parent
8fd18fa9ba
commit
b87690a9f1
|
@ -96,9 +96,6 @@ wsOct
|
|||
!/kronecker/test_kron.m
|
||||
!/load_octave_packages.m
|
||||
!/ls2003/data_ca1.m
|
||||
!/matrix_notation/extFunNoDerivsMatrix.m
|
||||
!/matrix_notation/extFunFirstDerivMatrix.m
|
||||
!/matrix_notation/extFunWithFirstAndSecondDerivsMatrix.m
|
||||
!/measurement_errors/data_ca1.m
|
||||
!/measurement_errors/fs2000_corr_me_ml_mcmc/fsdat_simul.m
|
||||
!/missing/simulate_data_with_missing_observations.m
|
||||
|
|
|
@ -416,18 +416,7 @@ MODFILES = \
|
|||
bgp/nk-1/nk.mod \
|
||||
bgp/ramsey-1/ramsey.mod \
|
||||
dynare-command-options/ramst.mod \
|
||||
particle/local_state_space_iteration_k_test.mod \
|
||||
matrix_notation/deterministic_matrix.mod \
|
||||
matrix_notation/deterministic_scalar.mod \
|
||||
matrix_notation/stochastic_matrix.mod \
|
||||
matrix_notation/stochastic_scalar.mod \
|
||||
matrix_notation/benchmark.mod \
|
||||
matrix_notation/no_deriv_given_matrix_dll.mod \
|
||||
matrix_notation/no_deriv_given_matrix.mod \
|
||||
matrix_notation/first_deriv_given_matrix_dll.mod \
|
||||
matrix_notation/first_deriv_given_matrix.mod \
|
||||
matrix_notation/first_and_2nd_deriv_given_matrix_dll.mod \
|
||||
matrix_notation/first_and_2nd_deriv_given_matrix.mod
|
||||
particle/local_state_space_iteration_k_test.mod
|
||||
|
||||
ECB_MODFILES = \
|
||||
var-expectations/1/example.mod \
|
||||
|
@ -817,23 +806,6 @@ discretionary_policy/dennis_1_estim.o.trs: discretionary_policy/dennis_1.o.trs
|
|||
discretionary_policy/Gali_2015_chapter_3_nonlinear.m.trs: discretionary_policy/Gali_2015_chapter_3.m.trs
|
||||
discretionary_policy/Gali_2015_chapter_3_nonlinear.o.trs: discretionary_policy/Gali_2015_chapter_3.o.trs
|
||||
|
||||
matrix_notation/deterministic_scalar.m.trs: matrix_notation/deterministic_matrix.m.trs
|
||||
matrix_notation/deterministic_scalar.o.trs: matrix_notation/deterministic_matrix.o.trs
|
||||
matrix_notation/stochastic_scalar.m.trs: matrix_notation/stochastic_matrix.m.trs
|
||||
matrix_notation/stochastic_scalar.o.trs: matrix_notation/stochastic_matrix.o.trs
|
||||
matrix_notation/first_deriv_given_matrix.m.trs: matrix_notation/benchmark.m.trs
|
||||
matrix_notation/first_deriv_given_matrix.o.trs: matrix_notation/benchmark.o.trs
|
||||
matrix_notation/first_deriv_given_matrix_dll.m.trs: matrix_notation/benchmark.m.trs
|
||||
matrix_notation/first_deriv_given_matrix_dll.o.trs: matrix_notation/benchmark.o.trs
|
||||
matrix_notation/first_and_2nd_deriv_given_matrix.m.trs: matrix_notation/benchmark.m.trs
|
||||
matrix_notation/first_and_2nd_deriv_given_matrix.o.trs: matrix_notation/benchmark.o.trs
|
||||
matrix_notation/first_and_2nd_deriv_given_matrix_dll.m.trs: matrix_notation/benchmark.m.trs
|
||||
matrix_notation/first_and_2nd_deriv_given_matrix_dll.o.trs: matrix_notation/benchmark.o.trs
|
||||
matrix_notation/no_deriv_given_matrix.m.trs: matrix_notation/benchmark.m.trs
|
||||
matrix_notation/no_deriv_given_matrix.o.trs: matrix_notation/benchmark.o.trs
|
||||
matrix_notation/no_deriv_given_matrix_dll.m.trs: matrix_notation/benchmark.m.trs
