116 lines
3.8 KiB
Matlab
116 lines
3.8 KiB
Matlab
function dr=set_state_space(dr,M_)
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% dr=set_state_space(dr,M_)
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% Write the state space representation of the reduced form solution.
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%@info:
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%! @deftypefn {Function File} {[@var{dr} =} set_state_space (@var{dr},@var{M_})
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%! @anchor{set_state_space}
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%! @sp 1
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%! Write the state space representation of the reduced form solution.
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%! @sp 2
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%! @strong{Inputs}
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%! @sp 1
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%! @table @ @var
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%! @item dr
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%! Matlab's structure describing decision and transition rules.
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%! @item M_
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%! Matlab's structure describing the model (initialized by dynare, see @ref{M_})
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%! @end table
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%! @sp 2
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%! @strong{Outputs}
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%! @sp 1
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%! @table @ @var
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%! @item dr
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%! Matlab's structure describing decision and transition rules.
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%! @end table
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%! @sp 2
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%! @strong{This function is called by:}
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%! @sp 1
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%! @ref{check}, @ref{discretionary_policy_1}, @ref{dynare_estimation_init}, @ref{dyn_risky_steady_state_solver}, @ref{osr1}, @ref{partial_information/dr1_PI}, @ref{pea/pea_initialization}, @ref{stochastic_solvers}, @ref{stoch_simul}
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%! @sp 2
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%! @strong{This function calls:}
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%! @sp 2
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%! @end deftypefn
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%@eod:
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% Copyright © 1996-2023 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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max_lead = M_.maximum_endo_lead;
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max_lag = M_.maximum_endo_lag;
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endo_nbr = M_.endo_nbr;
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lead_lag_incidence = M_.lead_lag_incidence;
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klen = max_lag + max_lead + 1;
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fwrd_var = find(lead_lag_incidence(max_lag+2:end,:))';
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if max_lag > 0
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pred_var = find(lead_lag_incidence(1,:))';
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both_var = intersect(pred_var,fwrd_var);
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pred_var = setdiff(pred_var,both_var);
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fwrd_var = setdiff(fwrd_var,both_var);
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stat_var = setdiff([1:endo_nbr]',union(union(pred_var,both_var),fwrd_var)); % static variables
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else
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pred_var = [];
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both_var = [];
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stat_var = setdiff([1:endo_nbr]',fwrd_var);
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end
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order_var = [ stat_var(:); pred_var(:); both_var(:); fwrd_var(:)];
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inv_order_var(order_var) = (1:endo_nbr);
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% building kmask for z state vector in t+1
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if max_lag > 0
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kmask = [];
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if max_lead > 0
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kmask = lead_lag_incidence(max_lag+2,order_var) ;
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end
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kmask = [kmask; lead_lag_incidence(1,order_var)] ;
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else
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if max_lead==0 %%in this case lead_lag_incidence has no entry max_lag+2
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error('Dynare currently does not allow to solve purely static models in a stochastic context.')
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end
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kmask = lead_lag_incidence(max_lag+2,order_var) ;
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end
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kmask = kmask';
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kmask = kmask(:);
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i_kmask = find(kmask);
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nd = nnz(kmask); % size of the state vector
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kmask(i_kmask) = (1:nd);
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% auxiliary equations
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% composition of state vector
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% col 1: variable (index in DR-order); col 2: lead/lag in z(t+1);
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% col 3: A cols for t+1 (D); col 4: A cols for t (E)
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kstate = [ repmat([1:endo_nbr]',klen-1,1) kron([klen:-1:2]',ones(endo_nbr,1)) ...
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zeros((klen-1)*endo_nbr,2)];
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kiy = flipud(lead_lag_incidence(:,order_var))';
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kiy = kiy(:);
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if max_lead > 0
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kstate(1:endo_nbr,3) = kiy(1:endo_nbr)-nnz(lead_lag_incidence(max_lag+1,:));
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kstate(kstate(:,3) < 0,3) = 0;
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kstate(endo_nbr+1:end,4) = kiy(2*endo_nbr+1:end);
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else
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kstate(:,4) = kiy(endo_nbr+1:end);
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end
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kstate = kstate(i_kmask,:);
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dr.order_var = order_var;
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dr.inv_order_var = inv_order_var';
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dr.kstate = kstate;
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dr.transition_auxiliary_variables = [];
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