headerfile=textscan(headerfid, '%s');
|
||||
fclose(headerfid);
|
||||
flatfile = dlmread(['est_flat_' file_tag '.out'], ' ');
|
||||
|
||||
headerfile = headerfile{:};
|
||||
for i=1:length(headerfile)
|
||||
line = char(headerfile{i});
|
||||
indob = strfind(line, '[');
|
||||
indcb = strfind(line, ']');
|
||||
indop = strfind(line, '(');
|
||||
indcp = strfind(line, ')');
|
||||
indc = strfind(line, ',');
|
||||
if isempty(indob)
|
||||
name = line(1:indop-1);
|
||||
dim3 = [];
|
||||
else
|
||||
name = line(1:indob-1);
|
||||
dim3 = line(indob+1:indcb-1);
|
||||
end
|
||||
row = line(indop+1:indc-1);
|
||||
col = line(indc+1:indcp-1);
|
||||
|
||||
if isempty(dim3)
|
||||
eval([name '(' row ',' col ') = ' num2str(flatfile(i)) ';']);
|
||||
else
|
||||
eval([name '(' row ',' col ',' dim3 ') = ' num2str(flatfile(i)) ';']);
|
||||
end
|
||||
end
|
||||
|
|
@ -67,8 +67,8 @@ end
|
|||
%build covariance matrix from correlation matrix and variances already on
|
||||
%diagonal
|
||||
Sigma_e = diag(sqrt(diag(Sigma_e)))*Correlation_matrix*diag(sqrt(diag(Sigma_e)));
|
||||
if isfield(estim_params,'calibrated_covariances')
|
||||
Sigma_e(estim_params.calibrated_covariances.position)=estim_params.calibrated_covariances.cov_value;
|
||||
if isfield(estim_params_,'calibrated_covariances')
|
||||
Sigma_e(estim_params_.calibrated_covariances.position)=estim_params_.calibrated_covariances.cov_value;
|
||||
end
|
||||
|
||||
% and update offset
|
||||
|
|
|
|||
|
|
@ -34,7 +34,7 @@ function dr=set_state_space(dr,DynareModel,DynareOptions)
|
|||
%! @end deftypefn
|
||||
%@eod:
|
||||
|
||||
% Copyright (C) 1996-2012 Dynare Team
|
||||
% Copyright (C) 1996-2013 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
|
|
@ -84,6 +84,9 @@ if max_lag > 0
|
|||
end
|
||||
kmask = [kmask; lead_lag_incidence(1,order_var)] ;
|
||||
else
|
||||
if max_lead==0 %%in this case lead_lag_incidence has no entry max_lag+2
|
||||
error('Dynare currently does not allow to solve purely static models in a stochastic context.')
|
||||
end
|
||||
kmask = lead_lag_incidence(max_lag+2,order_var) ;
|
||||
end
|
||||
|
||||
|
|
|
|||
|
|
@ -195,7 +195,7 @@ if options_.irf
|
|||
y(i_var(j),:)');
|
||||
eval(['oo_.irfs.' deblank(M_.endo_names(i_var(j),:)) '_' ...
