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ols: modify ols-style estimation routines to account for change in 7be8f10e0e

time-shift
Houtan Bastani 2018-01-11 17:10:12 +01:00
parent fe8dfba59d
commit aceeef876b
18 changed files with 56 additions and 71 deletions
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16
matlab/backward/checkdatabaseforinversion.m
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@ -5,7 +5,7 @@ function [dbase, info] = checkdatabaseforinversion(dbase, DynareModel)
% adds auxiliary variables, for lags greater than 1 on endogebnous variables
% or lags on the exogenous variables.
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -34,21 +34,21 @@ k = 0;
for i = DynareModel.orig_endo_nbr+1:DynareModel.endo_nbr
k = k+1;
if DynareModel.aux_vars(k).type==1
if ismember(deblank(DynareModel.endo_names(DynareModel.aux_vars(k).orig_index,:)), dbase.name)
dbase{deblank(DynareModel.endo_names(DynareModel.aux_vars(k).endo_index, :))} = dbase{deblank(DynareModel.endo_names(DynareModel.aux_vars(k).orig_index, :))}.lag(abs(DynareModel.aux_vars(k).orig_lead_lag));
if ismember(DynareModel.endo_names(DynareModel.aux_vars(k).orig_index,:), dbase.name)
dbase{DynareModel.endo_names(DynareModel.aux_vars(k).endo_index, :)} = dbase{DynareModel.endo_names(DynareModel.aux_vars(k).orig_index, :)}.lag(abs(DynareModel.aux_vars(k).orig_lead_lag));
else
error('%s not available in dbase!', deblank(DynareModel.endo_names(DynareModel.aux_vars(k).orig_index, :)));
error('%s not available in dbase!', DynareModel.endo_names(DynareModel.aux_vars(k).orig_index, :));
end
elseif DynareModel.aux_vars(k).type==3
dbase{deblank(DynareModel.endo_names(DynareModel.aux_vars(k).endo_index,:))} = dbase{deblank(DynareModel.exo_names(DynareModel.aux_vars(k).orig_index, :))}.lag(abs(DynareModel.aux_vars(k).orig_lead_lag));
listoflaggedexogenousvariables = vertcat(listoflaggedexogenousvariables, deblank(DynareModel.exo_names(DynareModel.aux_vars(k).orig_index, :)));
dbase{DynareModel.endo_names(DynareModel.aux_vars(k).endo_index,:)} = dbase{DynareModel.exo_names(DynareModel.aux_vars(k).orig_index, :)}.lag(abs(DynareModel.aux_vars(k).orig_lead_lag));
listoflaggedexogenousvariables = vertcat(listoflaggedexogenousvariables, DynareModel.exo_names(DynareModel.aux_vars(k).orig_index, :));
else
warning('Please contact Dynare Team!')
end
end
info.endonames = cellstr(DynareModel.endo_names);
info.exonames = cellstr(DynareModel.exo_names);
info.endonames = DynareModel.endo_names;
info.exonames = DynareModel.exo_names;
info.computeresiduals = false;
% Check that all the endogenous variables are defined in dbase.

