diff --git a/matlab/method_of_moments/method_of_moments.m b/matlab/method_of_moments/method_of_moments.m
index faa832f567ca50f47e59568add9f4c97d49149ce..28ec839c943e553dca316fa54788c46ef9b77f00 100644
--- a/matlab/method_of_moments/method_of_moments.m
+++ b/matlab/method_of_moments/method_of_moments.m
@@ -1,5 +1,5 @@
-function [oo_, options_mom_, M_] = method_of_moments(bayestopt_, options_, oo_, estim_params_, M_, matched_moments_, options_mom_)
-%function [oo_, options_mom_, M_] = method_of_moments(bayestopt_, options_, oo_, estim_params_, M_, matched_moments_, options_mom_)
+function [oo_, options_mom_, M_] = method_of_moments(bayestopt_, options_, oo_, estim_params_, M_, options_mom_)
+%function [oo_, options_mom_, M_] = method_of_moments(bayestopt_, options_, oo_, estim_params_, M_, options_mom_)
% -------------------------------------------------------------------------
% This function performs a method of moments estimation with the following steps:
% Step 0: Check if required structures and options exist
@@ -26,11 +26,11 @@ function [oo_, options_mom_, M_] = method_of_moments(bayestopt_, options_, oo_,
% o options_: [structure] information about global options
% o oo_: [structure] storage for results
% o estim_params_: [structure] information about estimated parameters
-% o M_: [structure] information about model
-% o matched_moments_: [cell] information about selected moments to match in estimation
-% vars: matched_moments_{:,1});
-% lead/lags: matched_moments_{:,2};
-% powers: matched_moments_{:,3};
+% o M_: [structure] information about model with
+% o matched_moments: [cell] information about selected moments to match in estimation
+% vars: matched_moments{:,1});
+% lead/lags: matched_moments{:,2};
+% powers: matched_moments{:,3};
% o options_mom_: [structure] information about settings specified by the user
% -------------------------------------------------------------------------
% OUTPUTS
@@ -111,7 +111,7 @@ if isempty(estim_params_) % structure storing the info about estimated parameter
error('method_of_moments: The ''estimated_params'' block must not be empty')
end
end
-if isempty(matched_moments_) % structure storing the moments used for the method of moments estimation
+if isempty(M_.matched_moments) % structure storing the moments used for the method of moments estimation
error('method_of_moments: You need to provide a ''matched_moments'' block')
end
if ~isempty(bayestopt_) && any(bayestopt_.pshape==0) && any(bayestopt_.pshape~=0)
@@ -373,52 +373,52 @@ options_mom_.mom.index.E_y_pos = zeros(options_mom_.obs_nbr,1);
options_mom_.mom.index.E_yy_pos = zeros(options_mom_.obs_nbr,options_mom_.obs_nbr); %position in matched moments block
options_mom_.mom.index.E_yyt_pos = zeros(options_mom_.obs_nbr,options_mom_.obs_nbr,0); %position in matched moments block
-for jm=1:size(matched_moments_,1)
+for jm=1:size(M_.matched_moments,1)
% higher-order product moments not supported yet for GMM
- if strcmp(options_mom_.mom.mom_method, 'GMM') && sum(matched_moments_{jm,3}) > 2
+ if strcmp(options_mom_.mom.mom_method, 'GMM') && sum(M_.matched_moments{jm,3}) > 2
error('method_of_moments: GMM does not yet support product moments higher than 2. Change row %d in ''matched_moments'' block.',jm);
end
% Check if declared variables are also observed (needed as otherwise the dataset variables won't coincide)
- if any(~ismember(oo_.dr.inv_order_var(matched_moments_{jm,1})', oo_.dr.obs_var))