|
||||
deblank(M_.exo_names(i,:)) ' = y(i_var(j),:);']);
|
||||
if max(y(i_var(j),:)) - min(y(i_var(j),:)) > 1e-10
|
||||
if max(y(i_var(j),:)) - min(y(i_var(j),:)) > options_.impulse_responses.plot_threshold
|
||||
irfs = cat(1,irfs,y(i_var(j),:));
|
||||
if isempty(mylist)
|
||||
mylist = deblank(var_list(j,:));
|
||||
|
|
@ -209,6 +209,10 @@ if options_.irf
|
|||
mylistTeX = char(mylistTeX,deblank(var_listTeX(j,:)));
|
||||
end
|
||||
end
|
||||
else
|
||||
if options_.debug
|
||||
fprintf('STOCH_SIMUL: The IRF of %s to %s is smaller than the irf_plot_threshold of %4.3f and will not be displayed.\n',deblank(M_.endo_names(i_var(j),:)),deblank(M_.exo_names(i,:)),options_.impulse_responses.plot_threshold)
|
||||
end
|
||||
end
|
||||
end
|
||||
if options_.nograph == 0
|
||||
|
|
|
|||
|
|
@ -581,15 +581,20 @@ EstimatedParamsStatement::writeOutput(ostream &output, const string &basename) c
|
|||
}
|
||||
|
||||
EstimatedParamsInitStatement::EstimatedParamsInitStatement(const vector<EstimationParams> &estim_params_list_arg,
|
||||
const SymbolTable &symbol_table_arg) :
|
||||
const SymbolTable &symbol_table_arg,
|
||||
const bool use_calibration_arg) :
|
||||
estim_params_list(estim_params_list_arg),
|
||||
symbol_table(symbol_table_arg)
|
||||
symbol_table(symbol_table_arg),
|
||||
use_calibration(use_calibration_arg)
|
||||
{
|
||||
}
|
||||
|
||||
void
|
||||
EstimatedParamsInitStatement::writeOutput(ostream &output, const string &basename) const
|
||||
{
|
||||
if (use_calibration)
|
||||
output << "options_.use_calibration_initialization = 1;" << endl;
|
||||
|
||||
vector<EstimationParams>::const_iterator it;
|
||||
|
||||
for (it = estim_params_list.begin(); it != estim_params_list.end(); it++)
|
||||
|
|
|
|||
|
|
@ -290,9 +290,11 @@ class EstimatedParamsInitStatement : public Statement
|
|||
private:
|
||||
const vector<EstimationParams> estim_params_list;
|
||||
const SymbolTable &symbol_table;
|
||||
const bool use_calibration;
|
||||
public:
|
||||
EstimatedParamsInitStatement(const vector<EstimationParams> &estim_params_list_arg,
|
||||
const SymbolTable &symbol_table_arg);
|
||||
const SymbolTable &symbol_table_arg,
|
||||
const bool use_calibration_arg);
|
||||
virtual void writeOutput(ostream &output, const string &basename) const;
|
||||
};
|
||||
|
||||
|
|
|
|||
|
|
@ -90,7 +90,7 @@ class ParsingDriver;
|
|||
%}
|
||||
|
||||
%token AIM_SOLVER ANALYTIC_DERIVATION AR AUTOCORR
|
||||
%token BAYESIAN_IRF BETA_PDF BLOCK
|
||||
%token BAYESIAN_IRF BETA_PDF BLOCK USE_CALIBRATION
|
||||
%token BVAR_DENSITY BVAR_FORECAST
|
||||
%token BVAR_PRIOR_DECAY BVAR_PRIOR_FLAT BVAR_PRIOR_LAMBDA
|
||||
%token BVAR_PRIOR_MU BVAR_PRIOR_OMEGA BVAR_PRIOR_TAU BVAR_PRIOR_TRAIN
|
||||
|
|
@ -106,7 +106,7 @@ class ParsingDriver;
|
|||
%token HISTVAL HOMOTOPY_SETUP HOMOTOPY_MODE HOMOTOPY_STEPS HOMOTOPY_FORCE_CONTINUE HP_FILTER HP_NGRID HYBRID
|
||||
%token IDENTIFICATION INF_CONSTANT INITVAL INITVAL_FILE BOUNDS JSCALE INIT
|
||||
