256 lines
6.2 KiB
Matlab
256 lines
6.2 KiB
Matlab
% Copyright (C) 2001 Michel Juillard
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%
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function dr=dr11(iorder,dr,cheik)
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global M_ options_ oo_
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global it_ stdexo_ means_ dr1_test_ bayestopt_
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% hack for Bayes
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global dr1_test_ bayestopt_
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options_ = set_default_option(options_,'loglinear',0);
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xlen = M_.maximum_lead + M_.maximum_lag + 1;
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klen = M_.maximum_lag + M_.maximum_lead + 1;
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iyv = transpose(M_.lead_lag_incidence);
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iyv = iyv(:);
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iyr0 = find(iyv) ;
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it_ = M_.maximum_lag + 1 ;
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if M_.exo_nbr == 0
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oo_.exo_steady_state = [] ;
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end
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if ~ M_.lead_lag_incidence(M_.maximum_lag+1,:) > 0
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error ('Error in model specification: some variables don"t appear as current') ;
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end
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if ~cheik
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% if xlen > 1
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% error (['SS: stochastic exogenous variables must appear only at the' ...
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% ' current period. Use additional endogenous variables']) ;
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% end
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end
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if M_.maximum_lead > 1 & iorder > 1
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error (['Models with leads on more than one period can only be solved' ...
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' at order 1'])
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end
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dr=set_state_space(dr);
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kstate = dr.kstate;
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kad = dr.kad;
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kae = dr.kae;
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nstatic = dr.nstatic;
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nfwrd = dr.nfwrd;
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npred = dr.npred;
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nboth = dr.nboth;
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order_var = dr.order_var;
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nd = size(kstate,1);
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sdyn = M_.endo_nbr - nstatic;
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tempex = oo_.exo_simul;
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it_ = M_.maximum_lag + 1;
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z = repmat(dr.ys,1,klen);
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z = z(iyr0) ;
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%M_.jacobia=real(diffext('ff1_',[z; oo_.exo_steady_state])) ;
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%M_.jacobia=real(jacob_a('ff1_',[z; oo_.exo_steady_state])) ;
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[junk,M_.jacobia] = feval([M_.fname '_dynamic'],z,oo_.exo_simul);
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oo_.exo_simul = tempex ;
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tempex = [];
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nz = size(z,1);
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k1 = M_.lead_lag_incidence(find([1:klen] ~= M_.maximum_lag+1),:);
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b = M_.jacobia(:,M_.lead_lag_incidence(M_.maximum_lag+1,order_var));
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a = b\M_.jacobia(:,nonzeros(k1'));
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if any(isinf(a(:)))
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dr1_test_(1) = 5;
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dr1_test_(2) = bayestopt_.penalty;
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end
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if M_.exo_nbr
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fu = b\M_.jacobia(:,nz+1:end);
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end
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if M_.maximum_lead == 0 & M_.maximum_lag == 1; % backward model with one lag
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dr.ghx = -a;
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dr.ghu = -fu;
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return;
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elseif M_.maximum_lead == 0 & M_.maximum_lag > 1 % backward model with lags on more than
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% one period
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e = zeros(endo_nbr,nd);
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k = find(kstate(:,2) <= M_.maximum_lag+1 & kstate(:,4));
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e(:,k) = -a(:,kstate(k,4)) ;
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dr.ghx = e;
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dr.ghu = -fu;
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end
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% buildind D and E
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d = zeros(nd,nd) ;
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e = d ;
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k = find(kstate(:,2) >= M_.maximum_lag+2 & kstate(:,3));
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d(1:sdyn,k) = a(nstatic+1:end,kstate(k,3)) ;
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k1 = find(kstate(:,2) == M_.maximum_lag+2);
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a1 = eye(sdyn);
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e(1:sdyn,k1) = -a1(:,kstate(k1,1)-nstatic);
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k = find(kstate(:,2) <= M_.maximum_lag+1 & kstate(:,4));
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e(1:sdyn,k) = -a(nstatic+1:end,kstate(k,4)) ;
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k2 = find(kstate(:,2) == M_.maximum_lag+1);
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k2 = k2(~ismember(kstate(k2,1),kstate(k1,1)));
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d(1:sdyn,k2) = a1(:,kstate(k2,1)-nstatic);
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if ~isempty(kad)
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for j = 1:size(kad,1)
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d(sdyn+j,kad(j)) = 1 ;
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e(sdyn+j,kae(j)) = 1 ;
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end
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end
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options_ = set_default_option(options_,'qz_criterium',1.000001);
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if ~exist('mjdgges')
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% using Chris Sim's routines
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use_qzdiv = 1;
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[ss,tt,qq,w] = qz(e,d);
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[tt,ss,qq,w] = qzdiv(options_.qz_criterium,tt,ss,qq,w);
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ss1=diag(ss);
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tt1=diag(tt);
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warning_state = warning;
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warning off;
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oo_.eigenvalues = ss1./tt1 ;
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warning warning_state;
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nba = nnz(abs(eigval) > options_.qz_criterium);
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else
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use_qzdiv = 0;
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[ss,tt,w,sdim,oo_.eigenvalues,info] = mjdgges(e,d,options_.qz_criterium);
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if info & info ~= nd+2;
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error(['ERROR' info ' in MJDGGES.DLL']);
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end
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nba = nd-sdim;
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end
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nyf = sum(kstate(:,2) > M_.maximum_lag+1);
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if cheik
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dr.rank = rank(w(1:nyf,nd-nyf+1:end));
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% dr.eigval = oo_.eigenvalues;
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return
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end
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eigenvalues = sort(oo_.eigenvalues);
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if nba > nyf;
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% disp('Instability !');
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dr1_test_(1) = 3; %% More eigenvalues superior to unity than forward variables ==> instability.