+ if any(~ismember(oo_.dr.inv_order_var(M_.matched_moments{jm,1})', oo_.dr.obs_var))
error('method_of_moments: Variables in row %d in ''matched_moments'' block need to be declared as VAROBS.', jm)
end
if strcmp(options_mom_.mom.mom_method, 'GMM')
% Check (for now) that only lags are declared
- if any(matched_moments_{jm,2}>0)
+ if any(M_.matched_moments{jm,2}>0)
error('method_of_moments: Leads in row %d in the ''matched_moments'' block are not supported for GMM, shift the moments and declare only lags.', jm)
end
% Check (for now) that first declared variable has zero lag
- if matched_moments_{jm,2}(1)~=0
+ if M_.matched_moments{jm,2}(1)~=0
error('method_of_moments: The first variable declared in row %d in the ''matched_moments'' block is not allowed to have a lead or lag for GMM;\n reorder the variables in the row such that the first variable has zero lag!',jm)
end
end
- vars = oo_.dr.inv_order_var(matched_moments_{jm,1})';
- if sum(matched_moments_{jm,3}) == 1
+ vars = oo_.dr.inv_order_var(M_.matched_moments{jm,1})';
+ if sum(M_.matched_moments{jm,3}) == 1
% First-order product moment
vpos = (oo_.dr.obs_var == vars);
options_mom_.mom.index.E_y(vpos,1) = true;
options_mom_.mom.index.E_y_pos(vpos,1) = jm;
- matched_moments_{jm,4}=['E(',M_.endo_names{matched_moments_{jm,1}},')'];
- matched_moments_{jm,5}=['$E(',M_.endo_names_tex{matched_moments_{jm,1}},')$'];
- elseif sum(matched_moments_{jm,3}) == 2
+ M_.matched_moments{jm,4}=['E(',M_.endo_names{M_.matched_moments{jm,1}},')'];
+ M_.matched_moments{jm,5}=['$E(',M_.endo_names_tex{M_.matched_moments{jm,1}},')$'];
+ elseif sum(M_.matched_moments{jm,3}) == 2
% Second-order product moment
idx1 = (oo_.dr.obs_var == vars(1));
idx2 = (oo_.dr.obs_var == vars(2));
- lag1 = matched_moments_{jm,2}(1);
- lag2 = matched_moments_{jm,2}(2);
+ lag1 = M_.matched_moments{jm,2}(1);
+ lag2 = M_.matched_moments{jm,2}(2);
if lag1==0 && lag2==0 % contemporaneous covariance matrix
options_mom_.mom.index.E_yy(idx1,idx2) = true;
options_mom_.mom.index.E_yy(idx2,idx1) = true;
options_mom_.mom.index.E_yy_pos(idx1,idx2) = jm;
options_mom_.mom.index.E_yy_pos(idx2,idx1) = jm;
- matched_moments_{jm,4}=['E(',M_.endo_names{matched_moments_{jm,1}(1)},',',M_.endo_names{matched_moments_{jm,1}(2)},')'];
- matched_moments_{jm,5}=['$E({',M_.endo_names_tex{matched_moments_{jm,1}(1)},'}_t,{',M_.endo_names_tex{matched_moments_{jm,1}(1)},'}_t)$'];
+ M_.matched_moments{jm,4}=['E(',M_.endo_names{M_.matched_moments{jm,1}(1)},',',M_.endo_names{M_.matched_moments{jm,1}(2)},')'];
+ M_.matched_moments{jm,5}=['$E({',M_.endo_names_tex{M_.matched_moments{jm,1}(1)},'}_t,{',M_.endo_names_tex{M_.matched_moments{jm,1}(1)},'}_t)$'];
elseif lag1==0 && lag2 < 0
options_mom_.mom.index.E_yyt(idx1,idx2,-lag2) = true;
options_mom_.mom.index.E_yyt_pos(idx1,idx2,-lag2) = jm;
- matched_moments_{jm,4}=['E(',M_.endo_names{matched_moments_{jm,1}(1)},',',M_.endo_names{matched_moments_{jm,1}(2)},'(',num2str(lag2),'))'];
- matched_moments_{jm,5}=['$E({',M_.endo_names_tex{matched_moments_{jm,1}(1)},'}_t\times{',M_.endo_names_tex{matched_moments_{jm,1}(1)},'_{t',num2str(lag2) ,'})$'];
+ M_.matched_moments{jm,4}=['E(',M_.endo_names{M_.matched_moments{jm,1}(1)},',',M_.endo_names{M_.matched_moments{jm,1}(2)},'(',num2str(lag2),'))'];
+ M_.matched_moments{jm,5}=['$E({',M_.endo_names_tex{M_.matched_moments{jm,1}(1)},'}_t\times{',M_.endo_names_tex{M_.matched_moments{jm,1}(1)},'_{t',num2str(lag2) ,'})$'];
end
end
end
@@ -427,27 +427,27 @@ end
% @wmutschl: add check for duplicate moments by using the cellfun and unique functions