%token <string_val> INT_NUMBER
|
||||
%token INV_GAMMA_PDF INV_GAMMA1_PDF INV_GAMMA2_PDF IRF IRF_SHOCKS
|
||||
%token INV_GAMMA_PDF INV_GAMMA1_PDF INV_GAMMA2_PDF IRF IRF_SHOCKS IRF_PLOT_THRESHOLD
|
||||
%token KALMAN_ALGO KALMAN_TOL SUBSAMPLES OPTIONS TOLF
|
||||
%token LAPLACE LIK_ALGO LIK_INIT LINEAR LOAD_IDENT_FILES LOAD_MH_FILE LOAD_PARAMS_AND_STEADY_STATE LOGLINEAR LYAPUNOV
|
||||
%token LYAPUNOV_FIXED_POINT_TOL LYAPUNOV_DOUBLING_TOL LYAPUNOV_SQUARE_ROOT_SOLVER_TOL LOG_DEFLATOR LOG_TREND_VAR LOG_GROWTH_FACTOR MARKOWITZ MARGINAL_DENSITY MAX MAXIT
|
||||
|
|
@ -990,6 +990,7 @@ stoch_simul_primary_options : o_dr_algo
|
|||
| o_dr_cycle_reduction_tol
|
||||
| o_dr_logarithmic_reduction_tol
|
||||
| o_dr_logarithmic_reduction_maxiter
|
||||
| o_irf_plot_threshold
|
||||
;
|
||||
|
||||
stoch_simul_options : stoch_simul_primary_options
|
||||
|
|
@ -1136,7 +1137,10 @@ estimated_elem3 : expression_or_empty COMMA expression_or_empty
|
|||
;
|
||||
|
||||
estimated_params_init : ESTIMATED_PARAMS_INIT ';' estimated_init_list END ';'
|
||||
{ driver.estimated_params_init(); };
|
||||
{ driver.estimated_params_init(); }
|
||||
| ESTIMATED_PARAMS_INIT '(' USE_CALIBRATION ')' ';' estimated_init_list END ';'
|
||||
{ driver.estimated_params_init(true); }
|
||||
;
|
||||
|
||||
estimated_init_list : estimated_init_list estimated_init_elem
|
||||
{ driver.add_estimated_params_element(); }
|
||||
|
|
@ -1562,6 +1566,7 @@ estimation_options : o_datafile
|
|||
| o_taper_steps
|
||||
| o_geweke_interval
|
||||
| o_mcmc_jumping_covariance
|
||||
| o_irf_plot_threshold
|
||||
;
|
||||
|
||||
list_optim_option : QUOTED_STRING COMMA QUOTED_STRING
|
||||
|
|
@ -2689,6 +2694,7 @@ o_mcmc_jumping_covariance : MCMC_JUMPING_COVARIANCE EQUAL HESSIAN
|
|||
| MCMC_JUMPING_COVARIANCE EQUAL filename
|
||||
{ driver.option_str("MCMC_jumping_covariance", $3); }
|
||||
;
|
||||
o_irf_plot_threshold : IRF_PLOT_THRESHOLD EQUAL non_negative_number { driver.option_num("impulse_responses.plot_threshold", $3); };
|
||||
|
||||
range : symbol ':' symbol
|
||||
{
|
||||
|
|
|
|||
|
|
@ -397,7 +397,7 @@ string eofbuff;
|
|||
return token::CNUM;
|
||||
}
|
||||
<DYNARE_STATEMENT>banact {return token::BANACT;}
|
||||
|
||||
<DYNARE_BLOCK>use_calibration {return token::USE_CALIBRATION;}
|
||||
<DYNARE_STATEMENT>output_file_tag {return token::OUTPUT_FILE_TAG;}
|
||||
<DYNARE_STATEMENT>file_tag {return token::FILE_TAG;};
|
||||
<DYNARE_STATEMENT>no_create_init {return token::NO_CREATE_INIT;};
|
||||
|
|
@ -569,6 +569,7 @@ string eofbuff;
|
|||
<DYNARE_STATEMENT>mh_recover {return token::MH_RECOVER;}
|
||||
<DYNARE_STATEMENT>planner_discount {return token::PLANNER_DISCOUNT;}
|
||||
<DYNARE_STATEMENT>calibration {return token::CALIBRATION;}
|
||||
<DYNARE_STATEMENT>irf_plot_threshold {return token::IRF_PLOT_THRESHOLD;}
|
||||
|
||||
<DYNARE_BLOCK>equation {return token::EQUATION;}
|
||||
<DYNARE_BLOCK>exclusion {return token::EXCLUSION;}
|
||||
|
|
|
|||
|
|