|
||||
matrix_notation/no_deriv_given_matrix_dll.o.trs: matrix_notation/benchmark.o.trs
|
||||
|
||||
observation_trends_and_prefiltering/MCMC: m/observation_trends_and_prefiltering/MCMC o/observation_trends_and_prefiltering/MCMC
|
||||
m/observation_trends_and_prefiltering/MCMC: $(patsubst %.mod, %.m.trs, $(filter observation_trends_and_prefiltering/MCMC/%.mod, $(MODFILES)))
|
||||
o/observation_trends_and_prefiltering/MCMC: $(patsubst %.mod, %.o.trs, $(filter observation_trends_and_prefiltering/MCMC/%.mod, $(MODFILES)))
|
||||
|
@ -1046,10 +1018,6 @@ estimation/univariate: m/estimation/univariate o/estimation/univariate
|
|||
m/estimation/univariate: $(patsubst %.mod, %.m.trs, $(filter estimation/univariate/%.mod, $(MODFILES)))
|
||||
o/estimation/univariate: $(patsubst %.mod, %.o.trs, $(filter estimation/univariate/%.mod, $(MODFILES)))
|
||||
|
||||
matrix_notation: m/matrix_notation o/matrix_notation
|
||||
m/matrix_notation: $(patsubst %.mod, %.m.trs, $(filter matrix_notation/%.mod, $(MODFILES)))
|
||||
o/matrix_notation: $(patsubst %.mod, %.o.trs, $(filter matrix_notation/%.mod, $(MODFILES)))
|
||||
|
||||
# ECB files
|
||||
M_ECB_TRS_FILES = $(patsubst %.mod, %.m.trs, $(ECB_MODFILES))
|
||||
|
||||
|
@ -1235,10 +1203,7 @@ EXTRA_DIST = \
|
|||
histval_initval_file/my_assert.m \
|
||||
histval_initval_file/ramst_data.xls \
|
||||
histval_initval_file/ramst_data.xlsx \
|
||||
histval_initval_file/ramst_initval_file_data.m \
|
||||
matrix_notation/extFunFirstDerivMatrix.m \
|
||||
matrix_notation/extFunNoDerivsMatrix.m \
|
||||
matrix_notation/extFunWithFirstAndSecondDerivsMatrix.m
|
||||
histval_initval_file/ramst_initval_file_data.m
|
||||
|
||||
if ENABLE_MATLAB
|
||||
check-local: check-matlab
|
||||
|
|
|
@ -1,44 +0,0 @@
|
|||
/* This file is used as a benchmark against with the other tests with external
|
||||
functions are compared.
|
||||
It is almost the same as example1.mod, except that the shocks process is
|
||||
nonlinear (in order to have a non-zero Hessian of the
|
||||
external function) */
|
||||
|
||||
var y, c, k, h, a, b;
|
||||
varexo e, u;
|
||||
parameters beta, alpha, delta, theta, psi, rho, tau;
|
||||
|
||||
alpha = 0.36;
|
||||
rho = 0.95;
|
||||
tau = 0.025;
|
||||
beta = 0.99;
|
||||
delta = 0.025;
|
||||
psi = 0;
|
||||
theta = 2.95;
|
||||
|
||||
phi = 0.1;
|
||||
|
||||
model;
|
||||
c*theta*h^(1+psi)=(1-alpha)*y;
|
||||
k = beta*(((exp(b)*c)/(exp(b(+1))*c(+1)))
|
||||
*(exp(b(+1))*alpha*y(+1)+(1-delta)*k));
|
||||
y = exp(a)*(k(-1)^alpha)*(h^(1-alpha));
|
||||
k = exp(b)*(y-c)+(1-delta)*k(-1) ;
|
||||
a = rho*a(-1)^2+5*tau*b(-1)^2 + e;
|
||||
b = 3*tau/2*a(-1)^2+7*rho/3*b(-1)^2 + u;
|
||||
end;
|
||||
|
||||
initval;
|
||||
y = 1.08068253095672;
|
||||
c = 0.80359242014163;
|
||||
h = 0.29175631001732;
|
||||
k = 11.08360443260358;
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var e; stderr 0.009;
|
||||
var u; stderr 0.009;
|
||||
var e, u = phi*0.009*0.009;
|
||||
end;
|
||||
|
||||
stoch_simul;
|
|
@ -1,38 +0,0 @@
|
|||
// Do not forget to update deterministic_scalar.mod when this file is modified
|
||||
|
||||
var(rows=3) X, Y, Z;
|
||||
var t;
|
||||
varexo(rows=3) E, U, V;
|
||||
parameters(rows=3, cols=3) P;
|
||||
|
||||
P = [.1, .2, -.3; -.1, .5, .1; .2, -.3, .9];
|
||||
|
||||
model;
|
||||
X = P*X(-1)+E;
|
||||
transpose(Y) = transpose(Y(-1))*transpose(P)+transpose(U);
|
||||
Z = V;
|
||||
t = Y[1](-1) + Y[2](+1);
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var E;
|
||||
periods 1 2;
|
||||
values [0.5; 0.6; 0.7] [0.2; 0.3; 0.4];
|
||||
|
||||
var U[1];
|
||||
periods 3;
|
||||
values 0.8;
|
||||
|
||||
var U[2];
|
||||
periods 3;
|
||||
values 0.7;
|
||||
|
||||
var V[:];
|
||||
periods 1;
|
||||
values 0.1;
|
||||
end;
|
||||
|
||||
perfect_foresight_setup(periods=50);
|
||||
perfect_foresight_solver;
|
||||
|
||||
write_latex_dynamic_model;
|
|
@ -1,70 +0,0 @@
|
|||
// Scalar translation of deterministic_matrix.mod
|
||||
// The declaration orders are the same as those of the expanded matrix version
|
||||
var t X_1 X_2 X_3 Y_1 Y_2 Y_3 Z_1 Z_2 Z_3;
|
||||
varexo E_1 E_2 E_3 U_1 U_2 U_3 V_1 V_2 V_3;
|
||||
parameters P_1_1 P_1_2 P_1_3 P_2_1 P_2_2 P_2_3 P_3_1 P_3_2 P_3_3;
|
||||
|
||||
P_1_1 = .1;
|
||||
P_1_2 = .2;
|
||||
P_1_3 = -.3;
|
||||
P_2_1 = -.1;
|
||||
P_2_2 = .5;
|
||||
P_2_3 = .1;
|
||||
P_3_1 = .2;
|
||||
P_3_2 = -.3;
|
||||
P_3_3 = .9;
|
||||
|
||||
model;
|
||||
X_1 = P_1_1*X_1(-1) + P_1_2*X_2(-1) + P_1_3*X_3(-1) + E_1;
|
||||
X_2 = P_2_1*X_1(-1) + P_2_2*X_2(-1) + P_2_3*X_3(-1) + E_2;
|
||||
X_3 = P_3_1*X_1(-1) + P_3_2*X_2(-1) + P_3_3*X_3(-1) + E_3;
|
||||
Y_1 = P_1_1*Y_1(-1) + P_1_2*Y_2(-1) + P_1_3*Y_3(-1) + U_1;
|
||||
Y_2 = P_2_1*Y_1(-1) + P_2_2*Y_2(-1) + P_2_3*Y_3(-1) + U_2;
|
||||
Y_3 = P_3_1*Y_1(-1) + P_3_2*Y_2(-1) + P_3_3*Y_3(-1) + U_3;
|
||||
Z_1 = V_1;
|
||||
Z_2 = V_2;
|
||||
Z_3 = V_3;
|
||||
t = Y_1(-1) + Y_2(+1);
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var E_1;
|
||||
periods 1 2;
|
||||
values 0.5 0.2;
|
||||
|
||||
var E_2;
|
||||
periods 1 2;
|
||||
values 0.6 0.3;
|
||||
|
||||
var E_3;
|
||||
periods 1 2;
|
||||
values 0.7 0.4;
|
||||
|
||||
var U_1;
|
||||
periods 3;
|
||||
values 0.8;
|
||||
|
||||
var U_2;
|
||||
periods 3;
|
||||
values 0.7;
|
||||
|
||||
var V_1;
|
||||
periods 1;
|
||||
values 0.1;
|
||||
|
||||
var V_2;
|
||||
periods 1;
|
||||
values 0.1;
|
||||
|
||||
var V_3;
|
||||
periods 1;
|
||||
values 0.1;
|
||||
end;
|
||||
|
||||
perfect_foresight_setup(periods=50);
|
||||
perfect_foresight_solver;
|
||||
|
||||
L = load('deterministic_matrix_results.mat');
|
||||
if max(max(abs(L.oo_.endo_simul - oo_.endo_simul))) > 1e-12
|
||||
error('Failure in matrix expansion')
|
||||
end
|
|
@ -1,4 +0,0 @@
|
|||
function dy=extFunFirstDerivMatrix(a,b,c)
|
||||
dy = [ c(1)^2 0 5*c(2)^2 0 2*a(1)*c(1) 10*b(1)*c(2);
|
||||
0 3*c(1)^2 0 7*c(2)^2 6*a(2)*c(1) 14*b(2)*c(2) ];
|
||||
end
|
|
@ -1,3 +0,0 @@
|
|||
function y=extFunNoDerivsMatrix(a,b,c)
|
||||
y=[a(1), 5*b(1); 3*a(2) 7*b(2)]*c.^2;
|
||||
end
|
|
@ -1,20 +0,0 @@
|
|||
function [y dy d2y]=extFunWithFirstAndSecondDerivsMatrix(a,b,c)
|
||||
y=[a(1), 5*b(1); 3*a(2), 7*b(2)]*c.^2;
|
||||
|
||||
dy = [ c(1)^2 0 5*c(2)^2 0 2*a(1)*c(1) 10*b(1)*c(2);
|
||||
0 3*c(1)^2 0 7*c(2)^2 6*a(2)*c(1) 14*b(2)*c(2) ];
|
||||
|
||||
d2y=zeros(2,6,6);
|
||||
d2y(1,1,5) = 2*c(1);
|
||||
d2y(1,3,6) = 10*c(2);
|
||||
d2y(1,5,1) = 2*c(1);
|
||||
d2y(1,5,5) = 2*a(1);
|
||||
d2y(1,6,3) = 10*c(2);
|
||||
d2y(1,6,6) = 10*b(1);
|
||||
d2y(2,2,5) = 6*c(1);
|
||||
d2y(2,4,6) = 14*c(2);
|
||||
d2y(2,5,2) = 6*c(1);
|
||||
d2y(2,5,5) = 6*a(2);
|
||||
d2y(2,6,4) = 14*c(2);
|
||||
d2y(2,6,6) = 14*b(2);
|
||||
end
|
|
@ -1,71 +0,0 @@
|
|||
var y, c, k, h;
|
||||
var(rows = 2) A; // A == [a; b]
|
||||
varexo(rows = 2) E; // E == [e; u]
|
||||
parameters beta, alpha, delta, theta, psi;
|
||||
parameters(rows=2,cols=2) P;
|
||||
|
||||
alpha = 0.36;
|
||||
rho = 0.95;
|
||||
tau = 0.025;
|
||||
beta = 0.99;
|
||||
delta = 0.025;
|
||||
psi = 0;
|
||||
theta = 2.95;
|
||||
|
||||
phi = 0.1;
|
||||
|
||||
P = [rho, tau; tau/2, rho/3];
|
||||
|
||||
external_function(nargs=3, name=extFunWithFirstAndSecondDerivsMatrix, in_arg_dim=[2,2,2],
|
||||
out_arg_dim=2, first_deriv_provided, second_deriv_provided);
|
||||
|
||||
model;
|
||||
[endogenous='c',name='law of motion of capital']
|
||||
c*theta*h^(1+psi)=(1-alpha)*y;
|
||||
k = beta*(((exp(A[2])*c)/(exp(A[2](+1))*c(+1)))
|
||||
*(exp(A[2](+1))*alpha*y(+1)+(1-delta)*k));
|
||||
y = exp(A[1])*(k(-1)^alpha)*(h^(1-alpha));
|
||||
k = exp(A[2])*(y-c)+(1-delta)*k(-1) ;
|
||||
A = extFunWithFirstAndSecondDerivsMatrix(P[:,1], transpose(P[:,2]), A(-1)) + E;
|
||||
end;
|
||||
|
||||
initval;
|
||||
y = 1.08068253095672;
|
||||
c = 0.80359242014163;
|
||||
h = 0.29175631001732;
|
||||
k = 11.08360443260358;
|
||||
|
||||
A[1] = 0;
|
||||
A[2] = 0;
|
||||
E[:] = 0;
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var E[:]; stderr 0.009;
|
||||
var E[1], E[2] = phi*0.009*0.009;
|
||||
end;
|
||||
|
||||
stoch_simul;
|
||||
|
||||
L = load('benchmark_results.mat');
|
||||
if max(max(abs(L.oo_.dr.ghu - oo_.dr.ghu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghx - oo_.dr.ghx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxu - oo_.dr.ghxu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxx - oo_.dr.ghxx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghuu - oo_.dr.ghuu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghs2 - oo_.dr.ghs2))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.var - oo_.var))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
|
@ -1,71 +0,0 @@
|
|||
var y, c, k, h;
|
||||
var(rows = 2) A; // A == [a; b]
|
||||
varexo(rows = 2) E; // E == [e; u]
|
||||
parameters beta, alpha, delta, theta, psi;
|
||||
parameters(rows=2,cols=2) P;
|
||||
|
||||
alpha = 0.36;
|
||||
rho = 0.95;
|
||||
tau = 0.025;
|
||||
beta = 0.99;
|
||||
delta = 0.025;
|
||||
psi = 0;
|
||||
theta = 2.95;
|
||||
|
||||
phi = 0.1;
|
||||
|
||||
P = [rho, tau; tau/2, rho/3];
|
||||
|
||||
external_function(nargs=3, name=extFunWithFirstAndSecondDerivsMatrix, in_arg_dim=[2,2,2],
|
||||
out_arg_dim=2, first_deriv_provided, second_deriv_provided);
|
||||
|
||||
model(use_dll);
|
||||
[endogenous='c',name='law of motion of capital']
|
||||
c*theta*h^(1+psi)=(1-alpha)*y;
|
||||
k = beta*(((exp(A[2])*c)/(exp(A[2](+1))*c(+1)))
|
||||
*(exp(A[2](+1))*alpha*y(+1)+(1-delta)*k));
|
||||
y = exp(A[1])*(k(-1)^alpha)*(h^(1-alpha));
|
||||
k = exp(A[2])*(y-c)+(1-delta)*k(-1) ;
|
||||
A = extFunWithFirstAndSecondDerivsMatrix(P[:,1], transpose(P[:,2]), A(-1)) + E;
|
||||
end;
|
||||
|
||||
initval;
|
||||
y = 1.08068253095672;
|
||||
c = 0.80359242014163;
|
||||
h = 0.29175631001732;
|
||||
k = 11.08360443260358;
|
||||
|
||||
A[1] = 0;
|
||||
A[2] = 0;
|
||||
E[:] = 0;
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var E[:]; stderr 0.009;
|
||||
var E[1], E[2] = phi*0.009*0.009;
|
||||
end;
|
||||
|
||||
stoch_simul;
|
||||
|
||||
L = load('benchmark_results.mat');
|
||||
if max(max(abs(L.oo_.dr.ghu - oo_.dr.ghu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghx - oo_.dr.ghx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxu - oo_.dr.ghxu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxx - oo_.dr.ghxx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghuu - oo_.dr.ghuu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghs2 - oo_.dr.ghs2))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.var - oo_.var))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
|
@ -1,72 +0,0 @@
|
|||
// --+ options: json=compute +--
|
||||
|
||||
var y, c, k, h;
|
||||
var(rows = 2) A; // A == [a; b]
|
||||
varexo(rows = 2) E; // E == [e; u]
|
||||
parameters beta, alpha, delta, theta, psi;
|
||||
parameters(rows=2,cols=2) P;
|
||||
|
||||
alpha = 0.36;
|
||||
rho = 0.95;
|
||||
tau = 0.025;
|
||||
beta = 0.99;
|
||||
delta = 0.025;
|
||||
psi = 0;
|
||||
theta = 2.95;
|
||||
|
||||
phi = 0.1;
|
||||
|
||||
P = [rho, tau; tau/2, rho/3];
|
||||
|
||||
external_function(nargs=3, name=extFunNoDerivsMatrix, in_arg_dim=[2,2,2],
|
||||
out_arg_dim=2, first_deriv_provided=extFunFirstDerivMatrix);
|
||||
|
||||
model;
|
||||
c*theta*h^(1+psi)=(1-alpha)*y;
|
||||
k = beta*(((exp(A[2])*c)/(exp(A[2](+1))*c(+1)))
|
||||
*(exp(A[2](+1))*alpha*y(+1)+(1-delta)*k));
|
||||
y = exp(A[1])*(k(-1)^alpha)*(h^(1-alpha));
|
||||
k = exp(A[2])*(y-c)+(1-delta)*k(-1) ;
|
||||
A = extFunNoDerivsMatrix(P[:,1], transpose(P[:,2]), A(-1)) + E;
|
||||
end;
|
||||
|
||||
initval;
|
||||
y = 1.08068253095672;
|
||||
c = 0.80359242014163;
|
||||
h = 0.29175631001732;
|
||||
k = 11.08360443260358;
|
||||
|
||||
A[1] = 0;
|
||||
A[2] = 0;
|
||||
E[:] = 0;
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var E[:]; stderr 0.009;
|
||||
var E[1], E[2] = phi*0.009*0.009;
|
||||
end;
|
||||
|
||||
stoch_simul;
|
||||
|
||||
L = load('benchmark_results.mat');
|
||||
if max(max(abs(L.oo_.dr.ghu - oo_.dr.ghu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghx - oo_.dr.ghx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxu - oo_.dr.ghxu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxx - oo_.dr.ghxx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghuu - oo_.dr.ghuu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghs2 - oo_.dr.ghs2))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.var - oo_.var))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
|
@ -1,73 +0,0 @@
|
|||
// --+ options: json=compute +--
|
||||
|
||||
var y, c, k, h;
|
||||
var(rows = 2) A; // A == [a; b]
|
||||
varexo(rows = 2) E; // E == [e; u]
|
||||
parameters beta, alpha, delta, theta, psi;
|
||||
parameters(rows=2,cols=2) P;
|
||||
|
||||
alpha = 0.36;
|
||||
rho = 0.95;
|
||||
tau = 0.025;
|
||||
beta = 0.99;
|
||||
delta = 0.025;
|
||||
psi = 0;
|
||||
theta = 2.95;
|
||||
|
||||
phi = 0.1;
|
||||
|
||||
P = [rho, tau; tau/2, rho/3];
|
||||
|
||||
external_function(nargs=3, name=extFunNoDerivsMatrix, in_arg_dim=[2,2,2],
|
||||
out_arg_dim=2, first_deriv_provided=extFunFirstDerivMatrix);
|
||||
|
||||
model(use_dll);
|
||||
c*theta*h^(1+psi)=(1-alpha)*y;
|
||||
k = beta*(((exp(A[2])*c)/(exp(A[2](+1))*c(+1)))
|
||||
*(exp(A[2](+1))*alpha*y(+1)+(1-delta)*k));
|
||||
y = exp(A[1])*(k(-1)^alpha)*(h^(1-alpha));
|
||||
k = exp(A[2])*(y-c)+(1-delta)*k(-1) ;
|
||||
A = extFunNoDerivsMatrix(P[:,1], transpose(P[:,2]), A(-1)) + E;
|
||||
end;
|
||||
|
||||
initval;
|
||||
y = 1.08068253095672;
|
||||
c = 0.80359242014163;
|
||||
h = 0.29175631001732;
|
||||
k = 11.08360443260358;
|
||||
|
||||
A[1] = 0;
|
||||
A[2] = 0;
|
||||
E[:] = 0;
|
||||
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var E[:]; stderr 0.009;
|
||||
var E[1], E[2] = phi*0.009*0.009;
|
||||
end;
|
||||
|
||||
stoch_simul;
|
||||
|
||||
L = load('benchmark_results.mat');
|
||||
if max(max(abs(L.oo_.dr.ghu - oo_.dr.ghu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghx - oo_.dr.ghx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxu - oo_.dr.ghxu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxx - oo_.dr.ghxx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghuu - oo_.dr.ghuu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghs2 - oo_.dr.ghs2))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.var - oo_.var))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
|
@ -1,71 +0,0 @@
|
|||
// --+ options: json=compute +--
|
||||
|
||||
var y, c, k, h;
|
||||
var(rows = 2) A; // A == [a; b]
|
||||
varexo(rows = 2) E; // E == [e; u]
|
||||
parameters beta, alpha, delta, theta, psi;
|
||||
parameters(rows=2,cols=2) P;
|
||||
|
||||
alpha = 0.36;
|
||||
rho = 0.95;
|
||||
tau = 0.025;
|
||||
beta = 0.99;
|
||||
delta = 0.025;
|
||||
psi = 0;
|
||||
theta = 2.95;
|
||||
|
||||
phi = 0.1;
|
||||
|
||||
P = [rho, tau; tau/2, rho/3];
|
||||
|
||||
external_function(nargs=3, name=extFunNoDerivsMatrix, in_arg_dim=[2,2,2], out_arg_dim=2);
|
||||
|
||||
model;
|
||||
c*theta*h^(1+psi)=(1-alpha)*y;
|
||||
k = beta*(((exp(A[2])*c)/(exp(A[2](+1))*c(+1)))
|
||||
*(exp(A[2](+1))*alpha*y(+1)+(1-delta)*k));
|
||||
y = exp(A[1])*(k(-1)^alpha)*(h^(1-alpha));
|
||||
k = exp(A[2])*(y-c)+(1-delta)*k(-1) ;
|
||||
A = extFunNoDerivsMatrix(P[:,1], transpose(P[:,2]), A(-1)) + E;
|
||||
end;
|
||||
|
||||
initval;
|
||||
y = 1.08068253095672;
|
||||
c = 0.80359242014163;
|
||||
h = 0.29175631001732;
|
||||
k = 11.08360443260358;
|
||||
|
||||
A[1] = 0;
|
||||
A[2] = 0;
|
||||
E[:] = 0;
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var E[:]; stderr 0.009;
|
||||
var E[1], E[2] = phi*0.009*0.009;
|
||||
end;
|
||||
|
||||
stoch_simul;
|
||||
|
||||
L = load('benchmark_results.mat');
|
||||
if max(max(abs(L.oo_.dr.ghu - oo_.dr.ghu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghx - oo_.dr.ghx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxu - oo_.dr.ghxu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxx - oo_.dr.ghxx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghuu - oo_.dr.ghuu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghs2 - oo_.dr.ghs2))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.var - oo_.var))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
|
@ -1,71 +0,0 @@
|
|||
// --+ options: json=compute +--
|
||||
|
||||
var y, c, k, h;
|
||||
var(rows = 2) A; // A == [a; b]
|
||||
varexo(rows = 2) E; // E == [e; u]
|
||||
parameters beta, alpha, delta, theta, psi;
|
||||
parameters(rows=2,cols=2) P;
|
||||
|
||||
alpha = 0.36;
|
||||
rho = 0.95;
|
||||
tau = 0.025;
|
||||
beta = 0.99;
|
||||
delta = 0.025;
|
||||
psi = 0;
|
||||
theta = 2.95;
|
||||
|
||||
phi = 0.1;
|
||||
|
||||
P = [rho, tau; tau/2, rho/3];
|
||||
|
||||
external_function(nargs=3, name=extFunNoDerivsMatrix, in_arg_dim=[2,2,2], out_arg_dim=2);
|
||||
|
||||
model(use_dll);
|
||||
c*theta*h^(1+psi)=(1-alpha)*y;
|
||||
k = beta*(((exp(A[2])*c)/(exp(A[2](+1))*c(+1)))
|
||||
*(exp(A[2](+1))*alpha*y(+1)+(1-delta)*k));
|
||||
y = exp(A[1])*(k(-1)^alpha)*(h^(1-alpha));
|
||||
k = exp(A[2])*(y-c)+(1-delta)*k(-1) ;
|
||||
A = extFunNoDerivsMatrix(P[:,1], transpose(P[:,2]), A(-1)) + E;
|
||||
end;
|
||||
|
||||
initval;
|
||||
y = 1.08068253095672;
|
||||
c = 0.80359242014163;
|
||||
h = 0.29175631001732;
|
||||
k = 11.08360443260358;
|
||||
|
||||
A[1] = 0;
|
||||
A[2] = 0;
|
||||
E[:] = 0;
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var E[:]; stderr 0.009;
|
||||
var E[1], E[2] = phi*0.009*0.009;
|
||||
end;
|
||||
|
||||
stoch_simul;
|
||||
|
||||
L = load('benchmark_results.mat');
|
||||
if max(max(abs(L.oo_.dr.ghu - oo_.dr.ghu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghx - oo_.dr.ghx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxu - oo_.dr.ghxu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghxx - oo_.dr.ghxx))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghuu - oo_.dr.ghuu))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghs2 - oo_.dr.ghs2))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
||||
if max(max(abs(L.oo_.var - oo_.var))) > 1e-12
|
||||
error('Failure in matrix notation with external function')
|
||||
end
|
|
@ -1,46 +0,0 @@
|
|||
// Do not forget to update stochastic_scalar.mod when this file is modified
|
||||
|
||||
var(rows=3) X, Y, Z, T;
|
||||
var r;
|
||||
varexo(rows=3) E, U, V, W;
|
||||
varexo f;
|
||||
parameters(rows=3, cols=3) P;
|
||||
varexo_det(rows=3) D;
|
||||
|
||||
P = [.1, .2, -.3; -.1, .5, .1; .2, -.3, .9];
|
||||
|
||||
model;
|
||||
X = P*X(-1)+E;
|
||||
transpose(Y) = transpose(Y(-1))*transpose(P)+transpose(U);
|
||||
Z[1] = V[1];
|
||||
Z[2] = V[2];
|
||||
Z[3] = V[3];
|
||||
T = D + W;
|
||||
r = 0.9*r(+1)+f;
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var E = [ 0.1, 0.2, 0.3 ];
|
||||
var E[1], E[2] = 0.08;
|
||||
|
||||
var U[1] = 0.4;
|
||||
var U[2]; stderr 0.5;
|
||||
var U[3]; stderr 0.6;
|
||||
corr U[1], U[2] = 0.09;
|
||||
|
||||
var V; stderr [ 1.1, 1.2, 1.3 ];
|
||||
|
||||
vcov W = [
|
||||
1, 0.2, 0.3;
|
||||
0.2, 5, 0.6;
|
||||
0.3, 0.6, 9
|
||||
];
|
||||
|
||||
var f = 3;
|
||||
var f, E[2] = 0.5;
|
||||
corr U[1], f = 0.7;
|
||||
end;
|
||||
|
||||
stoch_simul(order=1, nodecomposition, irf=0);
|
||||
|
||||
write_latex_dynamic_model;
|
|
@ -1,72 +0,0 @@
|
|||
// Scalar translation of stochastic_matrix.mod
|
||||
// The declaration orders are the same as those of the expanded matrix version
|
||||
var r X_1 X_2 X_3 Y_1 Y_2 Y_3 Z_1 Z_2 Z_3 T_1 T_2 T_3;
|
||||
varexo f E_1 E_2 E_3 U_1 U_2 U_3 V_1 V_2 V_3 W_1 W_2 W_3;
|
||||
parameters P_1_1 P_1_2 P_1_3 P_2_1 P_2_2 P_2_3 P_3_1 P_3_2 P_3_3;
|
||||
varexo_det D_1 D_2 D_3;
|
||||
|
||||
P_1_1 = .1;
|
||||
P_1_2 = .2;
|
||||
P_1_3 = -.3;
|
||||
P_2_1 = -.1;
|
||||
P_2_2 = .5;
|
||||
P_2_3 = .1;
|
||||
P_3_1 = .2;
|
||||
P_3_2 = -.3;
|
||||
P_3_3 = .9;
|
||||
|
||||
model;
|
||||
X_1 = P_1_1*X_1(-1) + P_1_2*X_2(-1) + P_1_3*X_3(-1) + E_1;
|
||||
X_2 = P_2_1*X_1(-1) + P_2_2*X_2(-1) + P_2_3*X_3(-1) + E_2;
|
||||
X_3 = P_3_1*X_1(-1) + P_3_2*X_2(-1) + P_3_3*X_3(-1) + E_3;
|
||||
Y_1 = P_1_1*Y_1(-1) + P_1_2*Y_2(-1) + P_1_3*Y_3(-1) + U_1;
|
||||
Y_2 = P_2_1*Y_1(-1) + P_2_2*Y_2(-1) + P_2_3*Y_3(-1) + U_2;
|
||||
Y_3 = P_3_1*Y_1(-1) + P_3_2*Y_2(-1) + P_3_3*Y_3(-1) + U_3;
|
||||
Z_1 = V_1;
|
||||
Z_2 = V_2;
|
||||
Z_3 = V_3;
|
||||
T_1 = D_1 + W_1;
|
||||
T_2 = D_2 + W_2;
|
||||
T_3 = D_3 + W_3;
|
||||
r = 0.9*r(+1)+f;
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var E_1 = 0.1;
|
||||
var E_2 = 0.2;
|
||||
var E_3 = 0.3;
|
||||
var E_1, E_2 = 0.08;
|
||||
|
||||
var U_1 = 0.4;
|
||||
var U_2; stderr 0.5;
|
||||
var U_3; stderr 0.6;
|
||||
corr U_1, U_2 = 0.09;
|
||||
|
||||
var V_1; stderr 1.1;
|
||||
var V_2; stderr 1.2;
|
||||
var V_3; stderr 1.3;
|
||||
|
||||
var W_1 = 1;
|
||||
var W_2 = 5;
|
||||
var W_3 = 9;
|
||||
var W_1, W_2 = 0.2;
|
||||
var W_1, W_3 = 0.3;
|
||||
var W_2, W_3 = 0.6;
|
||||
|
||||
var f = 3;
|
||||
var f, E_2 = 0.5;
|
||||
corr U_1, f = 0.7;
|
||||
end;
|
||||
|
||||
stoch_simul(order=1, nodecomposition, irf=0);
|
||||
|
||||
L = load('stochastic_matrix_results.mat');
|
||||
if max(max(abs(L.oo_.dr.ghu - oo_.dr.ghu))) > 1e-12
|
||||
error('Failure in matrix expansion')
|
||||
end
|
||||
if max(max(abs(L.oo_.dr.ghx - oo_.dr.ghx))) > 1e-12
|
||||
error('Failure in matrix expansion')
|
||||
end
|
||||
if max(max(abs(L.oo_.var - oo_.var))) > 1e-12
|
||||
error('Failure in matrix expansion')
|
||||
end
|
Loading…
Reference in New Issue