%Remove duplicate elements
UniqueMomIdx = [nonzeros(options_mom_.mom.index.E_y_pos); nonzeros(tril(options_mom_.mom.index.E_yy_pos)); nonzeros(options_mom_.mom.index.E_yyt_pos)];
-DuplicateMoms = setdiff(1:size(matched_moments_,1),UniqueMomIdx);
+DuplicateMoms = setdiff(1:size(M_.matched_moments,1),UniqueMomIdx);
if ~isempty(DuplicateMoms)
fprintf('Found and removed duplicate declared moments in ''matched_moments'' block in rows: %s.\n',num2str(DuplicateMoms))
end
-%reorder matched_moments_ to be compatible with options_mom_.mom.index
-matched_moments_ = matched_moments_(UniqueMomIdx,:);
+%reorder M_.matched_moments to be compatible with options_mom_.mom.index
+M_.matched_moments = M_.matched_moments(UniqueMomIdx,:);
if strcmp(options_mom_.mom.mom_method,'SMM')
options_mom_.mom=rmfield(options_mom_.mom,'index');
end
% Check if both prefilter and first moments were specified
-options_mom_.mom.first_moment_indicator = find(cellfun(@(x) sum(abs(x))==1,matched_moments_(:,3)))';
+options_mom_.mom.first_moment_indicator = find(cellfun(@(x) sum(abs(x))==1,M_.matched_moments(:,3)))';
if options_mom_.prefilter && ~isempty(options_mom_.mom.first_moment_indicator)
fprintf('Centered moments requested (prefilter option is set); therefore, ignore declared first moments in ''matched_moments'' block in rows: %u.\n',options_mom_.mom.first_moment_indicator');
- matched_moments_(options_mom_.mom.first_moment_indicator,:)=[]; %remove first moments entries
+ M_.matched_moments(options_mom_.mom.first_moment_indicator,:)=[]; %remove first moments entries
options_mom_.mom.first_moment_indicator = [];
end
-options_mom_.mom.mom_nbr = size(matched_moments_,1);
+options_mom_.mom.mom_nbr = size(M_.matched_moments,1);
% Get maximum lag number for autocovariances/autocorrelations
-options_mom_.ar = max(cellfun(@max,matched_moments_(:,2))) - min(cellfun(@min,matched_moments_(:,2)));
+options_mom_.ar = max(cellfun(@max,M_.matched_moments(:,2))) - min(cellfun(@min,M_.matched_moments(:,2)));
% -------------------------------------------------------------------------
% Step 3: Checks and transformations for estimated parameters, priors, and bounds
@@ -625,7 +625,7 @@ if options_mom_.ar > options_mom_.nobs+1
end
% Get data moments for the method of moments
-[oo_.mom.data_moments, oo_.mom.m_data] = method_of_moments_data_moments(dataset_.data, oo_, matched_moments_, options_mom_);
+[oo_.mom.data_moments, oo_.mom.m_data] = method_of_moments_data_moments(dataset_.data, oo_, M_.matched_moments, options_mom_);
% Get shock series for SMM and set variance correction factor
if strcmp(options_mom_.mom.mom_method,'SMM')
@@ -702,7 +702,7 @@ try
% at initial parameters and identity weighting matrix
oo_.mom.Sw = eye(options_mom_.mom.mom_nbr);
tic_id = tic;
- [fval, info, ~, ~, ~, oo_, M_] = feval(objective_function, xparam0, Bounds, oo_, estim_params_, matched_moments_, M_, options_mom_);
+ [fval, info, ~, ~, ~, oo_, M_] = feval(objective_function, xparam0, Bounds, oo_, estim_params_, M_, options_mom_);
elapsed_time = toc(tic_id);
if isnan(fval)
error('method_of_moments: The initial value of the objective function is NaN')
@@ -840,7 +840,7 @@ for stage_iter=1:size(options_mom_.mom.weighting_matrix,1)
options_mom_.vector_output = false;
end
[xparam1, fval, exitflag] = dynare_minimize_objective(objective_function, xparam0, optimizer_vec(optim_iter), options_mom_, [Bounds.lb Bounds.ub], bayestopt_laplace.name, bayestopt_laplace, [],...