@ -703,7 +703,15 @@ ModFile::writeOutputFiles(const string &basename, bool clear_all, bool no_log, b
|
|||
if (block && !byte_code)
|
||||
mOutputFile << "rmpath " << basename << ";" << endl;
|
||||
|
||||
mOutputFile << "save('" << basename << "_results.mat', 'oo_', 'M_', 'options_');" << endl;
|
||||
mOutputFile << "save('" << basename << "_results.mat', 'oo_', 'M_', 'options_');" << endl
|
||||
<< "if exist('estim_params_', 'var') == 1" << endl
|
||||
<< " save('" << basename << "_results.mat', 'estim_params_', '-append');" << endl << "end" << endl
|
||||
<< "if exist('bayestopt_', 'var') == 1" << endl
|
||||
<< " save('" << basename << "_results.mat', 'bayestopt_', '-append');" << endl << "end" << endl
|
||||
<< "if exist('dataset_', 'var') == 1" << endl
|
||||
<< " save('" << basename << "_results.mat', 'dataset_', '-append');" << endl << "end" << endl
|
||||
<< "if exist('estimation_info', 'var') == 1" << endl
|
||||
<< " save('" << basename << "_results.mat', 'estimation_info', '-append');" << endl << "end" << endl;
|
||||
|
||||
config_file.writeEndParallel(mOutputFile);
|
||||
|
||||
|
|
|
|||
|
|
@ -1209,9 +1209,9 @@ ParsingDriver::estimated_params()
|
|||
}
|
||||
|
||||
void
|
||||
ParsingDriver::estimated_params_init()
|
||||
ParsingDriver::estimated_params_init(bool use_calibration)
|
||||
{
|
||||
mod_file->addStatement(new EstimatedParamsInitStatement(estim_params_list, mod_file->symbol_table));
|
||||
mod_file->addStatement(new EstimatedParamsInitStatement(estim_params_list, mod_file->symbol_table, use_calibration));
|
||||
estim_params_list.clear();
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -394,7 +394,7 @@ public:
|
|||
//! Writes estimated params command
|
||||
void estimated_params();
|
||||
//! Writes estimated params init command
|
||||
void estimated_params_init();
|
||||
void estimated_params_init(bool use_calibration = false);
|
||||
//! Writes estimated params bound command
|
||||
void estimated_params_bounds();
|
||||
//! Adds a declaration for a user-defined external function
|
||||
|
|
|
|||
|
|
@ -4,6 +4,8 @@ MODFILES = \
|
|||
estimation/fs2000_mc6.mod \
|
||||
estimation/fs2000_mc6_mf.mod \
|
||||
estimation/fs2000_MCMC_jumping_covariance.mod \
|
||||
estimation/fs2000_initialize_from_calib.mod \
|
||||
estimation/fs2000_calibrated_covariance.mod \
|
||||
gsa/ls2003.mod \
|
||||
ramst.mod \
|
||||
ramst_a.mod \
|
||||
|
|
@ -311,7 +313,8 @@ EXTRA_DIST = \
|
|||
third_order/policyfunctions.mat \
|
||||
shock_decomposition/example1_calib_shock_decomp_data.mat \
|
||||
shock_decomposition/fsdat_simul.m \
|
||||
estimation/fs2000_MCMC_jumping_covariance_steadystate.m
|
||||
estimation/fs2000_MCMC_jumping_covariance_steadystate.m \
|
||||
estimation/fs2000_initialize_from_calib_steadystate.m
|
||||
|
||||
TARGETS =
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,94 @@
|
|||
//uses a prior mean for bet that does not allow solving the model. Then uses the calibrated value to initialize.
