diff --git a/matlab/+mom/mode_compute_irf_matching.m b/matlab/+mom/mode_compute_irf_matching.m
new file mode 100644
index 0000000000000000000000000000000000000000..71bb8f9dfc8ed847e4954ab001dccf1ae05e7480
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+++ b/matlab/+mom/mode_compute_irf_matching.m
@@ -0,0 +1,122 @@
+function [xparam1, hessian_xparam1, fval, mom_verbose] = mode_compute_irf_matching(xparam0, hessian_xparam0, objective_function, doBayesianEstimation, weighting_info, data_moments, options_mom_, M_, estim_params_, bayestopt_, BoundsInfo, dr, endo_steady_state, exo_steady_state, exo_det_steady_state)
+% [xparam1, hessian_xparam1, fval, mom_verbose] = mode_compute_irf_matching(xparam0, hessian_xparam0, objective_function, doBayesianEstimation, weighting_info, data_moments, options_mom_, M_, estim_params_, bayestopt_, BoundsInfo, dr, endo_steady_state, exo_steady_state, exo_det_steady_state)
+% -------------------------------------------------------------------------
+% Computes the minimum of the objective function (distance between data irfs
+% and model irfs) for a sequence of optimizers.
+% Note that we call a "mode" the minimum of the objective function, i.e.
+% the parameter vector that minimizes the distance between the irfs
+% computed from the model and the irfs computed from the data.
+% -------------------------------------------------------------------------
+% INPUTS
+% xparam0: [vector] initialized parameters
+% hessian_xparam0: [matrix] initialized hessian at xparam0
+% objective_function: [func handle] name of the objective function
+% doBayesianEstimation: [logical] true if Bayesian estimation
+% weighting_info: [structure] information on weighting matrix
+% data_moments: [vector] data moments
+% options_mom_: [structure] options
+% M_: [structure] model information
+% estim_params_: [structure] information on estimated parameters
+% bayestopt_: [structure] information on priors
+% BoundsInfo: [structure] bounds for optimization
+% dr: [structure] information reduced-form model
+% endo_steady_state: [vector] steady state of endogenous variables (initval)
+% exo_steady_state: [vector] steady state of exogenous variables (initval)
+% exo_det_steady_state: [vector] steady state of deterministic exogenous variables (initval)
+% -------------------------------------------------------------------------
+% OUTPUT
+% xparam1: [vector] mode of objective function
+% hessian_xparam1: [matrix] hessian at xparam1
+% fval: [double] function value at mode
+% mom_verbose: [structure] information on intermediate estimation results
+% Also saves the computed mode and hessian to a file.
+% -------------------------------------------------------------------------
+% This function is called by
+% o mom.run
+% -------------------------------------------------------------------------
+% This function calls
+% o display_estimation_results_table
+% o dynare_minimize_objective
+% o hessian
+% o mom.objective_function
+% -------------------------------------------------------------------------
+
+% Copyright © 2023 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 <https://www.gnu.org/licenses/>.
+
+
+mom_verbose = [];
+for optim_iter = 1:length(options_mom_.optimizer_vec)
+ options_mom_.current_optimizer = options_mom_.optimizer_vec{optim_iter};
+ if options_mom_.optimizer_vec{optim_iter}==0
+ % no minimization, evaluate objective at current values
+ xparam1 = xparam0;
+ hessian_xparam1 = hessian_xparam0;
+ fval = feval(objective_function, xparam1, data_moments, weighting_info, options_mom_, M_, estim_params_, bayestopt_, BoundsInfo, dr, endo_steady_state, exo_steady_state, exo_det_steady_state);
+ else
+ [xparam1, fval, exitflag, hessian_xparam1, options_mom_, Scale, new_rat_hess_info] = dynare_minimize_objective(objective_function, xparam0, options_mom_.optimizer_vec{optim_iter}, options_mom_, [BoundsInfo.lb BoundsInfo.ub], bayestopt_.name, bayestopt_, hessian_xparam0,...
+ data_moments, weighting_info, options_mom_, M_, estim_params_, bayestopt_, BoundsInfo, dr, endo_steady_state, exo_steady_state, exo_det_steady_state);
+ end
+ fprintf('\nMode Compute Iteration %d: Value of minimized moment distance objective function: %12.10f.\n',optim_iter,fval);
+ if options_mom_.mom.verbose
+ fprintf('\n''verbose'' option: ');
+ if options_mom_.cova_compute
+ if options_mom_.optimizer_vec{optim_iter}==0
+ hessian_xparam1_iter = hessian_xparam1;
+ else
+ fprintf('computing hessian');
+ hessian_xparam1_iter = hessian(objective_function, xparam1, options_mom_.gstep,...
+ data_moments, weighting_info, options_mom_, M_, estim_params_, bayestopt_, BoundsInfo, dr, endo_steady_state, exo_steady_state, exo_det_steady_state);
+ hessian_xparam1_iter = reshape(hessian_xparam1_iter, length(xparam1), length(xparam1));
+ end
+ hsd_iter = sqrt(diag(hessian_xparam1_iter));
+ invhessian_xparam1_iter = inv(hessian_xparam1_iter./(hsd_iter*hsd_iter'))./(hsd_iter*hsd_iter');
+ std_via_invhessian_xparam1_iter = sqrt(diag(invhessian_xparam1_iter));
+ else
+ std_via_invhessian_xparam1_iter = NaN(size(xparam1));
+ end
+ fprintf(' and displaying intermediate results.');
+ if doBayesianEstimation
+ tbl_title_iter = sprintf('BAYESIAN %s (OPTIM ITERATION %d) VERBOSE',strrep(options_mom_.mom.mom_method,'_',' '),optim_iter);
+ field_name_iter = sprintf('posterior_iter_%d',optim_iter);
+ else
+ tbl_title_iter = sprintf('FREQUENTIST %s (OPTIM ITERATION %d) VERBOSE',strrep(options_mom_.mom.mom_method,'_',' '),optim_iter);
+ field_name_iter = sprintf('iter_%d',optim_iter);
+ end
+ mom_verbose.(field_name_iter) = display_estimation_results_table(xparam1,std_via_invhessian_xparam1_iter,M_,options_mom_,estim_params_,bayestopt_,[],prior_dist_names,tbl_title_iter,field_name_iter);
+ end
+ xparam0 = xparam1;
+ hessian_xparam0 = hessian_xparam1;
+end
+
+if options_mom_.cova_compute
+ if options_mom_.mom.verbose
+ hessian_xparam1 = hessian_xparam1_iter;
+ else
+ fprintf('\nComputing Hessian at the mode.\n');
+ hessian_xparam1 = hessian(objective_function, xparam1, options_mom_.gstep,...
+ data_moments, weighting_info, options_mom_, M_, estim_params_, bayestopt_, BoundsInfo, dr, endo_steady_state, exo_steady_state, exo_det_steady_state);
+ hessian_xparam1 = reshape(hessian_xparam1, length(xparam1), length(xparam1));
+ end
+end
+parameter_names = bayestopt_.name;
+if options_mom_.cova_compute || options_mom_.mode_compute==5 || options_mom_.mode_compute==6
+ hh = hessian_xparam1;
+ save([M_.dname filesep 'method_of_moments' filesep M_.fname '_mode.mat'],'xparam1','hh','parameter_names','fval');
+else
+ save([M_.dname filesep 'method_of_moments' filesep M_.fname '_mode.mat'],'xparam1','parameter_names','fval');
+end
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