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extended_path: update tests models; correct bugs introduced in 

previous commit
time-shift
Michel Juillard 2014-05-12 14:17:19 +02:00
parent c83eac26bb
commit 23134353e3
9 changed files with 26 additions and 18 deletions
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26
matlab/ep/ep_problem_2.m
View File

@ -49,11 +49,11 @@ for i = 1:order+1
innovation = x;
if i <= order && j == 1
% first world, integrating future shocks
if nargin > 1
if nargout > 1
A1 = sparse([],[],[],i*ny,dimension,nnzA*world_nbr);
end
for k=1:nnodes
if nargin > 1
if nargout > 1
if i == 2
i_cols_Ap = i_cols_Ap0;
elseif i > 2
@ -86,7 +86,7 @@ for i = 1:order+1
Y(i_cols_s,1);
Y(i_cols_f,k1)];
end
if nargin > 1
if nargout > 1
[d1,jacobian] = dynamic_model(z,innovation,params,steady_state,i+1);
if i == 1
% in first period we don't keep track of
@ -102,14 +102,14 @@ for i = 1:order+1
end
res(:,i,1) = res(:,i,1)+weights(k)*d1;
end
if nargin > 1
if nargout > 1
[ir,ic,v] = find(A1);
nzA{i,j} = [ir,ic,v]';
end
elseif j > 1 + (nnodes-1)*(i-2)
% new world, using previous state of world 1 and hit
% by shocks from nodes
if nargin > 1
if nargout > 1
i_cols_Ap = i_cols_Ap0 + ny*(i-2+(nnodes-1)*(i-2)*(i-3)/2);
i_cols_Af = i_cols_Af0 + ny*(i+(nnodes-1)*i*(i-1)/2+j-2);
end
@ -118,7 +118,7 @@ for i = 1:order+1
z = [Y(i_cols_p,1);
Y(i_cols_s,j);
Y(i_cols_f,j)];
if nargin > 1
if nargout > 1
[d1,jacobian] = dynamic_model(z,innovation,params,steady_state,i+1);
i_cols_A = [i_cols_Ap; i_cols_As; i_cols_Af];
[ir,ic,v] = find(jacobian(:,i_cols_j));
@ -127,34 +127,34 @@ for i = 1:order+1
d1 = dynamic_model(z,innovation,params,steady_state,i+1);
end
res(:,i,j) = d1;
if nargin > 1
if nargout > 1
i_cols_Af = i_cols_Af + ny;
end
else
% existing worlds other than 1
if nargin > 1
if nargout > 1
i_cols_Ap = i_cols_Ap0 + ny*(i-2+(nnodes-1)*(i-2)*(i-3)/2+j-1);
i_cols_Af = i_cols_Af0 + ny*(i+(nnodes-1)*i*(i-1)/2+j-2);
end
z = [Y(i_cols_p,j);
Y(i_cols_s,j);
Y(i_cols_f,j)];
if nargin > 1
if nargout > 1
[d1,jacobian] = dynamic_model(z,innovation,params,steady_state,i+1);
i_cols_A = [i_cols_Ap; i_cols_As; i_cols_Af];
[ir,ic,v] = find(jacobian(:,i_cols_j));
nzA{i,j} = [i_rows(ir),i_cols_A(ic),v]';
i_cols_Af = i_cols_Af + ny;
else
d1 = dynamic_model(z,innovation,params,steady_state,i+1);
end
res(:,i,j) = d1;
i_cols_Af = i_cols_Af + ny;
end
i_rows = i_rows + ny;
if mod(j,nnodes) == 0
i_w_p = i_w_p + 1;
end
if nargin > 1 && i > 1
if nargout > 1 && i > 1
i_cols_As = i_cols_As + ny;
end
offset_r0 = offset_r0 + ny;
@ -168,7 +168,7 @@ for j=1:world_nbr
offset_c = ny*(order+(nnodes-1)*(order-1)*order/2+j-1);
offset_r = offset_r0+(j-1)*ny;
for i=order+2:periods
if nargin > 1
if nargout > 1
[d1,jacobian] = dynamic_model(Y(i_rows_y,j),x,params, ...
steady_state,i+1);
if i < periods
@ -187,7 +187,7 @@ for j=1:world_nbr
offset_r = offset_r + world_nbr*ny;
end
end
if nargin > 1
if nargout > 1
iA = [nzA{:}]';
A = sparse(iA(:,1),iA(:,2),iA(:,3),dimension,dimension);
end