|
||||
var m P c e W R k d n l gy_obs gp_obs y dA;
|
||||
varexo e_a e_m e_f;
|
||||
|
||||
parameters alp bet gam mst rho psi del;
|
||||
|
||||
alp = 0.33;
|
||||
bet = 0.99;
|
||||
gam = 0.003;
|
||||
mst = 1.011;
|
||||
rho = 0.7;
|
||||
psi = 0.787;
|
||||
del = 0.02;
|
||||
|
||||
model;
|
||||
dA = exp(gam+e_a);
|
||||
log(m) = (1-rho)*log(mst) + rho*log(m(-1))+e_m;
|
||||
-P/(c(+1)*P(+1)*m)+bet*P(+1)*(alp*exp(-alp*(gam+log(e(+1))))*k^(alp-1)*n(+1)^(1-alp)+(1-del)*exp(-(gam+log(e(+1)))))/(c(+2)*P(+2)*m(+1))=0;
|
||||
W = l/n;
|
||||
-(psi/(1-psi))*(c*P/(1-n))+l/n = 0;
|
||||
R = P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(-alp)/W;
|
||||
1/(c*P)-bet*P*(1-alp)*exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)/(m*l*c(+1)*P(+1)) = 0;
|
||||
c+k = exp(-alp*(gam+e_a))*k(-1)^alp*n^(1-alp)+(1-del)*exp(-(gam+e_a))*k(-1);
|
||||
P*c = m;
|
||||
m-1+d = l;
|
||||
e = exp(e_a);
|
||||
y = k(-1)^alp*n^(1-alp)*exp(-alp*(gam+e_a));
|
||||
gy_obs = dA*y/y(-1);
|
||||
gp_obs = (P/P(-1))*m(-1)/dA;
|
||||
end;
|
||||
|
||||
initval;
|
||||
k = 6;
|
||||
m = mst;
|
||||
P = 2.25;
|
||||
c = 0.45;
|
||||
e = 1;
|
||||
W = 4;
|
||||
R = 1.02;
|
||||
d = 0.85;
|
||||
n = 0.19;
|
||||
l = 0.86;
|
||||
y = 0.6;
|
||||
gy_obs = exp(gam);
|
||||
gp_obs = exp(-gam);
|
||||
dA = exp(gam);
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var e_a; stderr 0.014;
|
||||
var e_m; stderr 0.005;
|
||||
var e_f; stderr 0.005;
|
||||
corr gy_obs, gp_obs = 0.1;
|
||||
var gy_obs; stderr 0.005;
|
||||
end;
|
||||
|
||||
steady;
|
||||
//check;
|
||||
|
||||
estimated_params;
|
||||
alp, beta_pdf, 0.356, 0.02;
|
||||
bet, normal_pdf, 2, 1;
|
||||
gam, normal_pdf, 0.0085, 0.003;
|
||||
mst, normal_pdf, 1.0002, 0.007;
|
||||
rho, normal_pdf, 0.129, 0.223;
|
||||
psi, beta_pdf, 0.65, 0.05;
|
||||
del, beta_pdf, 0.01, 0.005;
|
||||
stderr e_a, inv_gamma_pdf, 0.035449, inf;
|
||||
stderr e_m, inv_gamma_pdf, 0.008862, inf;
|
||||
corr e_a, e_m, normal_pdf, 0, 0.007;
|
||||
corr e_a, e_f, normal_pdf, 0, 0.007;
|
||||
stderr gp_obs, inv_gamma_pdf, 0.008862, inf;
|
||||
corr gp_obs, gy_obs, normal_pdf, 0, 0.007;
|
||||
end;
|
||||
|
||||
varobs gp_obs gy_obs;
|
||||
|
||||
estimated_params_init(use_calibration);
|
||||
//stderr e_a, 0.014000;
|
||||
//stderr e_m, 0.005000;
|
||||
//stderr gp_obs, 0.1;
|
||||
corr e_m, e_a, 0.1;
|
||||
//corr gy_obs, gp_obs, 0.000000;
|
||||
//alp, 0.330000;
|
||||
//bet, 0.990000;
|
||||
gam, 0.003000;
|
||||
mst, 1.011000;
|
||||
