1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252
|
function results = get_prior_info(info,plt_flag)
% Computes various prior statistics.
%
% INPUTS
% info [integer] scalar specifying what has to be done.
%
% OUTPUTS
% none
%
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2009-2012 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/>.
global options_ M_ estim_params_ oo_ objective_function_penalty_base
if ~nargin
info = 0;
plt_flag = 0;
end
if nargin==1
plt_flag = 1;
end
% Initialize returned variable.
results = [];
changed_qz_criterium_flag = 0;
if isempty(options_.qz_criterium)
options_.qz_criterium = 1+1e-9;
changed_qz_criterium_flag = 1;
end
M_.dname = M_.fname;
% Temporarly set options_.order equal to one
order = options_.order;
options_.order = 1;
[xparam1,estim_params_,bayestopt_,lb,ub,M_] = set_prior(estim_params_,M_,options_);
if plt_flag
plot_priors(bayestopt_,M_,estim_params_,options_)
end
PriorNames = { 'Beta' , 'Gamma' , 'Gaussian' , 'Inverted Gamma' , 'Uniform' , 'Inverted Gamma -- 2' };
if size(M_.param_names,1)==size(M_.param_names_tex,1)% All the parameters have a TeX name.
fidTeX = fopen('priors_data.tex','w+');
fprintf(fidTeX,'%% TeX-table generated by get_prior_info (Dynare).\n');
fprintf(fidTeX,'%% Prior Information\n');
fprintf(fidTeX,['%% ' datestr(now,0)]);
fprintf(fidTeX,' \n');
fprintf(fidTeX,' \n');
fprintf(fidTeX,'\\begin{center}\n');
fprintf(fidTeX,'\\begin{longtable}{l|ccccccc} \n');
fprintf(fidTeX,'\\caption{Prior information (parameters)}\\\\\n ');
fprintf(fidTeX,'\\label{Table:Prior}\\\\\n');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Lower Bound & Upper Bound & LB Untrunc. 80\\%% HPDI & UB Untrunc. 80\\%% HPDI \\\\ \n');
fprintf(fidTeX,'\\hline \\endfirsthead \n');
fprintf(fidTeX,'\\caption{(continued)}\\\\\n ');
fprintf(fidTeX,'\\hline\\hline \\\\ \n');
fprintf(fidTeX,' & Prior distribution & Prior mean & Prior s.d. & Lower Bound & Upper Bound & LB Untrunc. 80\\%% HPDI & UB Untrunc. 80\\%% HPDI \\\\ \n');
fprintf(fidTeX,'\\hline \\endhead \n');
fprintf(fidTeX,'\\hline \\multicolumn{8}{r}{(Continued on next page)} \\\\ \\hline \\endfoot \n');
fprintf(fidTeX,'\\hline \\hline \\endlastfoot \n');
% Column 1: a string for the name of the prior distribution.
% Column 2: the prior mean.
% Column 3: the prior standard deviation.
% Column 4: the lower bound of the prior density support.
% Column 5: the upper bound of the prior density support.
% Column 6: the lower bound of the interval containing 80% of the prior mass.
% Column 7: the upper bound of the interval containing 80% of the prior mass.
prior_trunc_backup = options_.prior_trunc ;
options_.prior_trunc = (1-options_.prior_interval)/2 ;
PriorIntervals = prior_bounds(bayestopt_,options_) ;
options_.prior_trunc = prior_trunc_backup ;
for i=1:size(bayestopt_.name,1)
[tmp,TexName] = get_the_name(i,1,M_,estim_params_,options_);
PriorShape = PriorNames{ bayestopt_.pshape(i) };
PriorMean = bayestopt_.p1(i);
PriorStandardDeviation = bayestopt_.p2(i);
switch bayestopt_.pshape(i)
case { 1 , 5 }
LowerBound = bayestopt_.p3(i);
UpperBound = bayestopt_.p4(i);
if ~isinf(bayestopt_.lb(i))
LowerBound=max(LowerBound,bayestopt_.lb(i));
end
if ~isinf(bayestopt_.ub(i))
UpperBound=min(UpperBound,bayestopt_.ub(i));
end
case { 2 , 4 , 6 }
LowerBound = bayestopt_.p3(i);
if ~isinf(bayestopt_.lb(i))
LowerBound=max(LowerBound,bayestopt_.lb(i));
end
if ~isinf(bayestopt_.ub(i))
UpperBound=bayestopt_.ub(i);
else
UpperBound = '$\infty$';
end
case 3
if isinf(bayestopt_.p3(i)) && isinf(bayestopt_.lb(i))
LowerBound = '$-\infty$';
else
LowerBound = bayestopt_.p3(i);
if ~isinf(bayestopt_.lb(i))
LowerBound=max(LowerBound,bayestopt_.lb(i));
end
end
if isinf(bayestopt_.p4(i)) && isinf(bayestopt_.ub(i))
UpperBound = '$\infty$';
else
UpperBound = bayestopt_.p4(i);
if ~isinf(bayestopt_.ub(i))
UpperBound=min(UpperBound,bayestopt_.ub(i));
end
end
otherwise
error('get_prior_info:: Dynare bug!')
end
format_string = build_format_string(PriorStandardDeviation,LowerBound,UpperBound);
fprintf(fidTeX,format_string, ...