- Bounds, oo_, estim_params_, matched_moments_, M_, options_mom_);
+ Bounds, oo_, estim_params_, M_, options_mom_);
if options_mom_.vector_output
fval = fval'*fval;
end
@@ -853,9 +853,9 @@ for stage_iter=1:size(options_mom_.mom.weighting_matrix,1)
options_mom_.vector_output = false;
% Update M_ and DynareResults (in particular to get oo_.mom.model_moments)
M_ = set_all_parameters(xparam1,estim_params_,M_);
- [fval, ~, ~,~,~, oo_] = feval(objective_function, xparam1, Bounds, oo_, estim_params_, matched_moments_, M_, options_mom_);
+ [fval, ~, ~,~,~, oo_] = feval(objective_function, xparam1, Bounds, oo_, estim_params_, M_, options_mom_);
% Compute Standard errors
- SE = method_of_moments_standard_errors(xparam1, objective_function, Bounds, oo_, estim_params_, matched_moments_, M_, options_mom_, Woptflag);
+ SE = method_of_moments_standard_errors(xparam1, objective_function, Bounds, oo_, estim_params_, M_, options_mom_, Woptflag);
% Store results in output structure
oo_.mom = display_estimation_results_table(xparam1,SE,M_,options_mom_,estim_params_,bayestopt_laplace,oo_.mom,prior_dist_names,sprintf('%s (STAGE %u)',options_mom_.mom.mom_method,stage_iter),sprintf('%s_stage_%u',lower(options_mom_.mom.mom_method),stage_iter));
@@ -870,7 +870,7 @@ if options_mom_.mom.mom_nbr > length(xparam1)
W_opt = method_of_moments_optimal_weighting_matrix(oo_.mom.m_data, oo_.mom.model_moments, options_mom_.mom.bartlett_kernel_lag);
oo_j=oo_;
oo_j.mom.Sw = chol(W_opt);
- [fval] = feval(objective_function, xparam1, Bounds, oo_j, estim_params_, matched_moments_, M_, options_mom_);
+ [fval] = feval(objective_function, xparam1, Bounds, oo_j, estim_params_, M_, options_mom_);
end
% Compute J statistic
@@ -891,18 +891,18 @@ end
% -------------------------------------------------------------------------
title = ['Data moments and model moments (',options_mom_.mom.mom_method,')'];
headers = {'Moment','Data','Model','% dev. target'};
-labels= matched_moments_(:,4);
+labels= M_.matched_moments(:,4);
data_mat=[oo_.mom.data_moments oo_.mom.model_moments 100*abs((oo_.mom.model_moments-oo_.mom.data_moments)./oo_.mom.data_moments)];
dyntable(options_mom_, title, headers, labels, data_mat, cellofchararraymaxlength(labels)+2, 10, 7);
if options_mom_.TeX
lh = cellofchararraymaxlength(labels)+2;
- labels_TeX = matched_moments_(:,5);
+ labels_TeX = M_.matched_moments(:,5);
dyn_latex_table(M_, options_mom_, title, 'sim_corr_matrix', headers, labels_TeX, data_mat, lh, 10, 7);
end
if options_mom_.mode_check.status
method_of_moments_mode_check(objective_function,xparam1,SE,options_mom_,M_,estim_params_,Bounds,bayestopt_laplace,...
