148 lines
7.2 KiB
Matlab
148 lines
7.2 KiB
Matlab
function perfect_foresight_with_expectation_errors_setup
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% Copyright © 2021-2023 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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global M_ oo_ options_
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if ~isempty(M_.endo_histval)
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error('perfect_foresight_with_expectation_errors_setup: cannot be used in conjunction with histval')
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end
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if ~isempty(oo_.initval_series)
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error('perfect_foresight_with_expectation_errors_setup: cannot be used in conjunction with histval_file/initval_file')
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end
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periods = options_.periods;
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%% Initialize informational structures
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oo_.pfwee.terminal_info = NaN(M_.exo_nbr, periods); % 2nd dimension is informational time
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oo_.pfwee.shocks_info = NaN(M_.exo_nbr, periods, periods); % 2nd dimension is real time, 3rd dimension is informational time
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if exist(options_.datafile, 'file')
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if ~isempty(M_.det_shocks) || ~isempty(M_.learnt_shocks) || ~isempty(oo_.initial_steady_state) || ~isempty(M_.learnt_endval)
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warning('perfect_foresight_with_expectation_errors_setup: since you passed the datafile option, the contents of shocks and endval blocks will be ignored')
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end
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%% Read CSV file
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%% We can’t use readcell (only in MATLAB ≥ R2019a), so instead rely on csvread and manual hacks
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% Read numeric data, skipping first row and first column
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raw_csv = csvread(options_.datafile, 1, 1);
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if size(raw_csv, 1)-2 ~= periods
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error(['perfect_foresight_with_expectation_errors_setup: the number of rows in ' options_.datafile ' does not match the periods setting'])
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end
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% Read first line (exogenous variable names)
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fid = fopen(options_.datafile);
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csv_first_line = fgetl(fid);
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fclose(fid);
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exo_header_names = strsplit(csv_first_line, ',');
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exo_header_names = exo_header_names(2:end); % Remove first column
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if numel(exo_header_names) ~= size(raw_csv, 2)
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error(['perfect_foresight_with_expectation_errors_setup: first line malformed in ' options_.datafile])
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end
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%% Create and fill structures containing information sets
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for i = 1:size(raw_csv, 2)
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exo_id = strmatch(exo_header_names{i}, M_.exo_names, 'exact');
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period_id = raw_csv(1, i);
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% Ignore irrelevant periods when copying shocks information
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oo_.pfwee.shocks_info(exo_id, period_id:end, period_id) = raw_csv(1+period_id:end-1, i);
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oo_.pfwee.terminal_info(exo_id, period_id) = raw_csv(end, i);
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end
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else
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%% No datafile option given, use the contents of shocks and endval blocks
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if isempty(M_.learnt_shocks) && isempty(M_.learnt_endval)
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warning('perfect_foresight_with_expectation_errors_setup: there is no shocks(learnt_in=...) or endval(learnt_in=...) block, and you did not pass the datafile option, so there is no point in using this command')
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end
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%% Initialize information set at period 1 using “bare” shocks and endval blocks (or initval if there is no endval)
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oo_.pfwee.terminal_info(:, 1) = oo_.exo_steady_state;
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oo_.pfwee.shocks_info(:, :, 1) = repmat(oo_.exo_steady_state, 1, periods);
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for i = 1:length(M_.det_shocks)
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prds = M_.det_shocks(i).periods;
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exo_id = M_.det_shocks(i).exo_id;
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v = M_.det_shocks(i).value;
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if ~M_.det_shocks(i).exo_det
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switch M_.det_shocks(i).type
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case 'level'
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oo_.pfwee.shocks_info(exo_id, prds, 1) = v;
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case 'multiply_steady_state'
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oo_.pfwee.shocks_info(exo_id, prds, 1) = oo_.exo_steady_state(exo_id) * v;
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case 'multiply_initial_steady_state'
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if isempty(oo_.initial_exo_steady_state)
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error('Option relative_to_initval of mshocks block cannot be used without an endval block')
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end
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oo_.pfwee.shocks_info(exo_id, prds, 1) = oo_.initial_exo_steady_state(exo_id) * v;
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end
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end
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end
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%% Construct information sets for subsequent informational periods
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for p = 2:periods
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oo_.pfwee.terminal_info(:, p) = oo_.pfwee.terminal_info(:, p-1);
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oo_.pfwee.shocks_info(:, :, p) = oo_.pfwee.shocks_info(:, :, p-1);
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if ~isempty(M_.learnt_endval)
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idx = find([M_.learnt_endval.learnt_in] == p);
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for i = 1:length(idx)
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j = idx(i);
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exo_id = M_.learnt_endval(j).exo_id;
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switch M_.learnt_endval(j).type
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case 'level'
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oo_.pfwee.terminal_info(exo_id, p) = M_.learnt_endval(j).value;
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case 'add'
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oo_.pfwee.terminal_info(exo_id, p) = oo_.pfwee.terminal_info(exo_id, p-1) + M_.learnt_endval(j).value;
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case 'multiply'
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oo_.pfwee.terminal_info(exo_id, p) = oo_.pfwee.terminal_info(exo_id, p-1) * M_.learnt_endval(j).value;
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otherwise
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error('Unknown type in M_.learnt_endval')
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end
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oo_.pfwee.shocks_info(exo_id, p:end, p) = oo_.pfwee.terminal_info(exo_id, p);
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end
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end
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if ~isempty(M_.learnt_shocks)
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idx = find([M_.learnt_shocks.learnt_in] == p);
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for i = 1:length(idx)
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j = idx(i);
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exo_id = M_.learnt_shocks(j).exo_id;
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prds = M_.learnt_shocks(j).periods;
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switch M_.learnt_shocks(j).type
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case 'level'
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oo_.pfwee.shocks_info(exo_id, prds, p) = M_.learnt_shocks(j).value;
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case 'add'
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oo_.pfwee.shocks_info(exo_id, prds, p) = oo_.pfwee.shocks_info(exo_id, prds, p-1) + M_.learnt_shocks(j).value;
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case 'multiply'
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oo_.pfwee.shocks_info(exo_id, prds, p) = oo_.pfwee.shocks_info(exo_id, prds, p-1) .* M_.learnt_shocks(j).value;
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case 'multiply_steady_state'
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oo_.pfwee.shocks_info(exo_id, prds, p) = oo_.pfwee.terminal_info(exo_id, p) * M_.learnt_shocks(j).value;
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otherwise
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error('Unknown type in M_.learnt_shocks')
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end
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end
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end
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end
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end
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% Build initial paths for endos and exos (only initial conditions are set, the rest is NaN)
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if isempty(oo_.initial_steady_state)
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oo_.endo_simul = repmat(oo_.steady_state, 1, M_.maximum_lag+periods+M_.maximum_lead);
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else
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oo_.endo_simul = [repmat(oo_.initial_steady_state, 1, M_.maximum_lag) repmat(oo_.steady_state, 1, periods+M_.maximum_lead)];
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end
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if isempty(oo_.initial_exo_steady_state)
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oo_.exo_simul = repmat(oo_.exo_steady_state', M_.maximum_lag+periods+M_.maximum_lead, 1);
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else
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oo_.exo_simul = [repmat(oo_.initial_exo_steady_state', M_.maximum_lag, 1); repmat(oo_.exo_steady_state', periods+M_.maximum_lead, 1)];
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end
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