12
matlab/ols/dyn_ols.m
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@ -18,7 +18,7 @@ function ds = dyn_ols(ds, fitted_names_dict, eqtags)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -67,9 +67,7 @@ else
end
%% Estimation
M_endo_trim = cellstr(M_.endo_names);
M_exo_trim = cellstr(M_.exo_names);
M_endo_exo_names_trim = [M_endo_trim; M_exo_trim];
M_endo_exo_names_trim = [M_.endo_names; M_.exo_names];
regex = strjoin(M_endo_exo_names_trim(:,1), '|');
mathops = '[\+\*\^\-\/\(\)]';
M_param_names_trim = cellfun(@strtrim, num2cell(M_.param_names,2), 'UniformOutput', false);
@ -77,7 +75,7 @@ for i = 1:length(lhs)
%% Construct regression matrices
rhs_ = strsplit(rhs{i}, {'+','-','*','/','^','log(','exp(','(',')'});
rhs_(cellfun(@(x) all(isstrprop(x, 'digit')), rhs_)) = [];
vnames = setdiff(rhs_, cellstr(M_.param_names));
vnames = setdiff(rhs_, M_.param_names);
if ~isempty(regexp(rhs{i}, ...
['(' strjoin(vnames, '\\(\\d+\\)|') '\\(\\d+\\))'], ...
'once'))
@ -85,7 +83,7 @@ for i = 1:length(lhs)
lineno{i} ': ' lhs{i} ' = ' rhs{i}]);
end
pnames = intersect(rhs_, cellstr(M_.param_names));
pnames = intersect(rhs_, M_.param_names);
vnames = cell(1, length(pnames));
splitstrings = cell(length(pnames), 1);
X = dseries();
@ -144,7 +142,7 @@ for i = 1:length(lhs)
end
lhssub = getRhsToSubFromLhs(ds, rhs{i}, regex, [splitstrings; pnames]);
residuals = setdiff(intersect(rhs_, M_exo_trim), ds.name);
residuals = setdiff(intersect(rhs_, M_.exo_names), ds.name);
assert(~isempty(residuals), ['No residuals in equation ' num2str(i)]);
assert(length(residuals) == 1, ['More than one residual in equation ' num2str(i)]);

3
matlab/ols/getRhsToSubFromLhs.m
View File

@ -39,7 +39,6 @@ assert(ischar(rhs), 'The second argument must be a string');
assert(ischar(regex), 'The third argument must be a string');
assert(iscell(splits), 'The fourth argument must be a cell');
M_exo_trim = cellstr(M_.exo_names);
lhssub = dseries();
rhs_ = strsplit(rhs, splits);
for j = 1:length(rhs_)
@ -61,7 +60,7 @@ for j = 1:length(rhs_)
lhssub = [lhssub eval(regexprep([minusstr str], regex, 'ds.$&'))];
lhssub.rename_(lhssub{lhssub.vobs}.name{:}, [minusstr str]);
catch
if ~any(strcmp(M_exo_trim, str))
if ~any(strcmp(M_.exo_names, str))
error(['getRhsToSubFromLhs: problem evaluating ' minusstr str]);
end
end

4
matlab/ols/olseqs.m
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@ -11,7 +11,7 @@ function olseqs(ds, varargin)
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -44,7 +44,7 @@ for i = 1:length(lhs)
%% Construct regression matrices
rhs_ = strsplit(rhs{i}, {'+','-','*','/','^','log(','exp(','(',')'});
rhs_(cellfun(@(x) all(isstrprop(x, 'digit')), rhs_)) = [];
vnames = setdiff(rhs_, cellstr(M_.param_names));
vnames = setdiff(rhs_, M_.param_names);
regexprnoleads = cell2mat(strcat('(', vnames, {'\(\d+\))|'}));
if ~isempty(regexp(rhs{i}, regexprnoleads(1:end-1), 'match'))
error(['olseqs: you cannot have leads in equation on line ' ...

7
matlab/ols/pooled_fgls.m
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@ -15,7 +15,7 @@ function pooled_fgls(ds, param_common, param_regex)
% SPECIAL REQUIREMENTS
% dynare must be run with the option: json=parse
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -45,7 +45,6 @@ kLeye = kron(chol(inv(M_.Sigma_e)), eye(oo_.sur.dof));
[q, r] = qr(kLeye*oo_.pooled_fgls.X, 0);
oo_.pooled_fgls.beta = r\(q'*kLeye*oo_.pooled_fgls.Y);
param_names_trim = cellstr(M_.param_names);
regexcountries = ['(' strjoin(param_common(1:end),'|') ')'];
pbeta = oo_.pooled_fgls.pbeta;
assigned_idxs = false(size(pbeta));
@ -54,14 +53,14 @@ for i = 1:length(param_regex)
assigned_idxs = assigned_idxs | beta_idx;
value = oo_.pooled_fgls.beta(beta_idx);
assert(~isempty(value));
M_.params(~cellfun(@isempty, regexp(param_names_trim, ...
M_.params(~cellfun(@isempty, regexp(M_.param_names, ...
strrep(param_regex{i}, '*', regexcountries)))) = value;
end
idxs = find(assigned_idxs == 0);
values = oo_.pooled_fgls.beta(idxs);
names = pbeta(idxs);
for i = 1:length(idxs)
M_.params(strcmp(param_names_trim, names{i})) = values(i);
M_.params(strcmp(M_.param_names, names{i})) = values(i);
end
oo_.pooled_fgls = rmfield(oo_.pooled_fgls, 'X');