- Bounds, oo_, estim_params_, matched_moments_, M_, options_mom_)
+ Bounds, oo_, estim_params_, M_, options_mom_)
end
fprintf('\n==== Method of Moments Estimation (%s) Completed ====\n\n',options_mom_.mom.mom_method)
diff --git a/matlab/method_of_moments/method_of_moments_objective_function.m b/matlab/method_of_moments/method_of_moments_objective_function.m
index e4f6714aaf91e6ae6b9cbe1c22d0756453c7d850..ca4a49d47fcd4b40084c110221a0aabcb83f851d 100644
--- a/matlab/method_of_moments/method_of_moments_objective_function.m
+++ b/matlab/method_of_moments/method_of_moments_objective_function.m
@@ -1,5 +1,5 @@
-function [fval, info, exit_flag, junk1, junk2, oo_, M_, options_mom_] = method_of_moments_objective_function(xparam1, Bounds, oo_, estim_params_, matched_moments_, M_, options_mom_)
-% [fval, info, exit_flag, junk1, junk2, oo_, M_, options_mom_] = method_of_moments_objective_function(xparam1, Bounds, oo_, estim_params_, matched_moments_, M_, options_mom_)
+function [fval, info, exit_flag, junk1, junk2, oo_, M_, options_mom_] = method_of_moments_objective_function(xparam1, Bounds, oo_, estim_params_, M_, options_mom_)
+% [fval, info, exit_flag, junk1, junk2, oo_, M_, options_mom_] = method_of_moments_objective_function(xparam1, Bounds, oo_, estim_params_, M_, options_mom_)
% -------------------------------------------------------------------------
% This function evaluates the objective function for GMM/SMM estimation
% =========================================================================
@@ -8,7 +8,6 @@ function [fval, info, exit_flag, junk1, junk2, oo_, M_, options_mom_] = method_o
% o Bounds: structure containing parameter bounds
% o oo_: structure for results
% o estim_params_: structure describing the estimated_parameters
-% o matched_moments_: structure containing information about selected moments to match in estimation
% o M_ structure describing the model
% o options_mom_: structure information about all settings (specified by the user, preprocessor, and taken from global options_)
% -------------------------------------------------------------------------
@@ -186,7 +185,7 @@ elseif strcmp(options_mom_.mom.mom_method,'SMM')
if options_mom_.prefilter
y_sim = bsxfun(@minus, y_sim, mean(y_sim,1));
end
- oo_.mom.model_moments = method_of_moments_data_moments(y_sim, oo_, matched_moments_, options_mom_);
+ oo_.mom.model_moments = method_of_moments_data_moments(y_sim, oo_, M_.matched_moments, options_mom_);
end
diff --git a/matlab/method_of_moments/method_of_moments_standard_errors.m b/matlab/method_of_moments/method_of_moments_standard_errors.m
index 785f4e8a29ab75c227e711f2690295c4d11e99e9..888ccf01f59e9650a5a3472c146d7254eaf67e8b 100644
--- a/matlab/method_of_moments/method_of_moments_standard_errors.m
+++ b/matlab/method_of_moments/method_of_moments_standard_errors.m
@@ -1,5 +1,5 @@
-function [SE_values, Asympt_Var] = method_of_moments_standard_errors(xparam, objective_function, Bounds, oo_, estim_params_, matched_moments_, M_, options_mom_, Wopt_flag)
-% [SE_values, Asympt_Var] = method_of_moments_standard_errors(xparam, objective_function, Bounds, oo_, estim_params_, matched_moments_, M_, options_mom_, Wopt_flag)
+function [SE_values, Asympt_Var] = method_of_moments_standard_errors(xparam, objective_function, Bounds, oo_, estim_params_, M_, options_mom_, Wopt_flag)
+% [SE_values, Asympt_Var] = method_of_moments_standard_errors(xparam, objective_function, Bounds, oo_, estim_params_, M_, options_mom_, Wopt_flag)
% -------------------------------------------------------------------------
