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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
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4
matlab/perfect-foresight-models/make_y_.m
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@ -51,6 +51,8 @@ else
if ~isempty(ys0_) if ~isempty(ys0_)
error('histval and endval cannot be used simultaneously') error('histval and endval cannot be used simultaneously')
end 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)]; oo_.steady_state*ones(1,options_.periods+M_.maximum_lead)];
end end

10
matlab/perfect-foresight-models/perfect_foresight_problem.m
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@ -1,10 +1,10 @@
function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function, Y0, YT, ... function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function, Y0, YT, ...
exo_simul, params, steady_state, ... 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_J1, i_cols_1, i_cols_T, ...
i_cols_j,nnzJ) i_cols_j,nnzJ)
% function perfect_foresight_problem(x, model_dynamic, Y0, YT,exo_simul, % function [residuals,JJacobian] = perfect_foresight_problem(x, model_dynamic, Y0, YT,exo_simul,
% params, steady_state, periods, ny, i_cols,i_cols_J1, i_cols_1, % params, steady_state, maximum_lag, periods, ny, i_cols,i_cols_J1, i_cols_1,
% i_cols_T, i_cols_j, nnzA) % i_cols_T, i_cols_j, nnzA)
% computes the residuals and th Jacobian matrix % computes the residuals and th Jacobian matrix
% for a perfect foresight problem over T periods. % for a perfect foresight problem over T periods.
@ -19,7 +19,7 @@ function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function,
% SPECIAL REQUIREMENTS % SPECIAL REQUIREMENTS
% None. % None.
% Copyright (C) 1996-2014 Dynare Team % Copyright (C) 1996-2015 Dynare Team
% %
% This file is part of Dynare. % This file is part of Dynare.
% %
@ -47,7 +47,7 @@ function [residuals,JJacobian] = perfect_foresight_problem(y, dynamic_function,
i_rows = 1:ny; i_rows = 1:ny;
i_cols_J = i_cols; i_cols_J = i_cols;
for it = 2:(T+1) for it = maximum_lag+(1:T)
if nargout == 1 if nargout == 1
residuals(i_rows) = dynamic_function(YY(i_cols),exo_simul, params, ... residuals(i_rows) = dynamic_function(YY(i_cols),exo_simul, params, ...
steady_state,it); steady_state,it);

4
matlab/perfect-foresight-models/perfect_foresight_solver.m
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@ -56,7 +56,7 @@ if options_.debug
end end
initperiods = 1:M_.maximum_lag; 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_); oo_ = simulation_core(options_, M_, oo_);
@ -116,7 +116,7 @@ if ~oo_.deterministic_simulation.status && ~options_.no_homotopy
if isequal(iteration,1) if isequal(iteration,1)
oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead) = endoinit(:,1:options_.periods); oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead) = endoinit(:,1:options_.periods);
elseif path_with_nans || path_with_cplx 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 end
saved_endo_simul = oo_.endo_simul; saved_endo_simul = oo_.endo_simul;

4
matlab/perfect-foresight-models/private/simulation_core.m
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@ -82,7 +82,7 @@ else
[y,info] = dynare_solve(@perfect_foresight_problem,z(:),options_, ... [y,info] = dynare_solve(@perfect_foresight_problem,z(:),options_, ...
str2func([M_.fname '_dynamic']),y0,yT, ... str2func([M_.fname '_dynamic']),y0,yT, ...
oo_.exo_simul,M_.params,oo_.steady_state, ... 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, ... i_cols_J1, i_cols_1, i_cols_T, i_cols_j, ...
M_.NNZDerivatives(1)); M_.NNZDerivatives(1));
if all(imag(y)<.1*options_.dynatol.f) if all(imag(y)<.1*options_.dynatol.f)
@ -122,7 +122,7 @@ if nargout>1
else else
residuals = perfect_foresight_problem(yy(:),str2func([M_.fname '_dynamic']), y0, yT, ... residuals = perfect_foresight_problem(yy(:),str2func([M_.fname '_dynamic']), y0, yT, ...
oo_.exo_simul,M_.params,oo_.steady_state, ... 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, ... i_cols_J1, i_cols_1, i_cols_T, i_cols_j, ...
M_.NNZDerivatives(1)); M_.NNZDerivatives(1));
end end