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Added homotopic steps on the size of the shocks. 

git-svn-id: https://www.dynare.org/svn/dynare/trunk@3148 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
stepan 2009-11-13 14:18:01 +00:00
parent ef3ee28ce8
commit c393fa92e4
1 changed files with 41 additions and 7 deletions
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48
matlab/extended_path.m
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@ -1,4 +1,4 @@
function time_series = extended_path(initial_conditions,sample_size)
function time_series = extended_path(initial_conditions,sample_size,init)
% Stochastic simulation of a non linear DSGE model using the Extended Path method (Fair and Taylor 1983). A time
% series of size T is obtained by solving T perfect foresight models.
%
@ -44,7 +44,7 @@ function time_series = extended_path(initial_conditions,sample_size)
make_ex_;
% Initialize the endogenous variables.
make_y_;
make_y_;
% Initialize the output array.
time_series = NaN(M_.endo_nbr,sample_size+1);
@ -58,10 +58,44 @@ function time_series = extended_path(initial_conditions,sample_size)
tdx = M_.maximum_lag+1;
for t=1:sample_size
oo_.exo_simul(tdx,positive_var_indx) = exp(randn(1,number_of_structural_innovations)*covariance_matrix_upper_cholesky-.5*variances(positive_var_indx)');
perfect_foresight_simulation;
for t=1:sample_size
shocks = exp(randn(1,number_of_structural_innovations)*covariance_matrix_upper_cholesky-.5*variances(positive_var_indx)');
oo_.exo_simul(tdx,positive_var_indx) = shocks;
info = perfect_foresight_simulation;
if ~info.convergence
disp('homotopy')
info = homotopic_steps(tdx,positive_var_indx,shocks,0,.5);
end
if ~info.convergence
disp('merdre!')
end
time_series(:,t+1) = oo_.endo_simul(:,tdx);
oo_.endo_simul(:,1:end-1) = oo_.endo_simul(:,2:end);
oo_.endo_simul(:,end) = oo_.steady_state;
end
oo_.endo_simul(:,end) = oo_.steady_state;
end
function info = homotopic_steps(tdx,positive_var_indx,shocks,init_weight,step)
global oo_
weight = init_weight;
max_iter = 100;
iter = 0;
reduce_step = 0;
while iter<=100 && weight<=1
iter = iter+1;
old_weight = weight;
weight = weight+step;
oo_.exo_simul(tdx,positive_var_indx) = weight*shocks+(1-weight);
info = perfect_foresight_simulation;
if ~info.convergence
reduce_step = 1;
break
end
end
if reduce_step
step=step/1.5;
info = homotopic_steps(tdx,positive_var_indx,shocks,old_weight,step);
elseif weight<1 && iter<100
oo_.exo_simul(tdx,positive_var_indx) = shocks;
info = perfect_foresight_simulation;
end