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Changed the code so that if we are not able to solve for the deterministic equilibrium path 

at time t (even with the homotopic steps) then the size of the structural innovations is 
reduced (at time t *only*). The advantage of this trick is that the seed of the random 
number generator is not affected. The problem is that the structural innovations are now 
heteroscedastic. Should add something to evaluate the importance of this heteroscedasticity problem. 




git-svn-id: https://www.dynare.org/svn/dynare/trunk@3346 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
stepan 2010-01-11 16:29:50 +00:00
parent 77eec32811
commit 5f42e79bfc
1 changed files with 46 additions and 13 deletions
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59
matlab/extended_path.m
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@ -83,8 +83,18 @@ norme = 0;
% Set verbose option
verbose = 0;
for t=1:sample_size
shocks = exp(randn(1,number_of_structural_innovations)*covariance_matrix_upper_cholesky-.5*variances(positive_var_indx)');
t = 0;
new_draw = 1;
while (t<=sample_size)
t = t+1;
if new_draw
gaussian_draw = randn(1,number_of_structural_innovations);
else
gaussian_draw = .5*gaussian_draw ;
new_draw = 1;
end
shocks = exp(gaussian_draw*covariance_matrix_upper_cholesky-.5*variances(positive_var_indx)');
oo_.exo_simul(tdx,positive_var_indx) = shocks;
if init
% Compute first order solution.
@ -97,7 +107,7 @@ for t=1:sample_size
oo_.endo_simul = initial_path(:,1:end-1)*lambda + oo_.endo_simul*(1-lambda);
end
end
if init
if init
info = perfect_foresight_simulation(dr,oo_.steady_state);
else
info = perfect_foresight_simulation;
@ -109,33 +119,50 @@ for t=1:sample_size
info.iterations
end
if ~info.convergence
info = homotopic_steps(tdx,positive_var_indx,shocks,norme,.5,init);
clear homotopic_steps;
INFO = homotopic_steps(tdx,positive_var_indx,shocks,norme,.5,init);
if verbose
norme
info
end
if isnan(INFO)
t = t-1;
new_draw = 0;
else
info = INFO;
end
else
norme = sqrt(sum((shocks-1).^2,2));
end
if ~info.convergence
error('I am not able to simulate this model!')
%if ~info.convergence
% error('I am not able to simulate this model!')
%end
if new_draw
info.time = info.time+time;
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
info.time = info.time+time;
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
function info = homotopic_steps(tdx,positive_var_indx,shocks,init_weight,step,init)
global oo_
persistent number_of_calls
if isempty(number_of_calls)
number_of_calls = 1;
else
number_of_calls = number_of_calls + 1;
end
max_number_of_calls = 50;
max_iter = 100;
weight = init_weight;
verbose = 0;
iter = 0;
time = 0;
reduce_step = 0;
while iter<=100 && weight<=1
while iter<=max_iter && weight<=1
iter = iter+1;
old_weight = weight;
weight = weight+step;
@ -169,9 +196,15 @@ if reduce_step
step=step/1.5;
info = homotopic_steps(tdx,positive_var_indx,shocks,old_weight,step,init);
time = time+info.time;
elseif weight<1 && iter<100
return
end
if number_of_calls>max_number_of_calls
info = NaN;
return
end
if weight<1 && iter<max_iter
oo_.exo_simul(tdx,positive_var_indx) = shocks;
if init
if init
info = perfect_foresight_simulation(oo_.dr,oo_.steady_state);
else
info = perfect_foresight_simulation;