stepan
/
dynare
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

solve bugs when there are lags of exogenous variables on more than one 

period in deterministic models.
time-shift
Michel Juillard 2015-05-27 12:22:32 +02:00
parent eefa7bb70a
commit 127730d731
4 changed files with 12 additions and 10 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
matlab/perfect-foresight-models/make_y_.m
View File

@ -51,6 +51,8 @@ else
if ~isempty(ys0_)
error('histval and endval cannot be used simultaneously')
end
oo_.endo_simul = [M_.endo_histval ...
% the first NaNs take care of the case where there are lags > 1 on
% exogenous variables
oo_.endo_simul = [NaN(M_.endo_nbr,M_.maximum_lag-1) M_.endo_histval ...
oo_.steady_state*ones(1,options_.periods+M_.maximum_lead)];
end

10
matlab/perfect-foresight-models/perfect_foresight_problem.m
View File

@ -1,10 +1,10 @@
function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function, Y0, YT, ...
exo_simul, params, steady_state, ...
T, ny, i_cols, ...
maximum_lag, T, ny, i_cols, ...
i_cols_J1, i_cols_1, i_cols_T, ...
i_cols_j,nnzJ)
% function perfect_foresight_problem(x, model_dynamic, Y0, YT,exo_simul,
% params, steady_state, periods, ny, i_cols,i_cols_J1, i_cols_1,
% function [residuals,JJacobian] = perfect_foresight_problem(x, model_dynamic, Y0, YT,exo_simul,
% params, steady_state, maximum_lag, periods, ny, i_cols,i_cols_J1, i_cols_1,
% i_cols_T, i_cols_j, nnzA)
% computes the residuals and th Jacobian matrix
% for a perfect foresight problem over T periods.
@ -19,7 +19,7 @@ function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function,
% SPECIAL REQUIREMENTS
% None.
% Copyright (C) 1996-2014 Dynare Team
% Copyright (C) 1996-2015 Dynare Team
%
% This file is part of Dynare.
%
@ -47,7 +47,7 @@ function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function,
i_rows = 1:ny;
i_cols_J = i_cols;
for it = 2:(T+1)
for it = maximum_lag+(1:T)
if nargout == 1
residuals(i_rows) = dynamic_function(YY(i_cols),exo_simul, params, ...
steady_state,it);

4
matlab/perfect-foresight-models/perfect_foresight_solver.m
View File

@ -56,7 +56,7 @@ if options_.debug
end
initperiods = 1:M_.maximum_lag;
lastperiods = (M_.maximum_endo_lag+options_.periods+1):(M_.maximum_endo_lag+options_.periods+M_.maximum_endo_lead);
lastperiods = (M_.maximum_lag+options_.periods+1):(M_.maximum_lag+options_.periods+M_.maximum_lead);
oo_ = simulation_core(options_, M_, oo_);
@ -116,7 +116,7 @@ if ~oo_.deterministic_simulation.status && ~options_.no_homotopy
if isequal(iteration,1)
oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead) = endoinit(:,1:options_.periods);
elseif path_with_nans || path_with_cplx
oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead) = saved_endo_simul(:,1+M_.maximum_endo_lag:end-M_.maximum_endo_lead);
oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead) = saved_endo_simul(:,1+M_.maximum_lag:end-M_.maximum_lead);
end
saved_endo_simul = oo_.endo_simul;

4
matlab/perfect-foresight-models/private/simulation_core.m
View File

@ -82,7 +82,7 @@ else
[y,info] = dynare_solve(@perfect_foresight_problem,z(:),options_, ...
str2func([M_.fname '_dynamic']),y0,yT, ...
oo_.exo_simul,M_.params,oo_.steady_state, ...
options_.periods,M_.endo_nbr,i_cols, ...
M_.maximum_lag,options_.periods,M_.endo_nbr,i_cols, ...
i_cols_J1, i_cols_1, i_cols_T, i_cols_j, ...
M_.NNZDerivatives(1));
if all(imag(y)<.1*options_.dynatol.f)
@ -122,7 +122,7 @@ if nargout>1
else
residuals = perfect_foresight_problem(yy(:),str2func([M_.fname '_dynamic']), y0, yT, ...
oo_.exo_simul,M_.params,oo_.steady_state, ...
options_.periods,M_.endo_nbr,i_cols, ...
M_.maximum_lag,options_.periods,M_.endo_nbr,i_cols, ...
i_cols_J1, i_cols_1, i_cols_T, i_cols_j, ...
M_.NNZDerivatives(1));
end