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dr1_test_(2) = (abs(eigenvalues(nd-nba+1:nd-nyf))-1-1e-5)'*...
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(abs(eigenvalues(nd-nba+1:nd-nyf))-1-1e-5);% Distance to Blanchard-Khan conditions (penalty)
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return
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elseif nba < nyf;
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% disp('Indeterminacy !');
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dr1_test_(1) = 2; %% ==> Indeterminacy.
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dr1_test_(2) = (abs(eigenvalues(nd-nyf+1:nd-nba))-1-1e-5)'*...
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(abs(eigenvalues(nd-nyf+1:nd-nba))-1-1e-5);% Distance to Blanchard-Khan conditions (penality)
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%% warning('DR1: Blanchard-Kahn conditions are not satisfied. Run CHEIK to learn more!');
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return
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end
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np = nd - nyf;
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n2 = np + 1;
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n3 = nyf;
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n4 = n3 + 1;
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% derivatives with respect to dynamic state variables
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% forward variables
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if condest(w(1:n3,n2:nd)) > 1e9
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% disp('Indeterminacy !!');
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dr1_test_(1) = 2;
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dr1_test_(2) = 1;
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return
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end
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warning_state = warning;
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lastwarn('');
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warning off;
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gx = -w(1:n3,n2:nd)'\w(n4:nd,n2:nd)';
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if length(lastwarn) > 0;
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% disp('Indeterminacy !!');
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dr1_test_(1) = 2;
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dr1_test_(2) = 1;
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warning(warning_state);
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return
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end
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% predetermined variables
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hx = w(1:n3,1:np)'*gx+w(n4:nd,1:np)';
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hx = (tt(1:np,1:np)*hx)\(ss(1:np,1:np)*hx);
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lastwarn('');
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if length(lastwarn) > 0;
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% disp('Singularity problem in dr11.m');
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dr1_test_(1) = 2;
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dr1_test_(2) = 1;
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warning(warning_state);
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return
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end
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k1 = find(kstate(n4:nd,2) == M_.maximum_lag+1);
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k2 = find(kstate(1:n3,2) == M_.maximum_lag+2);
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dr.ghx = [hx(k1,:); gx(k2(nboth+1:end),:)];
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%lead variables actually present in the model
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j3 = nonzeros(kstate(:,3));
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j4 = find(kstate(:,3));
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% derivatives with respect to exogenous variables
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if M_.exo_nbr
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a1 = eye(M_.endo_nbr);
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aa1 = [];
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if nstatic > 0
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aa1 = a1(:,1:nstatic);
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end
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dr.ghu = -[aa1 a(:,j3)*gx(j4,1:npred)+a1(:,nstatic+1:nstatic+ ...
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npred) a1(:,nstatic+npred+1:end)]\fu;
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lastwarn('');
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if length(lastwarn) > 0;
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% disp('Singularity problem in dr11.m');
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dr1_test_(1) = 2;
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dr1_test_(2) = 1;
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return
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end
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end
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warning(warning_state);
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% static variables
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if nstatic > 0
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temp = -a(1:nstatic,j3)*gx(j4,:)*hx;
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j5 = find(kstate(n4:nd,4));
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temp(:,j5) = temp(:,j5)-a(1:nstatic,nonzeros(kstate(:,4)));
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dr.ghx = [temp; dr.ghx];
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temp = [];
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end
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if options_.loglinear == 1
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k = find(dr.kstate(:,2) <= M_.maximum_lag+1);
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klag = dr.kstate(k,[1 2]);
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k1 = dr.order_var;
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dr.ghx = repmat(1./dr.ys(k1),1,size(dr.ghx,2)).*dr.ghx.* ...
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repmat(dr.ys(k1(klag(:,1)))',size(dr.ghx,1),1);
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dr.ghu = repmat(1./dr.ys(k1),1,size(dr.ghu,2)).*dr.ghu;
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end
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% necessary when using Sims' routines
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if use_qzdiv
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gx = real(gx);
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hx = real(hx);
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dr.ghx = real(dr.ghx);
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dr.ghu = real(dr.ghu);
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end
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