commit
80bfbc0736
GPG Key ID:
295C1FE89E17EB3C
|
|
@ -0,0 +1,113 @@
|
|||
function decomposition = shock_decomposition_backward(simulations, initialconditions, shocklist, endograph, use_shock_groups)
|
||||
|
||||
% Computes and possibly plots the shock decomposition of a backward (possibly nonlinear)
|
||||
% model simulation.
|
||||
%
|
||||
% Inputs:
|
||||
% - simulations dseries object as returned by simul_backward_model
|
||||
% - initialconditions dseries object as passed to simul_backward_model
|
||||
% - shocklist a cell array listing the (names of the) shocks whose contribution should be
|
||||
% computed. The order matters: the contribution of a shock appearing at index
|
||||
% i is computed as the difference between the simulation where all shocks ≥i+1
|
||||
% are zero and the simulation where all shocks ≥i are zero. It is also
|
||||
% possible to put in this list shock groups, as defined in a shock_groups
|
||||
% block
|
||||
% - endograph an optional cell array listing the (names of the) endogenous variables for
|
||||
% which a shock decomposition graph should be created
|
||||
% - use_shock_groups an optional string giving the name of the shock_groups block to be used to
|
||||
% resolve shock groups listed in shocklist. If not given, 'default' is used.
|
||||
%
|
||||
% Output:
|
||||
% - decomposition a 3D array of size endo_nbr×nshocks×nperiods where nshocks=length(shocklist)
|
||||
% and nperiods is the number of simulation periods (i.e. excluding the initial
|
||||
% conditions)
|
||||
|
||||
% Copyright © 2020 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 <http://www.gnu.org/licenses/>.
|
||||
|
||||
global M_ options_
|
||||
|
||||
narginchk(3, 5);
|
||||
if nargin < 4
|
||||
endograph = {};
|
||||
end
|
||||
if nargin < 5
|
||||
use_shock_groups = 'default';
|
||||
end
|
||||
|
||||
% Extract matrix of innovations from the whole simulation paths
|
||||
simdates = simulations.dates(initialconditions.nobs+1:end);
|
||||
innovations = simulations{M_.exo_names{:}}(simdates);
|
||||
|
||||
% Number of simulation periods
|
||||
nperiods = simulations.nobs - initialconditions.nobs;
|
||||
|
||||
decomposition = NaN(M_.endo_nbr, length(shocklist), nperiods);
|
||||
|
||||
% Add auxiliary variables to simulation paths
|
||||
if exist(sprintf('+%s/dynamic_set_auxiliary_series', M_.fname), 'file')
|
||||
simulations = feval(sprintf('%s.dynamic_set_auxiliary_series', M_.fname), simulations, M_.params);
|
||||
end
|
||||
|
||||
for i = length(shocklist):-1:1
|
||||
% Zero the innovation(s) corresponding to this shock or shock group
|
||||
if ismember(shocklist{i}, M_.exo_names)
|
||||
innovations{shocklist{i}}(simdates) = zeros(nperiods, 1);
|
||||
else % This is a shock group
|
||||
if ~ismember(use_shock_groups, fieldnames(M_.shock_groups))
|
||||
error(['Unknown shock_groups block: ' use_shock_groups])
|
||||
end
|
||||
groups = fieldnames(M_.shock_groups.(use_shock_groups));
|
||||
shocks_in_group = [];
|
||||
for j = 1:length(groups)
|
||||
if strcmp(shocklist{i}, M_.shock_groups.(use_shock_groups).(groups{j}).label)
|
||||
shocks_in_group = M_.shock_groups.(use_shock_groups).(groups{j}).shocks;
|
||||
break
|
||||
end
|
||||
end
|
||||
if isempty(shocks_in_group)
|
||||
error(['Unknown shock group: ' shocklist{i}])
|
||||
end
|
||||
for j = 1:length(shocks_in_group)
|
||||
innovations{shocks_in_group{j}}(simdates) = zeros(nperiods, 1);
|
||||
end
|
||||
end
|
||||
|
||||
% Compute simulation with the current shock or shock group removed
|
||||
simulations_new = simul_backward_model(initialconditions, nperiods, innovations);
|
||||
if exist(sprintf('+%s/dynamic_set_auxiliary_series', M_.fname), 'file')
|
||||
simulations_new = feval(sprintf('%s.dynamic_set_auxiliary_series', M_.fname), simulations_new, M_.params);
|
||||
end
|
||||
|
||||
% Compute the contribution of the current shock or shock group
|
||||
contribution = simulations{M_.endo_names{:}}.data(initialconditions.nobs+1:end, :) ...
