diff --git a/matlab/det_forecast.m b/matlab/det_forecast.m
deleted file mode 100644
index dceb694386243d47324cc660f6a5d5372a55e1f4..0000000000000000000000000000000000000000
--- a/matlab/det_forecast.m
+++ /dev/null
@@ -1,163 +0,0 @@
-function det_cond_forecast(constrained_paths, constrained_vars, options_cond_fcst, constrained_perfect_foresight)
-% Computes forecasts using the schocks retrieved from a condition forecast for a deterministic model.
-%
-% INPUTS
-% o constrained_paths [double] m*p array, where m is the number of constrained endogenous variables and p is the number of constrained periods.
-% o constrained_vars [char] m*x array holding the names of the controlled endogenous variables.
-% o options_cond_fcst [structure] containing the options. The fields are:
-% + replic [integer] scalar, number of monte carlo simulations.
-% + parameter_set [char] values of the estimated parameters:
-% "posterior_mode",
-% "posterior_mean",
-% "posterior_median",
-% "prior_mode" or
-% "prior mean".
-% [double] np*1 array, values of the estimated parameters.
-% + controlled_varexo [char] m*x array, list of controlled exogenous variables.
-% + conf_sig [double] scalar in [0,1], probability mass covered by the confidence bands.
-% o constrained_perfect_foresight [double] m*1 array indicating if the endogenous variables path is perfectly foresight (1) or is a surprise (0)
-%
-%
-% OUTPUTS
-% None.
-%
-% SPECIAL REQUIREMENTS
-% This routine has to be called after an estimation statement or an estimated_params block.
-%
-% REMARKS
-% [1] Results are stored in a structure which is saved in a mat file called conditional_forecasts.mat.
-% [2] Use the function plot_icforecast to plot the results.
-
-% Copyright (C) 2013 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_ oo_ M_
-
-if ~isfield(options_cond_fcst,'periods') || isempty(options_cond_fcst.periods)
- options_cond_fcst.periods = 60;
-end
-
-maximum_lag = M_.maximum_lag;
-maximum_lead = M_.maximum_lead;
-ys = oo_.steady_state;
-ny = size(ys,1);
-xs = [oo_.exo_steady_state ; oo_.exo_det_steady_state];
-nx = size(xs,1);
-
-constrained_periods = size(constrained_paths,2);
-n_endo_constrained = size(constrained_vars,1);
-if isfield(options_cond_fcst,'controlled_varexo')
- n_control_exo = size(options_cond_fcst.controlled_varexo, 1);
- if n_control_exo ~= n_endo_constrained
- error(['det_cond_forecast:: the number of exogenous controlled variables (' int2str(n_control_exo) ') has to be equal to the number of constrained endogenous variabes (' int2str(n_endo_constrained) ')'])
- end;
-else
- error('det_cond_forecast:: to run a deterministic conditional forecast you have to specified the exogenous variables controlled using the option controlled_varex in forecast command');
-end;
-
-exo_names = M_.exo_names;
-controlled_varexo = zeros(1,n_control_exo);
-for i = 1:nx
- for j=1:n_control_exo
- if strcmp(exo_names(i,:), options_cond_fcst.controlled_varexo(j,:))
- controlled_varexo(j) = i;
- end
- end
-end
-
-save_options_initval_file = options_.initval_file;
-options_.initval_file = '__';
-
-[pos_constrained_pf, junk] = find(constrained_perfect_foresight);
-indx_endo_solve_pf = constrained_vars(pos_constrained_pf);
-if isempty(indx_endo_solve_pf)
- pf = 0;
-else
- pf = length(indx_endo_solve_pf);
-end;
-indx_endo_solve_surprise = setdiff(constrained_vars, indx_endo_solve_pf);
-
-if isempty(indx_endo_solve_surprise)
- surprise = 0;
-else
- surprise = length(indx_endo_solve_surprise);
-end;
-
-eps = options_.solve_tolf;
-maxit = options_.simul.maxit;
-
-% Check the solution using a unconditional forecast (soft tune)
-
-initial_conditions = oo_.steady_state;
-terminal_conditions = oo_.steady_state;
-exo = oo_.exo_simul;
-T = options_.periods + 2;
-endo_simul = zeros(ny, T);
-endo_simul(:,1) = initial_conditions;
-endo_simul(:,T) = initial_conditions;
-exo_simul = zeros(T, nx);
-exo_simul(1,:) = [oo_.exo_steady_state' oo_.exo_det_steady_state'];
-exo_simul(T,:) = [oo_.exo_steady_state' oo_.exo_det_steady_state'];
-past_val = 0;
-
-if pf && ~surprise
- make_ex_;
- make_y_;
- oo_.endo_simul(:,1) = initial_conditions;
- oo_.endo_simul(:,options_.periods + 2) = terminal_conditions;
- %oo_.exo_simul = repmat(oo_.exo_steady_state, options_.periods + 2, 1);
- oo_.exo_simul = exo;
- simul();
- endo_simul = oo_.endo_simul;
- exo_simul = oo_.exo_simul;
-else
- for t=1:constrained_periods
- make_ex_;
- make_y_;
- disp(['t=' int2str(t) ' constrained_periods=' int2str(constrained_periods)]);
- oo_.endo_simul(:,1) = initial_conditions;
- oo_.endo_simul(:,options_.periods + 2) = terminal_conditions;
- time_index_constraint = maximum_lag + 1:maximum_lag + constrained_periods - t + 1;
- if t <= constrained_periods
- for j = controlled_varexo
- if constrained_perfect_foresight(j)
- for time = time_index_constraint;
- oo_.exo_simul(time,j) = exo(past_val + time,j);
- end;
- oo_.exo_simul(time+1, j)= oo_.exo_steady_state(j);
- else
- oo_.exo_simul(maximum_lag + 1,j) = exo(maximum_lag + t,j);
- end;
- end;
- else
- tmp = size(oo_.exo_simul,1);
- oo_.exo_simul = repmat(oo_.exo_steady_state',tmp,1);
- end;
- past_val = past_val + length(time_index_constraint);
- simul();
- initial_conditions = oo_.endo_simul(:,2);
- if t < constrained_periods
- endo_simul(:,t+1) = initial_conditions;
- exo_simul(t+1,:) = oo_.exo_simul(2,:);
- else
- endo_simul(:,t + 1:t + options_cond_fcst.periods + maximum_lead) = oo_.endo_simul(:,maximum_lag + 1:maximum_lag + options_cond_fcst.periods + maximum_lead);
- exo_simul(t+1,:) = oo_.exo_simul(2,:);
- end;
- end;
-end;
-oo_.endo_simul = endo_simul;
-oo_.exo_simul = exo_simul;