6
matlab/ep/homotopic_steps.m
View File

@ -73,7 +73,7 @@ while weight<1
solve_stochastic_perfect_foresight_model(endo_simul0,exo_simul0,pfm,options_.ep.stochastic.quadrature.nodes,options_.ep.stochastic.order);
case 1
[flag,tmp] = ...
solve_stochastic_perfect_foresight_model_1(endo_simul0,exxo_simul,options_.ep,pfm,options_.ep.stochastic.order,weight);
solve_stochastic_perfect_foresight_model_1(endo_simul0,exxo_simul,options_,pfm,options_.ep.stochastic.order,weight);
% solve_stochastic_perfect_foresight_model_1(endo_simul0,exo_simul0,options_.ep,pfm,options_.ep.stochastic.order);
end
end
@ -114,7 +114,6 @@ while weight<1
endo_simul0 = endo_simul;
exo_simul0 = exxo_simul;
info.convergence = 0;
info.depth = d;
tmp = [];
return
end
@ -159,7 +158,7 @@ if weight<1
solve_stochastic_perfect_foresight_model(endo_simul0,exo_simul0,pfm,options_.ep.stochastic.quadrature.nodes,options_.ep.stochastic.order);
case 1
[flag,tmp] = ...
solve_stochastic_perfect_foresight_model_1(endo_simul0,exxo_simul,options_.ep,pfm,options_.ep.stochastic.order,weight);
solve_stochastic_perfect_foresight_model_1(endo_simul0,exxo_simul,options_,pfm,options_.ep.stochastic.order,weight);
% solve_stochastic_perfect_foresight_model_1(endo_simul0,exo_simul0,options_.ep,pfm,options_.ep.stochastic.order);
end
end
@ -173,7 +172,6 @@ if weight<1
endo_simul0 = endo_simul;
exo_simul0 = exxo_simul;
info.convergence = 0;
info.depth = d;
tmp = [];
return
else

6
matlab/ep/solve_stochastic_perfect_foresight_model_1.m
View File

@ -147,5 +147,9 @@ pfm.i_upd_y = i_upd_y;
options_.solve_algo = 9;
options_.steady.maxit = 100;
y = repmat(steady_state,block_nbr,1);
y = dynare_solve(@ep_problem_2,y,1,exo_simul,pfm);
[y,info] = dynare_solve(@ep_problem_2,y,1,exo_simul,pfm);
if info
flag = 1;
err = info;
end
endo_simul(:,2) = y(1:ny);

1
tests/ep/ar.mod
View File

@ -40,6 +40,7 @@ ts = extended_path([],1000);
options_.ep.verbosity = 0;
options_.ep.stochastic.order = 1;
options_.ep.IntegrationAlgorithm='Tensor-Gaussian-Quadrature';
options_.ep.stochastic.nodes = 3;
options_.console_mode = 0;

1
tests/ep/burnside.mod
View File

@ -53,6 +53,7 @@ set_dynare_seed('default');
ts = extended_path([],5000);
options_.ep.stochastic.order = 2;
options_.ep.IntegrationAlgorithm='Tensor-Gaussian-Quadrature';
set_dynare_seed('default');
ts1_4 = extended_path([],5000);

1
tests/ep/linearmodel.mod
View File

@ -36,6 +36,7 @@ options_.console_mode = 0;
ts = extended_path([],100);
options_.ep.stochastic.status = 1;
options_.ep.IntegrationAlgorithm='Tensor-Gaussian-Quadrature';
options_.ep.order = 1;
options_.ep.nnodes = 3;
sts = extended_path([],100);

1
tests/ep/rbc.mod
View File

@ -79,6 +79,7 @@ ts0 = extended_path([],100);
options_.ep.stochastic.order = 1;
options_.ep.stochastic.nodes = 3;
options_.ep.IntegrationAlgorithm='Tensor-Gaussian-Quadrature';
ts1_3 = extended_path([],100);
options_.ep.stochastic.nodes = 5;

1
tests/ep/rbc2.mod
View File

@ -76,5 +76,6 @@ end;
steady;
options_.ep.IntegrationAlgorithm='Tensor-Gaussian-Quadrature';
extended_path(periods=100);

1
tests/ep/rbcii.mod
View File

@ -75,6 +75,7 @@ copyfile('rbcii_steady_state.m','rbcii_steadystate2.m');
ts = extended_path([],100);
options_.ep.stochastic.order = 1;
options_.ep.IntegrationAlgorithm='Tensor-Gaussian-Quadrature';
// profile on
ts1_4 = extended_path([],100);
// profile off