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Explosive VARs (the companion matrix has eigenvalues outside the unit circle) are discarded from the posterior distribution (by default). 

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@1388 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
adjemian 2007-09-21 12:17:56 +00:00
parent 97d78558d3
commit 1224cec429
1 changed files with 26 additions and 3 deletions
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29
matlab/bvar_forecast.m
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@ -2,12 +2,14 @@ function bvar_forecast(nlags)
global options_ global options_
nvar = size(options_.varobs,1);
options_ = set_default_option(options_, 'bvar_replic', 2000); options_ = set_default_option(options_, 'bvar_replic', 2000);
if options_.forecast == 0 if options_.forecast == 0
error('bvar_forecast: you must specify "forecast" option') error('bvar_forecast: you must specify "forecast" option')
end end
[ny, nx, posterior, prior, forecast_data] = bvar_toolbox(nlags); [ny, nx, posterior, prior, forecast_data] = bvar_toolbox(nlags);
sims_no_shock = NaN(options_.forecast, ny, options_.bvar_replic); sims_no_shock = NaN(options_.forecast, ny, options_.bvar_replic);
sims_with_shocks = NaN(options_.forecast, ny, options_.bvar_replic); sims_with_shocks = NaN(options_.forecast, ny, options_.bvar_replic);
@ -20,7 +22,14 @@ function bvar_forecast(nlags)
k = ny*nlags+nx; k = ny*nlags+nx;
for d = 1:options_.bvar_replic % Declaration of the companion matrix:
Companion_matrix = diag(ones(nvar*(nlags-1),1),-nvar);
p = 0;
d = 0;
while d<=options_.bvar_replic
d = d+1;
Sigma = rand_inverse_wishart(ny, posterior.df, S_inv_upper_chol); Sigma = rand_inverse_wishart(ny, posterior.df, S_inv_upper_chol);
% Option 'lower' of chol() not available in old versions of % Option 'lower' of chol() not available in old versions of
@ -29,6 +38,15 @@ function bvar_forecast(nlags)
Phi = rand_matrix_normal(k, ny, posterior.PhiHat, XXi_lower_chol, Sigma_lower_chol); Phi = rand_matrix_normal(k, ny, posterior.PhiHat, XXi_lower_chol, Sigma_lower_chol);
% All the eigenvalues of the companion matrix have to be on or inside the unit circle
Companion_matrix(1:nvar,:) = Phi(1:nvar*nlags,:)';
test = (abs(eig(Companion_matrix)));
if any(test>1.0000000000001)
p = p+1;
d = d-1;
continue
end
% Without shocks % Without shocks
lags_data = forecast_data.initval; lags_data = forecast_data.initval;
for t = 1:options_.forecast for t = 1:options_.forecast
@ -48,7 +66,12 @@ function bvar_forecast(nlags)
sims_with_shocks(t, :, d) = y; sims_with_shocks(t, :, d) = y;
end end
end end
disp('')
disp(['Some of the VAR models sampled from the posterior distribution'])
disp(['were found to be explosive (' int2str(p) ').'])
disp('')
% Plot graphs % Plot graphs
sims_no_shock_mean = mean(sims_no_shock, 3); sims_no_shock_mean = mean(sims_no_shock, 3);