12
matlab/ols/pooled_ols.m
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@ -21,7 +21,7 @@ function pooled_ols(ds, param_common, param_regex, overlapping_dates, save_struc
% SPECIAL REQUIREMENTS
% dynare must be run with the option: json=compute
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -85,10 +85,8 @@ for i = 1:length(param_regex)
end
%% Find parameters and variable names in every equation & Setup estimation matrices
M_exo_names_trim = cellstr(M_.exo_names);
M_param_names_trim = cellstr(M_.param_names);
[X, Y, startdates, enddates, startidxs, residnames, pbeta, vars, surpidxs, surconstrainedparams] = ...
pooled_sur_common(ds, lhs, rhs, lineno, M_exo_names_trim, M_param_names_trim);
pooled_sur_common(ds, lhs, rhs, lineno);
if overlapping_dates
maxfp = max([startdates{:}]);
@ -141,7 +139,7 @@ for i = 1:length(param_regex)
assigned_idxs = assigned_idxs | beta_idx;
value = oo_.(save_structure_name).beta(beta_idx);
assert(~isempty(value));
M_.params(~cellfun(@isempty, regexp(M_param_names_trim, ...
M_.params(~cellfun(@isempty, regexp(M_.param_names, ...
strrep(param_regex{i}, '*', regexcountries)))) = value;
end
idxs = find(assigned_idxs == 0);
@ -149,7 +147,7 @@ values = oo_.(save_structure_name).beta(idxs);
names = pbeta(idxs);
assert(length(values) == length(names));
for i = 1:length(idxs)
M_.params(strcmp(M_param_names_trim, names{i})) = values(i);
M_.params(strcmp(M_.param_names, names{i})) = values(i);
end
residuals = Y - X * oo_.(save_structure_name).beta;
@ -160,7 +158,7 @@ for i = 1:length(lhs)
oo_.(save_structure_name).resid.(residnames{i}{:}) = residuals(startidxs(i):startidxs(i+1)-1);
end
oo_.(save_structure_name).varcovar.(['eq' num2str(i)]) = oo_.(save_structure_name).resid.(residnames{i}{:})*oo_.(save_structure_name).resid.(residnames{i}{:})';
idx = find(strcmp(residnames{i}{:}, M_exo_names_trim));
idx = find(strcmp(residnames{i}{:}, M_.exo_names));
M_.Sigma_e(idx, idx) = var(oo_.(save_structure_name).resid.(residnames{i}{:}));
end
end