|
||||
- simulations_new{M_.endo_names{:}}.data(initialconditions.nobs+1:end, :);
|
||||
decomposition(:, i, :) = contribution';
|
||||
|
||||
simulations = simulations_new;
|
||||
end
|
||||
|
||||
% Plot the decomposition
|
||||
|
||||
for i = 1:length(endograph)
|
||||
h = dyn_figure(options_.plot_shock_decomp.nodisplay, 'Name', [ 'Shock decomposition for ' endograph{i}]);
|
||||
endoidx = find(strcmp(endograph{i}, M_.endo_names));
|
||||
bar(double(simdates), squeeze(decomposition(endoidx, :, :))', 'stacked')
|
||||
legend(shocklist)
|
||||
end
|
||||
|
||||
end
|
||||
|
|
@ -338,6 +338,7 @@ MODFILES = \
|
|||
shock_decomposition/fs2000_est_varlist.mod \
|
||||
shock_decomposition/fs2000_cal_groups.mod \
|
||||
shock_decomposition/ls2003_plot.mod \
|
||||
shock_decomposition/shock_decomposition_backward.mod \
|
||||
stochastic_purely_forward/stochastic_purely_forward.mod \
|
||||
stochastic_purely_forward/stochastic_purely_forward_with_static.mod \
|
||||
forecast/Hansen_exo_det_forecast.mod \
|
||||
|
|
|
|||
|
|
@ -0,0 +1,146 @@
|
|||
// --+ options: json=compute, stochastic +--
|
||||
|
||||
/* This file tests the matlab/backward/shock_decomposition_backward.m routine,
|
||||
used for shock decomposition of nonlinear backward models */
|
||||
|
||||
var x1 x2 x3 x1bar x2bar z y x u v s;
|
||||
|
||||
varexo ex1
|
||||
ex2
|
||||
ex1bar (used='estimationonly')
|
||||
ex2bar (used='estimationonly')
|
||||
ez
|
||||
ey
|
||||
ex
|
||||
eu
|
||||
ev
|
||||
es;
|
||||
|
||||
parameters
|
||||
rho_1 rho_2 rho_3 rho_4
|
||||
a_x1_0 a_x1_1 a_x1_2 a_x1_x2_1 a_x1_x2_2
|
||||
a_x2_0 a_x2_1 a_x2_2 a_x2_x1_1 a_x2_x1_2
|
||||
e_c_m c_z_1 c_z_2 c_z_dx2 c_z_u c_z_dv c_z_s cx cy beta
|
||||
lambda
|
||||
px3;
|
||||
|
||||
rho_1 = .9;
|
||||
rho_2 = -.2;
|
||||
rho_3 = .4;
|
||||
rho_4 = -.3;
|
||||
|
||||
|
||||
a_x1_0 = -.9;
|
||||
a_x1_1 = .4;
|
||||
a_x1_2 = .3;
|
||||
a_x1_x2_1 = .1;
|
||||
a_x1_x2_2 = .2;
|
||||
|
||||
a_x2_0 = -.9;
|
||||
a_x2_1 = .2;
|
||||
a_x2_2 = -.1;
|
||||
a_x2_x1_1 = -.1;
|
||||
a_x2_x1_2 = .2;
|
||||
|
||||
beta = .2;
|
||||
e_c_m = .5;
|
||||
c_z_1 = .2;
|
||||
c_z_2 = -.1;
|
||||
c_z_dx2 = .3;
|
||||
c_z_u = .3;
|
||||
c_z_dv = .4;
|
||||
c_z_s = -.2;
|
||||
cx = 1.0;
|
||||
cy = 1.0;
|
||||
|
||||
|
||||
lambda = 0.5; // Share of optimizing agents.
|
||||
|
||||
px3 = -.1;
|
||||
|
||||
trend_component_model(model_name=toto, eqtags=['eq:x1', 'eq:x2', 'eq:x1bar', 'eq:x2bar'], targets=['eq:x1bar', 'eq:x2bar']);
|
||||
|
||||
pac_model(auxiliary_model_name=toto, discount=beta, model_name=pacman);
|
||||
|
||||
model;
|
||||
|
||||
[name='eq:s']
|
||||
s = .3*s(-1) - .1*s(-2) + es;
|
||||
|
||||
[name='eq:diff(v)']
|
||||
diff(v) = .5*diff(v(-1)) + ev;
|
||||
|
||||
[name='eq:u']
|
||||
u = .5*u(-1) - .2*u(-2) + eu;
|
||||
|
||||
[name='eq:y']
|
||||
y = rho_1*y(-1) + rho_2*y(-2) + ey;
|
||||
|
||||
[name='eq:x']
|
||||
x = rho_3*x(-1) + rho_4*x(-2) + ex;
|
||||
|
||||
[name='eq:x1']
|
||||
diff(x1) = a_x1_0*(x1(-1)-x1bar(-1)) + a_x1_1*diff(x1(-1)) + a_x1_2*diff(x1(-2)) + a_x1_x2_1*diff(x2(-1)) + a_x1_x2_2*diff(x2(-2)) + ex1;
|
||||
|
||||
[name='eq:x2']
|
||||
diff(x2) = a_x2_0*(x2(-1)-x2bar(-1)) + a_x2_1*diff(x1(-1)) + a_x2_2*diff(x1(-2)) + a_x2_x1_1*diff(x2(-1)) + a_x2_x1_2*diff(x2(-2)) + ex2;
|
||||
|
||||
[name='eq:x3']
|
||||
x3 = px3*x + y ;
|
||||
|
||||
[name='eq:x1bar']
|
||||
x1bar = x1bar(-1) + ex1bar;
|
||||
|
||||
[name='eq:x2bar']
|
||||
x2bar = x2bar(-1) + ex2bar;
|
||||
|
||||
[name='zpac']
|
||||
diff(z) = lambda*(e_c_m*(x1(-1)-z(-1)) + c_z_1*diff(z(-1)) + c_z_2*diff(z(-2)) + pac_expectation(pacman) + c_z_s*s + c_z_dv*diff(v) ) + (1-lambda)*( cy*y + cx*x) + c_z_u*u + c_z_dx2*diff(x2) + ez;
|
||||
|
||||
end;
|
||||
|
||||
shocks;
|
||||
var ex1 = 1.0;
|
||||
var ex2 = 1.0;
|
||||
var ex1bar = 1.0;
|
||||
var ex2bar = 1.0;
|
||||
var ez = 1.0;
|
||||
var ey = 0.1;
|
||||
var ex = 0.1;
|
||||
var eu = 0.05;
|
||||
var ev = 0.05;
|
||||
var es = 0.07;
|
||||
end;
|
||||
|
||||
shock_groups;
|
||||
g1 = ex, ey, ez;
|
||||
g2 = eu, ev;
|
||||
end;
|
||||
|
||||
|
||||
// Initialize the PAC model (build the Companion VAR representation for the auxiliary model).
|
||||
pac.initialize('pacman');
|
||||
|
||||
// Update the parameters of the PAC expectation model (h0 and h1 vectors).
|
||||
pac.update.expectation('pacman');
|
||||
|
||||
// Set initial conditions to zero for non logged variables, and one for logged variables
|
||||
init = zeros(10, M_.endo_nbr+M_.exo_nbr);
|
||||
initialconditions = dseries(init, 2000Q1, vertcat(M_.endo_names,M_.exo_names));
|
||||
|
||||
// Simulate the model for 500 periods
|
||||
TrueData = simul_backward_model(initialconditions, 500);
|
||||
|
||||
decomposition = shock_decomposition_backward(TrueData, initialconditions, { 'g1', 'g2', 'es' }, { 'z', 'y', 'u'});
|
||||
|
||||
% Verify that y is only influenced by g1 (which contains ey)
|
||||
y_idx = find(strcmp(M_.endo_names, 'y'));
|
||||
if ~(all(all(decomposition(y_idx, 2:3, :) == 0)) && all(all(decomposition(y_idx, 1, :) ~= 0)))
|
||||
error('Wrong decomposition for y')
|
||||
end
|
||||
|
||||
% Verify that u is only influenced by g2 (which contains eu)
|
||||
u_idx = find(strcmp(M_.endo_names, 'u'));
|
||||
if ~(all(all(decomposition(u_idx, [1 3], :) == 0)) && all(all(decomposition(u_idx, 2, :) ~= 0)))
|
||||
error('Wrong decomposition for u')
|
||||
end
|
||||
Loading…
Reference in New Issue