% This function computes standard errors to the method of moments estimates
% Adapted from replication codes of
@@ -11,7 +11,6 @@ function [SE_values, Asympt_Var] = method_of_moments_standard_errors(xparam, obj
% o Bounds: structure containing parameter bounds
% o oo_: structure for results
% o estim_params_: structure describing the estimated_parameters
-% o matched_moments_: structure containing information about selected moments to match in estimation
% o M_ structure describing the model
% o options_mom_: structure information about all settings (specified by the user, preprocessor, and taken from global options_)
% o Wopt_flag: indicator whether the optimal weighting is actually used
@@ -62,12 +61,12 @@ for i=1:dim_params
%Positive step
xparam_eps_p = xparam;
xparam_eps_p(i,1) = xparam_eps_p(i) + eps_value;
- [~, info_p, ~, ~,~, oo__p] = feval(objective_function, xparam_eps_p, Bounds, oo_, estim_params_, matched_moments_, M_, options_mom_);
+ [~, info_p, ~, ~,~, oo__p] = feval(objective_function, xparam_eps_p, Bounds, oo_, estim_params_, M_, options_mom_);
% Negative step
xparam_eps_m = xparam;
xparam_eps_m(i,1) = xparam_eps_m(i) - eps_value;
- [~, info_m, ~, ~,~, oo__m] = feval(objective_function, xparam_eps_m, Bounds, oo_, estim_params_, matched_moments_, M_, options_mom_);
+ [~, info_m, ~, ~,~, oo__m] = feval(objective_function, xparam_eps_m, Bounds, oo_, estim_params_, M_, options_mom_);
% The Jacobian:
if nnz(info_p)==0 && nnz(info_m)==0
diff --git a/tests/estimation/method_of_moments/AnScho_MoM.mod b/tests/estimation/method_of_moments/AnScho_MoM.mod
index 674111120283a75c0f3ac4a07b12555248d32bca..2f9c2c24d83991ff411a3d189ac146de41fa9a0b 100644
--- a/tests/estimation/method_of_moments/AnScho_MoM.mod
+++ b/tests/estimation/method_of_moments/AnScho_MoM.mod
@@ -148,7 +148,23 @@ pause(1);
%--------------------------------------------------------------------------
% Method of Moments Estimation
%--------------------------------------------------------------------------
-% matched_moments blocks : We don't have an interface yet
+matched_moments;
+YGR;
+INFL;
+INT;
+%second-order contemporenous product moments
+YGR*YGR;
+YGR*INFL;
+YGR*INT;
+INFL*INFL;
+INFL*INT;
+INT*INT;
+%second-order temporal product moments
+YGR*YGR(-1);
+INT*INT(-1);
+INFL*INFL(-1);
+end;
+
% get indices in declaration order
iYGR = strmatch('YGR', M_.endo_names,'exact');
iINFL = strmatch('INFL', M_.endo_names,'exact');
@@ -181,6 +197,9 @@ matched_moments_ = {
[iINFL iINFL] [0 -1], [1 1];
};
+if ~isequal(M_.matched_moments,matched_moments_)
+ error('Translation to matched_moments-block failed')
+end
@#for mommethod in ["GMM", "SMM"]
method_of_moments(
diff --git a/tests/estimation/method_of_moments/RBC_MoM_Andreasen.mod b/tests/estimation/method_of_moments/RBC_MoM_Andreasen.mod
index feb47cb3a7db966a98538d123d5eaa782161c06b..ae69840050f5f33165cbf36d2a13c04f84feda1e 100644
--- a/tests/estimation/method_of_moments/RBC_MoM_Andreasen.mod
+++ b/tests/estimation/method_of_moments/RBC_MoM_Andreasen.mod
@@ -82,10 +82,32 @@ end;
estimated_params_init(use_calibration);
end;
+
%--------------------------------------------------------------------------
% Method of Moments Estimation
%--------------------------------------------------------------------------
-% matched_moments blocks : We don't have an interface yet
+matched_moments;
+c;
+n;
+iv;
+c*c;
+c*iv;
+iv*n;
+iv*iv;
+n*c;
+n*n;
+c*c(-1);
+n*n(-1);
+iv*iv(-1);
+
+c*c(-3);
+n*n(-3);
+iv*iv(-3);
+
+c*c(-5);
+n*n(-5);
+iv*iv(-5);
+end;
% get indices in declaration order
ic = strmatch('c', M_.endo_names,'exact');
