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v4 bvar_forecast: added storage of results in oo_ 

git-svn-id: https://www.dynare.org/svn/dynare/dynare_v4@1482 ac1d8469-bf42-47a9-8791-bf33cf982152
time-shift
sebastien 2007-12-07 14:27:37 +00:00
parent fd6f89e0f3
commit ddc81ce534
3 changed files with 50 additions and 9 deletions
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doc/bvar-a-la-sims.pdf
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doc/bvar-a-la-sims.tex
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@ -504,6 +504,14 @@ The command will produce one graph per observed variable. Each graph displays:
Morever, if option \texttt{nobs} is specified, the command will also compute root mean squared error (RMSE) for all variables between end of sample and end of datafile.
Most results are stored for future use:
\begin{itemize}
\item mean, median, variance and confidence intervals for forecasts (with shocks) are stored in \texttt{oo\_.bvar.forecast.with\_shocks} (in time series form),
\item \textit{idem} for forecasts without shocks in \texttt{oo\_.bvar.forecast.no\_shock},
\item all simulated samples are stored in variables \texttt{sims\_no\_shock} and \texttt{sims\_with\_shocks} in file \textit{mod\_file}\texttt{/bvar\_forecast/simulations.mat}. Those variables are 3-dimensional arrays: first dimension is time, second dimension is variable (in the order of the \texttt{varobs} declaration), third dimension indexes the sample number,
\item if RMSE has been computed, results are in \texttt{oo\_.bvar.forecast.rmse}.
\end{itemize}
\section{Examples}
This section presents two short examples of BVAR estimations. These examples and the associated datafile (\texttt{test.xls}) can be found in the \texttt{tests/bvar\_a\_la\_sims} directory of the Dynare v4 subversion tree.

51
matlab/bvar_forecast.m
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@ -1,6 +1,6 @@
function bvar_forecast(nlags)
global options_
global options_ oo_ M_
options_ = set_default_option(options_, 'bvar_replic', 2000);
if options_.forecast == 0
@ -20,12 +20,14 @@ function bvar_forecast(nlags)
k = ny*nlags+nx;
% Declaration of the companion matrix:
% Declaration of the companion matrix
Companion_matrix = diag(ones(ny*(nlags-1),1),-ny);
% Number of explosive VAR models sampled
p = 0;
% Number of non-explosive VAR models sampled
d = 0;
while d<=options_.bvar_replic
while d <= options_.bvar_replic
Sigma = rand_inverse_wishart(ny, posterior.df, S_inv_upper_chol);
@ -46,7 +48,6 @@ function bvar_forecast(nlags)
% Without shocks
lags_data = forecast_data.initval;
for t = 1:options_.forecast
X = [ reshape(flipdim(lags_data, 1)', 1, ny*nlags) forecast_data.xdata(t, :) ];
y = X * Phi;
@ -67,10 +68,12 @@ function bvar_forecast(nlags)
end
end
disp('')
disp(['Some of the VAR models sampled from the posterior distribution'])
disp(['were found to be explosive (' int2str(p) ').'])
disp('')
if p > 0
disp('')
disp(['Some of the VAR models sampled from the posterior distribution'])
disp(['were found to be explosive (' int2str(p) ' samples).'])
disp('')
end
% Plot graphs
sims_no_shock_mean = mean(sims_no_shock, 3);
@ -118,5 +121,35 @@ function bvar_forecast(nlags)
for i = 1:size(options_.varobs, 1)
fprintf('%s: %10.4f\n', options_.varobs(i, :), rmse(i));
end
end
% Store results
DirectoryName = [ M_.fname '/bvar_forecast' ];
if ~isdir(DirectoryName)
mkdir('.',DirectoryName);
end
save([ DirectoryName '/simulations'], 'sims_no_shock', 'sims_with_shocks');
for i = 1:size(options_.varobs, 1)
name = options_.varobs(i, :);
sims = squeeze(sims_with_shocks(:,i,:));
eval(['oo_.bvar.forecast.with_shocks.Mean.' name ' = mean(sims, 2);']);
eval(['oo_.bvar.forecast.with_shocks.Median.' name ' = median(sims, 2);']);
eval(['oo_.bvar.forecast.with_shocks.Var.' name ' = var(sims, 0, 2);']);
eval(['oo_.bvar.forecast.with_shocks.HPDsup.' name ' = sims_with_shocks_up_conf(:,i);']);
eval(['oo_.bvar.forecast.with_shocks.HPDinf.' name ' = sims_with_shocks_down_conf(:,i);']);
sims = squeeze(sims_no_shock(:,i,:));
eval(['oo_.bvar.forecast.no_shock.Mean.' name ' = sims_no_shock_mean(:,i);']);
eval(['oo_.bvar.forecast.no_shock.Median.' name ' = median(sims, 2);']);
eval(['oo_.bvar.forecast.no_shock.Var.' name ' = var(sims, 0, 2);']);
eval(['oo_.bvar.forecast.no_shock.HPDsup.' name ' = sims_no_shock_up_conf(:,i);']);
eval(['oo_.bvar.forecast.no_shock.HPDinf.' name ' = sims_no_shock_down_conf(:,i);']);
if exist('rmse')
eval(['oo_.bvar.forecast.rmse.' name ' = rmse(i);']);
end
end
end