18
matlab/ols/pooled_sur_common.m
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@ -1,5 +1,5 @@
function [X, Y, startdates, enddates, startidxs, residnames, pbeta, vars, surpidxs, surconstrainedparams] = pooled_sur_common(ds, lhs, rhs, lineno, M_exo_names_trim, M_param_names_trim)
%function [X, Y, startdates, enddates, startidxs, residnames, pbeta, vars, surpidxs, surconstrainedparams] = pooled_sur_common(ds, lhs, rhs, lineno, M_exo_names_trim, M_param_names_trim)
function [X, Y, startdates, enddates, startidxs, residnames, pbeta, vars, surpidxs, surconstrainedparams] = pooled_sur_common(ds, lhs, rhs, lineno)
%function [X, Y, startdates, enddates, startidxs, residnames, pbeta, vars, surpidxs, surconstrainedparams] = pooled_sur_common(ds, lhs, rhs, lineno)
%
% Code common to sur.m and pooled_ols.m
%
@ -8,8 +8,6 @@ function [X, Y, startdates, enddates, startidxs, residnames, pbeta, vars, surpid
% lhs [cellstr] LHS of equations
% rhs [cellstr] RHS of equations
% lineno [cellstr] line number of equations
% M_exo_names_trim [cellarr] cellstr(M_.exo_names)
% M_param_names_trim [cellarr] cellstr(M_.param_names)
%
% OUTPUTS
% X [matrix] regressors
@ -33,7 +31,7 @@ function [X, Y, startdates, enddates, startidxs, residnames, pbeta, vars, surpid
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -52,7 +50,7 @@ function [X, Y, startdates, enddates, startidxs, residnames, pbeta, vars, surpid
global M_
M_endo_exo_names_trim = [cellstr(M_.endo_names); M_exo_names_trim];
M_endo_exo_names_trim = [M_.endo_names; M_.exo_names];
regex = strjoin(M_endo_exo_names_trim(:,1), '|');
mathops = '[\+\*\^\-\/]';
params = cell(length(rhs),1);
@ -70,7 +68,7 @@ surconstrainedparams = [];
for i = 1:length(lhs)
rhs_ = strsplit(rhs{i}, {'+','-','*','/','^','log(','ln(','log10(','exp(','(',')','diff('});
rhs_(cellfun(@(x) all(isstrprop(x, 'digit')), rhs_)) = [];
vnames = setdiff(rhs_, M_param_names_trim);
vnames = setdiff(rhs_, M_.param_names);
if ~isempty(regexp(rhs{i}, ...
['(' strjoin(vnames, '\\(\\d+\\)|') '\\(\\d+\\))'], 'once'))
error(['pooled_ols: you cannot have leads in equation on line ' ...
@ -78,7 +76,7 @@ for i = 1:length(lhs)
end
% Find parameters and associated variables
pnames = intersect(rhs_, M_param_names_trim);
pnames = intersect(rhs_, M_.param_names);
pidxs = zeros(length(pnames), 1);
vnames = cell(1, length(pnames));
splitstrings = cell(length(pnames), 1);
@ -91,7 +89,7 @@ for i = 1:length(lhs)
pbeta = [pbeta; pnames{j}];
pidxs(j) = length(pbeta);
surpidx = surpidx + 1;
surpidxs(surpidx, 1) = find(strcmp(pnames{j}, M_param_names_trim));
surpidxs(surpidx, 1) = find(strcmp(pnames{j}, M_.param_names));
else
pidxs(j) = idx;
surconstrainedparams = [surconstrainedparams idx];
@ -150,7 +148,7 @@ for i = 1:length(lhs)
lhssub = getRhsToSubFromLhs(ds, rhs{i}, regex, [splitstrings; pnames]);
residnames{i} = setdiff(intersect(rhs_, M_exo_names_trim), ds.name);
residnames{i} = setdiff(intersect(rhs_, M_.exo_names), ds.name);
assert(~isempty(residnames{i}), ['No residuals in equation ' num2str(i)]);
assert(length(residnames{i}) == 1, ['More than one residual in equation ' num2str(i)]);

6
matlab/ols/sur.m
View File

@ -44,14 +44,12 @@ jsonmodel = jsonmodel.model;
[lhs, rhs, lineno] = getEquationsByTags(jsonmodel);
%% Find parameters and variable names in equations and setup estimation matrices
M_exo_names_trim = cellstr(M_.exo_names);
M_param_names_trim = cellstr(M_.param_names);
[X, Y, startdates, enddates, startidxs, residnames, pbeta, vars, pidxs, surconstrainedparams] = ...
pooled_sur_common(ds, lhs, rhs, lineno, M_exo_names_trim, M_param_names_trim);
pooled_sur_common(ds, lhs, rhs, lineno);
if size(X, 2) ~= M_.param_nbr
warning(['Not all parameters were used in model: ' ...
sprintf('%s', strjoin(setdiff(M_param_names_trim, pbeta), ', '))]);
sprintf('%s', strjoin(setdiff(M_.param_names, pbeta), ', '))]);
end
%% Force equations to have the same sample range

