53 lines
1.4 KiB
Matlab
53 lines
1.4 KiB
Matlab
function y = irf(dr, e1, long, drop, replic, iorder)
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% function y = irf(dr, e1, long, drop, replic, iorder)
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% Computes impulse response functions
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%
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% INPUTS
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% dr: structure of decisions rules for stochastic simulations
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% e1: exogenous variables value in time 1 after one shock
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% long
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% drop: truncation (in order 2)
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% replic: number of replications (in order 2)
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% iorder: first or second order approximation
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%
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% OUTPUTS
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% y: impulse response matrix
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%
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% SPECIAL REQUIREMENTS
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% none
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%
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% part of DYNARE, copyright Dynare Team (2003-2008)
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% Gnu Public License.
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global M_ oo_ options_
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temps = repmat(dr.ys,1,M_.maximum_lag);
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y = 0;
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if iorder == 1
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y1 = repmat(dr.ys,1,long);
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ex2 = zeros(long,M_.exo_nbr);
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ex2(1,:) = e1';
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y2 = simult_(temps,dr,ex2,iorder);
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y = y2(:,M_.maximum_lag+1:end)-y1;
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else
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% eliminate shocks with 0 variance
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i_exo_var = setdiff([1:M_.exo_nbr],find(diag(M_.Sigma_e) == 0 ));
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nxs = length(i_exo_var);
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ex1 = zeros(long+drop,M_.exo_nbr);
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ex2 = ex1;
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chol_S = chol(M_.Sigma_e(i_exo_var,i_exo_var));
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for j = 1: replic
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randn('seed',j);
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ex1(:,i_exo_var) = randn(long+drop,nxs)*chol_S;
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ex2 = ex1;
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ex2(drop+1,:) = ex2(drop+1,:)+e1';
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y1 = simult_(temps,dr,ex1,iorder);
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y2 = simult_(temps,dr,ex2,iorder);
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y = y+(y2(:,M_.maximum_lag+drop+1:end)-y1(:,M_.maximum_lag+drop+1:end));
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end
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y=y/replic;
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end
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