73 lines
2.0 KiB
Matlab
73 lines
2.0 KiB
Matlab
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function z = shock_decomposition(M_,oo_,varlist)
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% function z = shock_decomposition(R,epsilon,varlist)
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% Computes shocks contribution to a simulated trajectory
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%
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% INPUTS
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% R: mm*rr matrix of shock impact
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% epsilon: rr*nobs matrix of shocks
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% varlist: list of variables
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%
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% OUTPUTS
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% z: nvar*rr*nobs shock decomposition
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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 (2004-2008)
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% Gnu Public License.
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% number of variables
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endo_nbr = M_.endo_nbr;
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% number of shocks
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nshocks = M_.exo_nbr;
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% indices of endogenous variables
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[i_var,nvar] = varlist_indices(varlist);
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% reduced form
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dr = oo_.dr;
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% data reordering
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order_var = dr.order_var;
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inv_order_var = dr.inv_order_var;
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% coefficients
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A = dr.ghx;
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B = dr.ghu;
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% initialization
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for i=1:nshocks
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epsilon(i,:) = eval(['oo_.SmoothedShocks.' M_.exo_names(i,:)]);
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end
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gend = size(epsilon,2);
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z = zeros(endo_nbr,nshocks+2,gend);
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for i=1:endo_nbr
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z(i,end,:) = eval(['oo_.SmoothedVariables.' M_.endo_names(i,:)]);
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end
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maximum_lag = M_.maximum_lag;
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lead_lag_incidence = M_.lead_lag_incidence;
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for i=1:gend
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if i > 1 & i <= maximum_lag+1
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lags = min(i-1,maximum_lag):-1:1;
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k2 = dr.kstate(find(dr.kstate(:,2) <= min(i,maximum_lag)+1),[1 2]);
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i_state = order_var(k2(:,1))+(min(i,maximum_lag)+1-k2(:,2))*M_.endo_nbr;
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end
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if i > 1
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tempx = permute(z(:,1:nshocks,lags),[1 3 2]);
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m = min(i-1,maximum_lag);
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tempx = [reshape(tempx,endo_nbr*m,nshocks); zeros(endo_nbr*(maximum_lag-i+1),nshocks)];
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z(:,1:nshocks,i) = A(inv_order_var,:)*tempx(i_state,:);
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lags = lags+1;
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end
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z(:,1:nshocks,i) = z(:,1:nshocks,i) + B(inv_order_var,:).*repmat(epsilon(:,i)',nvar,1);
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z(:,nshocks+1,i) = z(:,nshocks+2,i) - sum(z(:,1:nshocks,i),2);
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end
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