4
matlab/plot_contributions.m
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@ -22,7 +22,7 @@ function plot_contributions(equationname, ds1, ds0)
% [name='Phillips curve']
% pi = beta*pi(1) + slope*y + lam;
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -107,7 +107,7 @@ rhs = rhs{:};
% Get variable and parameter names in the equation.
rhs_ = strsplit(rhs,{'+','-','*','/','^','log(','exp(','(',')'});
rhs_(cellfun(@(x) all(isstrprop(x, 'digit')), rhs_)) = []; % Remove numbers
pnames = cellstr(M_.param_names);
pnames = M_.param_names;
vnames = setdiff(rhs_, pnames);
pnames = setdiff(rhs_, vnames);

2
matlab/surgibbs.m
View File

@ -62,7 +62,7 @@ end
%% Estimation
[nobs, pidxs, X, Y, m] = sur(ds);
pnamesall = cellstr(M_.param_names(pidxs, :));
pnamesall = M_.param_names(pidxs);
nparams = length(param_names);
pidxs = zeros(nparams, 1);
for i = 1:nparams

7
matlab/var_forecast.m
View File

@ -34,15 +34,14 @@ assert( ...
length(y) == length(M_.endo_names) || ... % when called from static model
length(y) == sum(sum(M_.lead_lag_incidence ~= 0)) ... % when called from dynamic model
);
endo_names = cellstr(M_.endo_names);
yidx = zeros(size(endo_names));
yidx = zeros(size(M_.endo_names));
for i=1:size(M_.var.(name).var_list_,1)
yidx = yidx | strcmp(strtrim(M_.var.(name).var_list_(i,:)), endo_names);
yidx = yidx | strcmp(strtrim(M_.var.(name).var_list_(i,:)), M_.endo_names);
end
y = y(yidx,:);
if nargin == 4
fvidx = strcmp(fcv, endo_names);
fvidx = strcmp(fcv, M_.endo_names);
end
%% load .mat file

9
matlab/writeVarExpectationFunction.m
View File

@ -12,7 +12,7 @@ function writeVarExpectationFunction(var_model_name, horizon)
%
% NONE
% Copyright (C) 2017 Dynare Team
% Copyright (C) 2017-2018 Dynare Team
%
% This file is part of Dynare.
%
@ -53,11 +53,10 @@ fprintf(fid, '%%\n%% Created automatically by Dynare on %s\n%%\n\n', datestr(now
fprintf(fid, '%%%% Construct y\n');
fprintf(fid, 'assert(length(y) == %d);\n', sum(sum(M_.lead_lag_incidence ~= 0)));
endo_names = cellstr(M_.endo_names);
nvars = size(M_.var.(var_model_name).var_list_,1);
var_model_order = M_.var.(var_model_name).order;
yidx = zeros(nvars, min(var_model_order, 2));
% first for order <= 2, drawing variables directly from their endo_names
% first for order <= 2, drawing variables directly from their M_.endo_names
for i=1:min(var_model_order, 2)
if mod(i, 2) == 0
ridx = 1;
@ -65,7 +64,7 @@ for i=1:min(var_model_order, 2)
ridx = 2;
end
for j=1:nvars
cidx = strcmp(strtrim(M_.var.(var_model_name).var_list_(j,:)), endo_names)';
cidx = strcmp(strtrim(M_.var.(var_model_name).var_list_(j,:)), M_.endo_names)';
if ~any(cidx)
error([strtrim(M_.var.(var_model_name).var_list_(j,:)) ' not found in the list of endogenous variables']);
end
@ -79,7 +78,7 @@ if var_model_order > 2
y1idx = zeros((var_model_order - 2)*nvars, var_model_order - 2);
for i=3:var_model_order
for j=1:nvars
idx = find(strcmp(strtrim(M_.var.(var_model_name).var_list_(j,:)), endo_names));
idx = find(strcmp(strtrim(M_.var.(var_model_name).var_list_(j,:)), M_.endo_names));
if ~any(idx)
error([strtrim(M_.var.(var_model_name).var_list_(j,:)) ' not found in the list of endogenous variables']);
end

