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function [resids, grad, state_out, E, M_, out] = match_function(err_0, obs_list,current_obs, opts_simul,...
M_, dr, endo_steady_state, exo_steady_state, exo_det_steady_state, options_)
% function [resids, grad, stateout, E, M_, out] = match_function(err_0, obs_list,current_obs, opts_simul,...
% M_, dr, endo_steady_state, exo_steady_state, exo_det_steady_state, options_)
% Outputs:
% - resids [double] [n_exo by 1] vector of residuals
% - grad [double] [n by n_exo] gradient (response of observables to shocks)
% - state_out [double] [ny by 1] value of endogenous variables
% - E [double] response of endogenous variables to shocks
% - M_ [structure] Matlab's structure describing the model (M_).
% - out [structure] Occbin's results structure
%
% Inputs
% - err_ [double] value of shocks
% - obs_list [cell] names of observables
% - current_obs [double] [1 by n_obs] current value of observables
% - opts_simul [structure] Structure with simulation options
% - M_ [structure] Matlab's structure describing the model (M_).
% - dr [structure] Reduced form model.
% - endo_steady_state [vector] steady state value for endogenous variables
% - exo_steady_state [vector] steady state value for exogenous variables
% - exo_det_steady_state [vector] steady state value for exogenous deterministic variables
% - options_ [structure] Matlab's structure describing the current options (options_).
% Original authors: Pablo Cuba-Borda, Luca Guerrieri, Matteo Iacoviello, and Molin Zhong
% Original file downloaded from:
% http://www.lguerrieri.com/jae-replication.zip
% Adapted for Dynare by Dynare Team.
%
% This code is in the public domain and may be used freely.
% However the authors would appreciate acknowledgement of the source by
% citation of any of the following papers:
%
% Pablo Cuba-Borda, Luca Guerrieri, Matteo Iacoviello, and Molin Zhong (2019): "Likelihood evaluation of models
% with occasionally binding constraints", Journal of Applied Econometrics,
% 34(7), 1073-1085
opts_simul.SHOCKS = err_0';
options_.occbin.simul=opts_simul;
options_.occbin.simul.full_output=1;
options_.noprint = 1;
[~, out, ss] = occbin.solver(M_,options_,dr,endo_steady_state,exo_steady_state,exo_det_steady_state);
nobs = size(obs_list,1);
resids = zeros(nobs,1);
if ~out.error_flag
state_out= out.piecewise(1,:)' - out.ys;
E = ss.R(:,opts_simul.exo_pos);
grad = ss.R(opts_simul.varobs_id,opts_simul.exo_pos);
resids = (out.piecewise(1,opts_simul.varobs_id)-current_obs)'; %-out.endo_ss.(obs_list{this_obs});
else
grad = NaN(length(opts_simul.varobs_id),length(opts_simul.exo_pos));
resids = resids+100;
end
end
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