//rho, 0.900000;
|
||||
psi, 0.787000;
|
||||
del, 0.020000;
|
||||
end;
|
||||
|
||||
options_.plot_priors=0;
|
||||
estimation(order=1, datafile=fsdat_simul, nobs=192, loglinear, mh_replic=2000, mh_nblocks=1, mh_jscale=0.8,prior_trunc=0);
|
||||
|
|
@ -0,0 +1,73 @@
|
|||
% computes the steady state of fs2000 analyticaly
|
||||
% largely inspired by the program of F. Schorfheide
|
||||
|
||||
% Copyright (C) 2004-2010 Dynare Team
|
||||
%
|
||||
% This file is part of Dynare.
|
||||
%
|
||||
% Dynare is free software: you can redistribute it and/or modify
|
||||
% it under the terms of the GNU General Public License as published by
|
||||
% the Free Software Foundation, either version 3 of the License, or
|
||||
% (at your option) any later version.
|
||||
%
|
||||
% Dynare is distributed in the hope that it will be useful,
|
||||
% but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
% GNU General Public License for more details.
|
||||
%
|
||||
% You should have received a copy of the GNU General Public License
|
||||
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
|
||||
|
||||
function [ys,check] = fs2000_steadystate(ys,exe)
|
||||
global M_
|
||||
|
||||
alp = M_.params(1);
|
||||
bet = M_.params(2);
|
||||
gam = M_.params(3);
|
||||
mst = M_.params(4);
|
||||
rho = M_.params(5);
|
||||
psi = M_.params(6);
|
||||
del = M_.params(7);
|
||||
|
||||
check = 0;
|
||||
|
||||
dA = exp(gam);
|
||||
gst = 1/dA;
|
||||
m = mst;
|
||||
|
||||
khst = ( (1-gst*bet*(1-del)) / (alp*gst^alp*bet) )^(1/(alp-1));
|
||||
xist = ( ((khst*gst)^alp - (1-gst*(1-del))*khst)/mst )^(-1);
|
||||
nust = psi*mst^2/( (1-alp)*(1-psi)*bet*gst^alp*khst^alp );
|
||||
n = xist/(nust+xist);
|
||||
P = xist + nust;
|
||||
k = khst*n;
|
||||
|
||||
l = psi*mst*n/( (1-psi)*(1-n) );
|
||||
c = mst/P;
|
||||
d = l - mst + 1;
|
||||
y = k^alp*n^(1-alp)*gst^alp;
|
||||
R = mst/bet;
|
||||
W = l/n;
|
||||
ist = y-c;
|
||||
q = 1 - d;
|
||||
|
||||
e = 1;
|
||||
|
||||
gp_obs = m/dA;
|
||||
gy_obs = dA;
|
||||
|
||||
ys =[
|
||||
m
|
||||
P
|
||||
c
|
||||
e
|
||||
W
|
||||
R
|
||||
k
|
||||
d
|
||||
n
|
||||
l
|
||||
gy_obs
|
||||
gp_obs
|
||||
y
|
||||
dA ];
|
||||
|
|
@ -104,7 +104,7 @@ corr gp_obs, gy_obs,0;
|
|||
end;
|
||||
|
||||
options_.TeX=1;
|
||||
estimation(mode_compute=9,order=1,datafile=fsdat_simul,mode_check,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
|
||||
estimation(order=1,datafile=fsdat_simul,mode_check,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue