Variance decomposition with pruning: add unit test
parent
c063d53646
commit
4e58e22bdd
|
@ -234,6 +234,7 @@ MODFILES = \
|
|||
AIM/ls2003_2L2L.mod \
|
||||
AIM/ls2003_2L2L_AIM.mod \
|
||||
conditional_variance_decomposition/example1.mod \
|
||||
conditional_variance_decomposition/example3.mod \
|
||||
dsge-var/simul_hybrid.mod \
|
||||
dsge-var/dsgevar_forward_calibrated_lambda.mod \
|
||||
dsge-var/dsgevar_forward_estimated_lambda.mod \
|
||||
|
@ -1359,6 +1360,7 @@ EXTRA_DIST = \
|
|||
measurement_errors/fs2000_corr_me_ml_mcmc/fsdat_simul.m \
|
||||
missing/simulate_data_with_missing_observations.m \
|
||||
conditional_forecasts/2/fsdat_simul.m \
|
||||
conditional_variance_decomposition/example3_steady_state_helper.m \
|
||||
ms-sbvar/msdata.m \
|
||||
ms-sbvar/archive-files/ftd_2s_caseall_upperchol3v.m \
|
||||
ms-sbvar/archive-files/ftd_2s_caseall_upperchol4v.m \
|
||||
|
|
|
@ -0,0 +1,138 @@
|
|||
/*
|
||||
* Example 1 from F. Collard (2001): "Stochastic simulations with DYNARE:
|
||||
* A practical guide" (see "guide.pdf" in the documentation directory).
|
||||
*
|
||||
* This file uses the steady_state_model-block to provide analytical steady state values.
|
||||
* To do so, the equations of the model have been transformed into a non-linear equation in
|
||||
* labor h. Within the steady_state_model-block, a helper function is called that uses fsolve
|
||||
* to solve this non-linear equation. The use of the helper function is necessary to avoid
|
||||
* interference of the MATLAB syntax with Dynare's preprocessor. A more complicated alternative
|
||||
* that provides more flexibility in the type of commands executed and functions called is the use
|
||||
* of an explicit steady state file. See the NK_baseline.mod in the Examples Folder.
|
||||
*
|
||||
* This mod-file also shows how to use Dynare's capacities to generate TeX-files of the model equations.
|
||||
* If you want to see the model equations belonging to this mod-file, run it using Dynare
|
||||
* and then use a TeX-editor to compile the TeX-files generated.
|
||||
*/
|
||||
|
||||
/*
|
||||
* Copyright © 2013 Dynare Team
|
||||
*
|
||||
* This file is part of Dynare.
|
||||
*
|
||||
* Dynare is free software: you can redistribute it and/or modify
|
||||
* it under the terms of the GNU General Public License as published by
|
||||
* the Free Software Foundation, either version 3 of the License, or
|
||||
* (at your option) any later version.
|
||||
*
|
||||
* Dynare is distributed in the hope that it will be useful,
|
||||
* but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
* GNU General Public License for more details.
|
||||
*
|
||||
* You should have received a copy of the GNU General Public License
|
||||
* along with Dynare. If not, see <https://www.gnu.org/licenses/>.
|
||||
*/
|
||||
|
||||
@#define unit_root_var=0
|
||||
|
||||
var y, c, k, a, h, b
|
||||
@#if unit_root_var==1
|
||||
, unit_root
|
||||
@#endif
|
||||
;
|
||||
varexo e, u;
|
||||
|
||||
parameters beta $\beta$
|
||||
rho $\rho$
|
||||
alpha $\alpha$
|
||||
delta $\delta$
|
||||
theta $\theta$
|
||||
psi $\psi$
|
||||
tau $\tau$;
|
||||
|
||||
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)+tau*b(-1) + e;
|
||||
b = tau*a(-1)+rho*b(-1) + u;
|
||||
@#if unit_root_var==1
|
||||
unit_root=unit_root(-1)+e;
|
||||
@#endif
|
||||
end;
|
||||
|
||||
steady_state_model;
|
||||
h=example3_steady_state_helper(alpha,beta,delta,psi,theta);
|
||||
k=((1/beta-(1-delta))/alpha)^(1/(alpha-1))*h;
|
||||
y = k^alpha*h^(1-alpha);
|
||||
c=(1-alpha)*y/(theta*h^(1+psi));
|
||||
a=0;
|
||||
b=0;
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var e; stderr 0.009;
|
||||
var u; stderr 0.009;
|
||||
var e, u = phi*0.009*0.009;
|
||||
end;
|
||||
|
||||
stoch_simul(irf=0,conditional_variance_decomposition=[1,4,40],pruning,order=1);
|
||||
oo1_=oo_;
|
||||
stoch_simul(irf=0,conditional_variance_decomposition=[1,4,40],pruning,order=1) y k;
|
||||
oo2_=oo_;
|
||||
stoch_simul(irf=0,conditional_variance_decomposition=[1,4,40],pruning,order=2) y k ;
|
||||
oo3_=oo_;
|
||||
stoch_simul(irf=0,conditional_variance_decomposition=[1,4,40],pruning,order=2);
|
||||
oo4_=oo_;
|
||||
|
||||
if max(max(abs(oo1_.variance_decomposition-oo4_.variance_decomposition)))>1e-8 || max(max(abs(oo2_.variance_decomposition-oo3_.variance_decomposition)))>1e-8
|
||||
error('Unconditional variance decomposition does not match.')
|
||||
end
|
||||
|
||||
if max(max(max(abs(oo1_.conditional_variance_decomposition-oo4_.conditional_variance_decomposition))))>1e-8 || max(max(max(abs(oo2_.conditional_variance_decomposition-oo3_.conditional_variance_decomposition)))) >1e-8
|
||||
error('Conditional variance decomposition does not match.')
|
||||
end
|
||||
|
||||
varobs y;
|
||||
shocks;
|
||||
var y; stderr 0.01;
|
||||
end;
|
||||
|
||||
stoch_simul(irf=0,conditional_variance_decomposition=[1,4,40],pruning,order=1);
|
||||
oo1_=oo_;
|
||||
stoch_simul(irf=0,conditional_variance_decomposition=[1,4,40],pruning,order=1) y k;
|
||||
oo2_=oo_;
|
||||
stoch_simul(irf=0,conditional_variance_decomposition=[1,4,40],pruning,order=2) y k ;
|
||||
oo3_=oo_;
|
||||
stoch_simul(irf=0,conditional_variance_decomposition=[1,4,40],pruning,order=2);
|
||||
oo4_=oo_;
|
||||
|
||||
|
||||
if max(max(abs(oo1_.variance_decomposition-oo4_.variance_decomposition)))>1e-8 || max(max(abs(oo2_.variance_decomposition-oo3_.variance_decomposition)))>1e-8
|
||||
error('Unconditional variance decomposition does not match.')
|
||||
end
|
||||
|
||||
if max(max(max(abs(oo1_.conditional_variance_decomposition-oo4_.conditional_variance_decomposition))))>1e-8 || max(max(max(abs(oo2_.conditional_variance_decomposition-oo3_.conditional_variance_decomposition)))) >1e-8
|
||||
error('Conditional variance decomposition does not match.')
|
||||
end
|
||||
|
||||
if max(max(abs(oo1_.variance_decomposition_ME-oo4_.variance_decomposition_ME)))>1e-2 || max(max(abs(oo2_.variance_decomposition_ME-oo3_.variance_decomposition_ME)))>1e-2
|
||||
error('Unconditional variance decomposition with ME does not match.')
|
||||
end
|
||||
|
||||
if max(max(max(abs(oo1_.conditional_variance_decomposition_ME-oo4_.conditional_variance_decomposition_ME))))>1e-8 || max(max(max(abs(oo2_.conditional_variance_decomposition_ME-oo3_.conditional_variance_decomposition_ME))))>1e-8
|
||||
error('Conditional variance decomposition with ME does not match.')
|
||||
end
|
|
@ -0,0 +1,5 @@
|
|||
function h=example3_steady_state_helper(alpha,beta,delta,psi,theta)
|
||||
options=optimset('Display','Final','TolX',1e-10,'TolFun',1e-10);
|
||||
h=fsolve(@(h)1- ((((((1/beta-(1-delta))/alpha)^(1/(alpha-1))*h)^(alpha-1))*(h^(1-alpha))-(((1-alpha)*((((1/beta-(1-delta))/alpha)^(1/(alpha-1)))^alpha))/(theta*h^psi))/(((1/beta-(1-delta))/alpha)^(1/(alpha-1))*h))+(1-delta)),0.2,options);
|
||||
|
||||
|
Loading…
Reference in New Issue