125 lines
4.7 KiB
Matlab
125 lines
4.7 KiB
Matlab
function [residuals, info] = calibrateresiduals(dbase, info, DynareModel)
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% Compute residuals in a backward model. Residuals are unobserved exogenous
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% variables appearing additively in equations and without lags. An equation
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% cannot have more than one residual, and a residual cannot appear in more
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% than one equation.
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%
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% INPUTS
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% - dbase [dseries] Object containing all the endogenous and observed exogenous variables.
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% - info [struct] Informations about the residuals.
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% - DynareModel [struct] M_ as produced by the preprocessor.
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%
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% OUTPUTS
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% - residuals [dseries] Object containing the identified residuals.
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% - info [struct] Informations about the residuals.
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%
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% REMARKS
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% The first two input arguments are the output of checkdatabaseforinversion
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% routine.
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% Copyright (C) 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 <http://www.gnu.org/licenses/>.
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% Get function handle for the dynamic model
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model_dynamic = str2func([DynareModel.fname,'.dynamic']);
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% Get data for all the endogenous variables.
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ydata = dbase{info.endonames{:}}.data;
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% Get data for all the exogenous variables. Missing exogenous variables, to be solved for, have NaN values.
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exogenousvariablesindbase = intersect(info.exonames, dbase.name);
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residuals = dseries(NaN(dbase.nobs, length(info.residuals)), dbase.init, info.residuals);
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allexogenousvariables = [dbase{exogenousvariablesindbase{:}}, residuals];
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allexogenousvariables = allexogenousvariables{info.exonames{:}};
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xdata = allexogenousvariables.data;
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% Evaluate the dynamic equation
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n = size(ydata, 2);
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c = find(DynareModel.lead_lag_incidence');
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y = [ydata(1,:)'; ydata(2,:)'];
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y = y(c);
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r = model_dynamic(y, xdata, DynareModel.params, zeros(n, 1), 2);
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% Check that the number of equations evaluating to NaN matches the number of residuals
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idr = find(isnan(r));
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if ~isequal(length(idr), residuals.vobs)
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error('Each residual should appear in only one equation, and an equation cannot have more than one residual!')
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end
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% Check that the non NaN equations have zero residuals (model and data consistency).
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ido = setdiff(1:n, idr);
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if ~isempty(find(abs(r(ido))>1e-6))
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disp('Provided data and model are not consistent in equations:')
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idx = find(abs(r)>1e-6);
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c1 = 'Equation';
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c1 = strvcat(c1, '--------');
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for i = 1:length(idx)
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c1 = strvcat(c1, sprintf(' %s', num2str(idx(i))));
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end
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c2 = 'Residual';
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c2 = strvcat(c2, '--------');
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for i = 1:length(idx)
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c2 = strvcat(c2, sprintf('%s', num2str(r(idx(i)))));
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end
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c2 = strvcat(c2(1, :), repmat('-', 1, size(c2, 2)), c2(3:end,:));
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c3 = repmat(' | ', size(c2, 1), 1);
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c4 = repmat(' ', size(c2, 1), 1);
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cc = [c4, c1, c3, c2];
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skipline()
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disp(cc)
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skipline()
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disp('Please check model and dataset.')
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end
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% Associate the residuals with equations equations evaluating to NaNs.
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info.equations = cell(residuals.vobs, 1);
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info.residualindex = cell(residuals.vobs, 1);
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for i = 1:residuals.vobs
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residualname = residuals.name{i};
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info.residualindex(i) = {strmatch(residualname, allexogenousvariables.name, 'exact')};
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tmpxdata = xdata;
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tmpxdata(2, info.residualindex{i}) = 0;
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r = model_dynamic(y, tmpxdata, DynareModel.params, zeros(n, 1), 2);
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info.equations(i) = { idr(find(~isnan(r(idr))))};
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end
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c1 = 'Residual';
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for i=1:length(info.residuals)
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c1 = strvcat(c1, sprintf('%s', info.residuals{i}));
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end
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c1 = strvcat(c1(1,:), repmat('-', 1, size(c1, 2)), c1(2:end,:));
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c2 = 'Equation';
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for i=1:length(info.residuals)
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c2 = strvcat(c2, sprintf(' %s', num2str(info.equations{i})));
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end
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c2 = strvcat(c2(1,:), repmat('-', 1, size(c2, 2)), c2(2:end,:));
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c3 = repmat(' | ', size(c2, 1), 1);
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c4 = repmat(' ', size(c2, 1), 1);
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cc = [c4, c1, c3, c2];
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skipline()
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disp(cc)
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skipline()
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% Compute residuals
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xdata(:,cell2mat(info.residualindex)) = 0;
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rdata = NaN(residuals.nobs, residuals.vobs);
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for t=2:size(xdata, 1)
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y = transpose([ydata(t-1,:); ydata(t,:)]);
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r = model_dynamic(y(c), xdata, DynareModel.params, zeros(n, 1), t);
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rdata(t,:) = transpose(r(cell2mat(info.equations)));
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end
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residuals = dseries(rdata, dbase.init, info.residuals); |