5
tests/ecb/SUR/run_simulation_test.m
View File

@ -10,15 +10,14 @@ Sigma_e = M_.Sigma_e;
options_.bnlms.set_dynare_seed_to_default = false;
M_endo_names_trim = cellstr(M_.endo_names);
nparampool = length(M_.params);
BETA = zeros(NSIMS, nparampool);
for i=1:NSIMS
i
firstobs = rand(3, length(M_endo_names_trim));
firstobs = rand(3, length(M_.endo_names));
M_.params = calibrated_values;
M_.Sigma_e = Sigma_e;
simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_endo_names_trim), 10000);
simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000);
simdata = simdata(simdata.dates(5001:6000));
names=regexp(simdata.name, 'res\w*');
idxs = [];

2
tests/ecb/SURGibbs/fulton_fish.mod
View File

@ -22,7 +22,7 @@ model(linear);
end;
% Estimate all parameters
%estparams = cellstr(M_.param_names);
%estparams = M_.param_names;
%estparamsval = M_.params;
% Estimate demand parameters

2
tests/ecb/partial-estimation/estimation_of_a_single_equation.mod
View File

@ -34,7 +34,7 @@ end;
oo_ = simul_backward_model([], 1000, options_, M_, oo_);
// Put all the simulated data in a dseries object.
ds1 = dseries(transpose(oo_.endo_simul), 1900Q1, cellstr(M_.endo_names));
ds1 = dseries(transpose(oo_.endo_simul), 1900Q1, M_.endo_names);
// Select a subsample for estimation

5
tests/ecb/pooled_fgls/run_simulation_test.m
View File

@ -9,15 +9,14 @@ Sigma_e = M_.Sigma_e;
options_.bnlms.set_dynare_seed_to_default = false;
M_endo_names_trim = cellstr(M_.endo_names);
nparampool = length(M_.params);
BETA = zeros(NSIMS, nparampool);
for i=1:NSIMS
i
firstobs = rand(3, length(M_endo_names_trim));
firstobs = rand(3, length(M_.endo_names));
M_.params = calibrated_values;
M_.Sigma_e = Sigma_e;
simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_endo_names_trim), 10000);
simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000);
simdata = simdata(simdata.dates(5001:6000));
names=regexp(simdata.name, 'res\w*');
idxs = [];

5
tests/ecb/pooled_ols/run_simulation_test.m
View File

@ -9,15 +9,14 @@ Sigma_e = M_.Sigma_e;
options_.bnlms.set_dynare_seed_to_default = false;
M_endo_names_trim = cellstr(M_.endo_names);
nparampool = length(M_.params);
BETA = zeros(NSIMS, nparampool);
for i=1:NSIMS
i
firstobs = rand(3, length(M_endo_names_trim));
firstobs = rand(3, length(M_.endo_names));
M_.params = calibrated_values;
M_.Sigma_e = Sigma_e;
simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_endo_names_trim), 10000);
simdata = simul_backward_model(dseries(firstobs, dates('1995Q1'), M_.endo_names), 10000);
simdata = simdata(simdata.dates(5001:6000));
names=regexp(simdata.name, 'res\w*');
idxs = [];

8
tests/ecb/var-expectation/run_var_comparison.m
View File

@ -73,13 +73,13 @@ exo_names = nv.M_.exo_names;
endo_names = nv.M_.endo_names;
for i = 1:length(exo_names)
figure('Name', ['Shock to ' exo_names(i)]);
figure('Name', ['Shock to ' exo_names{i}]);
for j = 1:length(endo_names)
subplot(ridx, cidx, j);
hold on
title(endo_names(j,:));
plot(nv.oo_.irfs.([deblank(endo_names(j,:)) '_' deblank(exo_names(i,:))]));
plot(wv.oo_.irfs.([deblank(endo_names(j,:)) '_' deblank(exo_names(i,:))]), '--');
title(endo_names{j});
plot(nv.oo_.irfs.([endo_names{j} '_' exo_names{i}]));
plot(wv.oo_.irfs.([endo_names{j} '_' exo_names{i}]), '--');
hold off
end
end