102 lines
5.7 KiB
Matlab
102 lines
5.7 KiB
Matlab
function plan = flip_plan(plan, exogenous, endogenous, expectation_type, date, value)
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% Adds to the forecast scenario a conditional forecast shock (the path of an endogenous variable is constrained and the values compatible values of the related exogenous variable will be compued)
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%
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% INPUTS
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% o plan [structure] A structure describing the different shocks and the implied variables, the date of the shocks and the path of the shock (forecast scenario).
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% The plan structure is created by the functions init_plan, basic_plan and flip_plan
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% o exogenous [string] A string containing the name of the endogenous variable with a constrained path.
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% o endogenous [string] A string containing the name of the exogenous. This exogenous variable will be en endogenous variable when the conditional forecast will be perform.
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% o expectation_type [string] A string indicating the type of expectation: 'surprise' for an unexpected shock, and 'perfect_foresight' for a perfectly anticpated shock.
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% o date [dates] The period of the shock
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% o value [array of double] A vector of double containing the constrined path on the endogenous variable
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%
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%
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% OUTPUTS
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% plan [structure] Returns a structure containing the updated forecast scenario.
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%
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%
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% Copyright © 2013-2017 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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if ~ischar(expectation_type) || size(expectation_type,1) ~= 1
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error(['in flip_plan the fourth argument should be a string containing the simulation type (''perfect_foresight'' or ''surprise'')']);
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end
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exogenous = strtrim(exogenous);
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ix = find(strcmp(exogenous, plan.endo_names));
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if isempty(ix)
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error(['in flip_plan the second argument ' exogenous ' is not an endogenous variable']);
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end
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endogenous = strtrim(endogenous);
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iy = find(strcmp(endogenous, plan.exo_names));
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if isempty(iy)
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error(['in flip_plan the third argument ' endogenous ' is not an exogenous variable']);
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end
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sdate = length(date);
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if sdate > 1
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if date(1) < plan.date(1) || date(end) > plan.date(end)
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error(['in flip_plan the fifth argument (date=' date ') must lay inside the plan.date ' plan.date]);
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end
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else
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if date < plan.date(1) || date > plan.date(end)
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error(['in flip_plan the fifth argument (date=' date ') must lay iside the plan.date ' plan.date]);
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end
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end
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if ~isempty(plan.shock_vars_)
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common_var = find(iy == plan.shock_vars_);
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if ~isempty(common_var)
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common_date = intersect(date, plan.shock_date_{common_var});
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if ~isempty(common_date)
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if common_date.length > 1
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the_dates = [cell2mat(strings(common_date(1))) ':' cell2mat(strings(common_date(end)))];
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else
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the_dates = cell2mat(strings(common_date));
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end
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error(['Impossible case: ' plan.exo_names{plan.shock_vars_(common_var)} ' is used both as a shock and as an endogenous variable to control the path of ' plan.endo_names{ix} ' at the dates ' the_dates]);
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end
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end
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end
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i_ix = find(ix == plan.constrained_vars_);
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if isempty(i_ix)
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if isempty(plan.constrained_vars_)
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plan.constrained_vars_ = ix;
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plan.options_cond_fcst_.controlled_varexo = iy;
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if strcmp(expectation_type, 'perfect_foresight')
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plan.constrained_perfect_foresight_ = 1;
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else
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plan.constrained_perfect_foresight_ = 0;
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end
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else
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plan.constrained_vars_ = [plan.constrained_vars_ ; ix];
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plan.options_cond_fcst_.controlled_varexo = [plan.options_cond_fcst_.controlled_varexo ; iy];
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if strcmp(expectation_type, 'perfect_foresight')
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plan.constrained_perfect_foresight_ = [plan.constrained_perfect_foresight_ ; 1];
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else
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plan.constrained_perfect_foresight_ = [plan.constrained_perfect_foresight_ ; 0];
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end
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end
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plan.constrained_date_{length(plan.constrained_date_) + 1} = date;
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plan.constrained_str_date_{length(plan.constrained_str_date_) + 1} = strings(date);
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plan.constrained_int_date_{length(plan.constrained_int_date_) + 1} = date - plan.date(1) + 1;
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plan.constrained_paths_{length(plan.constrained_paths_) + 1} = value;
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elseif plan.options_cond_fcst_.controlled_varexo(i_ix) == iy % same exogenous and endogenous hard tune
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[plan.constrained_str_date_{i_ix}, i1, i2] = union(strings(date), plan.constrained_str_date_{i_ix});
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plan.constrained_date_{i_ix} = [date(i1) plan.constrained_date_{i_ix}(i2)];
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plan.constrained_int_date_{i_ix} = [date(i1) - plan.date(1) + 1; plan.constrained_int_date_{i_ix}(i2)];
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plan.constrained_paths_{i_ix} = [value(i1)'; plan.constrained_paths_{i_ix}(i2)];
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else
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error(['impossible case you have two conditional forecasts:\n - one involving ' plan.endo_names{plan.options_cond_fcst_.controlled_varexo(i_ix),:} ' as control and ' plan_exo_names{plan.constrained_vars_(ix_)} ' as constrined endogenous\n - the other involving ' plan.endo_names{plan.options_cond_fcst_.controlled_varexo(iy),:} ' as control and ' plan_exo_names{plan.constrained_vars_(ix)} ' as constrined endogenous\n']);
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end
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