1function [endogenousvariables, exogenousvariables] = model_inversion(constraints, ... 2 exogenousvariables, ... 3 initialconditions, DynareModel, DynareOptions, DynareOutput) 4 5% INPUTS 6% - constraints [dseries] with N constrained endogenous variables from t1 to t2. 7% - exogenousvariables [dseries] with Q exogenous variables. 8% - initialconditions [dseries] with M endogenous variables starting before t1 (M initialcond must contain at least the state variables). 9% - DynareModel [struct] M_, Dynare global structure containing informations related to the model. 10% - DynareOptions [struct] options_, Dynare global structure containing all the options. 11% 12% OUTPUTS 13% - endogenous [dseries] 14% - exogenous [dseries] 15% 16% REMARKS 17 18% Copyright (C) 2018-2019 Dynare Team 19% 20% This file is part of Dynare. 21% 22% Dynare is free software: you can redistribute it and/or modify 23% it under the terms of the GNU General Public License as published by 24% the Free Software Foundation, either version 3 of the License, or 25% (at your option) any later version. 26% 27% Dynare is distributed in the hope that it will be useful, 28% but WITHOUT ANY WARRANTY; without even the implied warranty of 29% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 30% GNU General Public License for more details. 31% 32% You should have received a copy of the GNU General Public License 33% along with Dynare. If not, see <http://www.gnu.org/licenses/>. 34 35if ~isequal(nargin, 6) 36 error('model_inversion: This routine require six input arguments!') 37end 38 39if ~isdseries(constraints) 40 error('model_inversion: First input argument must be a dseries object!') 41end 42 43if ~isdseries(exogenousvariables) 44 error('model_inversion: Second input argument must be a dseries object!') 45end 46 47if ~isempty(initialconditions) && ~isdseries(initialconditions) 48 error('model_inversion: Third input argument must be a dseries object!') 49end 50 51if ~isstruct(DynareModel) 52 error('model_inversion: Last input argument must be structures (M_)!') 53end 54 55% Set range where the endogenous variables are constrained. 56crange = constraints.dates; 57 58% Check that the number of instruments match the number of constrained endogenous variables. 59instruments = exogenousvariables(crange); 60freeinnovations = instruments.name(find(all(isnan(instruments)))); 61if ~isequal(length(freeinnovations), constraints.vobs) 62 error('The number of instruments must be equal to the number of constrained variables!') 63end 64 65% Check if some of the exogenous variables are given. 66observed_exogenous_variables_flag = false; 67if exogenousvariables.vobs>constraints.vobs 68 observed_exogenous_variables_flag = true; 69end 70 71if DynareModel.maximum_lag 72 % Add auxiliary variables in initialconditions object. 73 initialconditions = checkdatabase(initialconditions, DynareModel, true, false); 74end 75 76% Get the list of endogenous and exogenous variables. 77endo_names = DynareModel.endo_names; 78exo_names = DynareModel.exo_names; 79 80% Use specidalized routine if the model is backward looking. 81if ~DynareModel.maximum_lead 82 if DynareModel.maximum_lag 83 [endogenousvariables, exogenousvariables] = ... 84 backward_model_inversion(constraints, exogenousvariables, initialconditions, ... 85 endo_names, exo_names, freeinnovations, ... 86 DynareModel, DynareOptions, DynareOutput); 87 else 88 [endogenousvariables, exogenousvariables] = ... 89 static_model_inversion(constraints, exogenousvariables, ... 90 endo_names, exo_names, freeinnovations, ... 91 DynareModel, DynareOptions, DynareOutput); 92 end 93 return 94end 95 96% Initialize fplan 97fplan = init_plan(crange); 98 99% Set the exogenous observed variables. 100if observed_exogenous_variables_flag 101 list_of_observed_exogenous_variables = setdiff(exo_names, freeinnovations); 102 observed_exogenous_variables = exogenousvariables{list_of_observed_exogenous_variables{:}}; 103 for i=1:length(list_of_observed_exogenous_variables) 104 fplan = basic_plan(fplan, list_of_observed_exogenous_variables{i}, ... 105 'surprise', crange, observed_exogenous_variables{list_of_observed_exogenous_variables{i}}.data(2:length(crange)+1)); 106 end 107end 108 109% Set constrained path for the endogenous variables. 110for i = 1:constraints.vobs 111 fplan = flip_plan(fplan, constraints.name{i}, freeinnovations{i}, 'surprise', crange, transpose(constraints.data(:,i))); 112end 113 114% Identify the innovations (model inversion) 115f = det_cond_forecast(fplan, initialconditions, crange); 116 117endogenousvariables = f{endo_names{:}}; 118exogenousvariables = f{exo_names{:}};