Cosmetic change.
parent
824ea68b3b
commit
a88bd230a8
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@ -86,7 +86,7 @@ verbose = 0;
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t = 0;
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t = 0;
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new_draw = 1;
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new_draw = 1;
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perfect_foresight_simulation([],[],[]);
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perfect_foresight_simulation();
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while (t<=sample_size)
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while (t<=sample_size)
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t = t+1;
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t = t+1;
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@ -1,4 +1,4 @@
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function info = perfect_foresight_simulation(compute_linear_solution,steady_state, init_flag)
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function info = perfect_foresight_simulation(compute_linear_solution,steady_state)
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% Performs deterministic simulations with lead or lag on one period
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% Performs deterministic simulations with lead or lag on one period
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%
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%
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% INPUTS
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% INPUTS
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@ -37,9 +37,9 @@ function info = perfect_foresight_simulation(compute_linear_solution,steady_stat
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global M_ options_ it_ oo_
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global M_ options_ it_ oo_
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persistent lead_lag_incidence dynamic_model ny nyp nyf nrs nrc iyf iyp isp is isf isf1 iz icf ghx
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persistent lead_lag_incidence dynamic_model ny nyp nyf nrs nrc iyf iyp isp is isf isf1 iz icf ghx iflag
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if nargin==3% Initialization of the persistent variables.
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if ~nargin && isempty(iflag)% Initialization of the persistent variables.
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lead_lag_incidence = M_.lead_lag_incidence;
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lead_lag_incidence = M_.lead_lag_incidence;
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dynamic_model = [M_.fname '_dynamic'];
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dynamic_model = [M_.fname '_dynamic'];
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ny = size(oo_.endo_simul,1);
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ny = size(oo_.endo_simul,1);
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@ -56,6 +56,7 @@ if nargin==3% Initialization of the persistent variables.
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iz = 1:(ny+nyp+nyf);
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iz = 1:(ny+nyp+nyf);
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icf = 1:size(iyf,2);
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icf = 1:size(iyf,2);
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info = [];
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info = [];
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iflag = 1;
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return
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return
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end
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end
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