TexName, ...
PriorShape, ...
PriorMean, ...
PriorStandardDeviation, ...
LowerBound, ...
UpperBound, ...
PriorIntervals(i,1), ...
PriorIntervals(i,2) );
end
fprintf(fidTeX,'\\end{longtable}\n ');
fprintf(fidTeX,'\\end{center}\n');
fprintf(fidTeX,'%% End of TeX file.\n');
fclose(fidTeX);
end
M_.dname = M_.fname;
if info==1% Prior simulations (BK).
results = prior_sampler(0,M_,bayestopt_,options_,oo_,estim_params_);
% Display prior mass info
disp(['Prior mass = ' num2str(results.prior.mass)])
disp(['BK indeterminacy share = ' num2str(results.bk.indeterminacy_share)])
disp(['BK unstability share = ' num2str(results.bk.unstability_share)])
disp(['BK singularity share = ' num2str(results.bk.singularity_share)])
disp(['Complex jacobian share = ' num2str(results.jacobian.problem_share)])
disp(['mjdgges crash share = ' num2str(results.dll.problem_share)])
disp(['Steady state problem share = ' num2str(results.ss.problem_share)])
disp(['Complex steady state share = ' num2str(results.ss.complex_share)])
disp(['Analytical steady state problem share = ' num2str(results.ass.problem_share)])
end
if info==2% Prior optimization.
% Initialize to the prior mode if possible
oo_.dr=set_state_space(oo_.dr,M_,options_);
k = find(~isnan(bayestopt_.p5));
xparam1(k) = bayestopt_.p5(k);
% Pertubation of the initial condition.
look_for_admissible_initial_condition = 1;
scale = 1.0;
iter = 0;
while look_for_admissible_initial_condition
xinit = xparam1+scale*randn(size(xparam1));
if all(xinit(:)>bayestopt_.p3) && all(xinit(:)<bayestopt_.p4)
M_ = set_all_parameters(xinit,estim_params_,M_);
[dr,INFO,M_,options_,oo_] = resol(0,M_,options_,oo_);
if ~INFO(1)
look_for_admissible_initial_condition = 0;
end
else
if iter == 2000;
scale = scale/1.1;
iter = 0;
else
iter = iter+1;
end
end
end
objective_function_penalty_base = minus_logged_prior_density(xinit, bayestopt_.pshape, ...
bayestopt_.p6, ...
bayestopt_.p7, ...
bayestopt_.p3, ...
bayestopt_.p4,options_,M_,estim_params_,oo_);
% Maximization
[xparams,lpd,hessian] = ...
maximize_prior_density(xinit, bayestopt_.pshape, ...
bayestopt_.p6, ...
bayestopt_.p7, ...
bayestopt_.p3, ...
bayestopt_.p4,options_,M_,estim_params_,oo_);
% Display the results.
skipline(2)
disp('------------------')
disp('PRIOR OPTIMIZATION')
disp('------------------')
skipline()
for i = 1:length(xparams)
disp(['deep parameter ' int2str(i) ': ' get_the_name(i,0,M_,estim_params_,options_) '.'])
disp([' Initial condition ....... ' num2str(xinit(i)) '.'])
disp([' Prior mode .............. ' num2str(bayestopt_.p5(i)) '.'])
disp([' Optimized prior mode .... ' num2str(xparams(i)) '.'])
skipline()
end
end
if info==3% Prior simulations (2nd order moments).
oo_ = compute_moments_varendo('prior',options_,M_,oo_);
end
if changed_qz_criterium_flag
options_.qz_criterium = [];
end
options_.order = order;
function format_string = build_format_string(PriorStandardDeviation,LowerBound,UpperBound)
format_string = ['%s & %s & %6.4f &'];
if ~isnumeric(PriorStandardDeviation)
format_string = [ format_string , ' %s &'];
else
format_string = [ format_string , ' %6.4f &'];
end
if ~isnumeric(LowerBound)
format_string = [ format_string , ' %s &'];
else
format_string = [ format_string , ' %6.4f &'];
end
if ~isnumeric(UpperBound)
format_string = [ format_string , ' %s &'];
else
format_string = [ format_string , ' %6.4f &'];
end
format_string = [ format_string , ' %6.4f & %6.4f \\\\ \n'];
|