@@ -104,9 +126,9 @@ matched_moments_ = {
[ic iiv] [0 0], [1 1];
%[ic in ] [0 0], [1 1];
%[iiv ic ] [0 0], [1 1];
- [iiv in ] [0 0], [1 1];
+ [in iiv] [0 0], [1 1];
[iiv iiv] [0 0], [1 1];
- [in ic ] [0 0], [1 1];
+ [ic in] [0 0], [1 1];
%[in iiv] [0 0], [1 1];
[in in ] [0 0], [1 1];
@@ -124,6 +146,9 @@ matched_moments_ = {
};
+if ~isequal(M_.matched_moments,matched_moments_)
+ error('Translation to matched_moments-block failed')
+end
method_of_moments(
@@ -133,7 +158,7 @@ matched_moments_ = {
% Options for both GMM and SMM
%, bartlett_kernel_lag = 20 % bandwith in optimal weighting matrix
- , order = 2 % order of Taylor approximation in perturbation
+ , order = @{orderApp} % order of Taylor approximation in perturbation
%, penalized_estimator % use penalized optimization
%, pruning % use pruned state space system at higher-order
%, verbose % display and store intermediate estimation results
diff --git a/tests/estimation/method_of_moments/RBC_MoM_SMM_ME.mod b/tests/estimation/method_of_moments/RBC_MoM_SMM_ME.mod
index a0e4ea654cd699c3db19dffc5a75645ba02f3cab..9648626709d0413dec27ceec9d09232a6b2da556 100644
--- a/tests/estimation/method_of_moments/RBC_MoM_SMM_ME.mod
+++ b/tests/estimation/method_of_moments/RBC_MoM_SMM_ME.mod
@@ -86,6 +86,23 @@ pause(1);
% Method of Moments Estimation
%--------------------------------------------------------------------------
% matched_moments blocks : We don't have an interface yet
+matched_moments;
+c;
+n;
+iv;
+
+c*c;
+c*iv;
+c*n;
+iv*c;
+iv*iv;
+iv*n;
+n*n;
+
+c*c(-1);
+n*n(-1);
+iv*iv(-1);
+end;
% get indices in declaration order
ic = strmatch('c', M_.endo_names,'exact');
@@ -102,9 +119,9 @@ matched_moments_ = {
[ic ic ] [0 0], [1 1];
[ic iiv] [0 0], [1 1];
[ic in ] [0 0], [1 1];
- [iiv ic ] [0 0], [1 1];
+ [ic iiv] [0 0], [1 1];
[iiv iiv] [0 0], [1 1];
- [iiv in ] [0 0], [1 1];
+ [in iiv] [0 0], [1 1];
% [in ic ] [0 0], [1 1];
% [in iiv] [0 0], [1 1];
[in in ] [0 0], [1 1];
@@ -114,7 +131,9 @@ matched_moments_ = {
% [iiv iiv] [0 -1], [1 1];
};
-
+if ~isequal(M_.matched_moments,matched_moments_)
+ error('Translation to matched_moments-block failed')
+end
@#for mommethod in ["SMM"]
method_of_moments(
diff --git a/tests/estimation/method_of_moments/RBC_MoM_prefilter.mod b/tests/estimation/method_of_moments/RBC_MoM_prefilter.mod
index 22924d0666800b38b523efa406562c68a75dc02b..7fb29f8abfb19ef53e9e6dbc90343b9843705308 100644
--- a/tests/estimation/method_of_moments/RBC_MoM_prefilter.mod
+++ b/tests/estimation/method_of_moments/RBC_MoM_prefilter.mod
@@ -58,7 +58,24 @@ end;
%--------------------------------------------------------------------------
% Method of Moments Estimation
%--------------------------------------------------------------------------
-% matched_moments blocks : We don't have an interface yet
+
+matched_moments;
+c;
+n;
+iv;
+
+c*c;
+c*iv;
+c*n;
+iv*c;
+iv*iv;
+iv*n;
+n*n;
+
+c*c(-1);
+n*n(-1);
+iv*iv(-1);
+end;
% get indices in declaration order
ic = strmatch('c', M_.endo_names,'exact');
@@ -75,18 +92,19 @@ matched_moments_ = {
[ic ic ] [0 0], [1 1];
[ic iiv] [0 0], [1 1];
[ic in ] [0 0], [1 1];
- [iiv ic ] [0 0], [1 1];
+ [ic iiv] [0 0], [1 1];
[iiv iiv] [0 0], [1 1];
- [iiv in ] [0 0], [1 1];
-% [in ic ] [0 0], [1 1];
-% [in iiv] [0 0], [1 1];
+ [in iiv] [0 0], [1 1];
[in in ] [0 0], [1 1];
[ic ic ] [0 -1], [1 1];
[in in ] [0 -1], [1 1];
[iiv iiv] [0 -1], [1 1];
-% [iiv iiv] [0 -1], [1 1];
};
+if ~isequal(M_.matched_moments,matched_moments_)
+ error('Translation to matched_moments-block failed')
+end
+
weighting_matrix=diag([1000;ones(8,1)]);
save('test_matrix.mat','weighting_matrix')