diff --git a/matlab/partial_information/PCL_Part_info_irf.m b/matlab/partial_information/PCL_Part_info_irf.m
index 81277b14fed67be3d61bf447d3c9e2820111c652..cd23fd775b03e1c3a3ecb26cb20f396b7e35ab61 100644
--- a/matlab/partial_information/PCL_Part_info_irf.m
+++ b/matlab/partial_information/PCL_Part_info_irf.m
@@ -1,147 +1,138 @@
-function y=PCL_Part_info_irf( H, varobs, ivar, M_, dr, irfpers,ii)
-% sets up parameters and calls part-info kalman filter
-% developed by G Perendia, July 2006 for implementation from notes by Prof. Joe Pearlman to
-% suit partial information RE solution in accordance with, and based on, the
-% Pearlman, Currie and Levine 1986 solution.
-% 22/10/06 - Version 2 for new Riccati with 4 params instead 5
-
-% Copyright (C) 2001-20010 Dynare Team
-%
-% This file is part of Dynare.
-%
-% Dynare is free software: you can redistribute it and/or modify
-% it under the terms of the GNU General Public License as published by
-% the Free Software Foundation, either version 3 of the License, or
-% (at your option) any later version.
-%
-% Dynare is distributed in the hope that it will be useful,
-% but WITHOUT ANY WARRANTY; without even the implied warranty of
-% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-% GNU General Public License for more details.
-%
-% You should have received a copy of the GNU General Public License
-% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
-
-
-% Recall that the state space is given by the
-% predetermined variables s(t-1), x(t-1)
-% and the jump variables x(t).
-% The jump variables have dimension NETA
-
-
- [junk,OBS] = ismember(varobs,M_.endo_names,'rows');
-
- G1=dr.PI_ghx;
- impact=dr.PI_ghu;
- nmat=dr.PI_nmat;
- CC=dr.PI_CC;
- NX=M_.exo_nbr; % no of exogenous varexo shock variables.
- FL_RANK=dr.PI_FL_RANK;
- NY=M_.endo_nbr;
- if isempty(OBS)
- NOBS=NY;
- LL=eye(NY,NY);
- else %and if no obsevations specify OBS=[0] but this is not going to work properly
- NOBS=length(OBS);
- LL=zeros(NOBS,NY);
- for i=1:NOBS
- LL(i,OBS(i))=1;
- end
- end
-
- ss=size(G1,1);
- pd=ss-size(nmat,1);
- SDX=M_.Sigma_e^0.5; % =SD,not V-COV, of Exog shocks or M_.Sigma_e^0.5 num_exog x num_exog matrix
- if isempty(H)
- H=M_.H;
- end
- VV=H; % V-COV of observation errors.
- MM=impact*SDX; % R*(Q^0.5) in standard KF notation
- % observation vector indices
- % mapping to endogenous variables.
-
- L1=LL*dr.PI_TT1;
- L2=LL*dr.PI_TT2;
-
- MM1=MM(1:ss-FL_RANK,:);
- U11=MM1*MM1';
- % SDX
-
- U22=0;
- % determine K1 and K2 observation mapping matrices
- % This uses the fact that measurements are given by L1*s(t)+L2*x(t)
- % and s(t) is expressed in the dynamics as
- % H1*eps(t)+G11*s(t-1)+G12*x(t-1)+G13*x(t).
- % Thus the observations o(t) can be written in the form
- % o(t)=K1*[eps(t)' s(t-1)' x(t-1)']' + K2*x(t) where
- % K1=[L1*H1 L1*G11 L1*G12] K2=L1*G13+L2
-
- G12=G1(NX+1:ss-2*FL_RANK,:);
- KK1=L1*G12;
- K1=KK1(:,1:ss-FL_RANK);
- K2=KK1(:,ss-FL_RANK+1:ss)+L2;
-
- %pre calculate time-invariant factors
- A11=G1(1:pd,1:pd);
- A22=G1(pd+1:end, pd+1:end);
- A12=G1(1:pd, pd+1:end);
- A21=G1(pd+1:end,1:pd);
- Lambda= nmat*A12+A22;
- I_L=inv(Lambda);
- BB=A12*inv(A22);
- FF=K2*inv(A22);
- QQ=BB*U22*BB' + U11;
- UFT=U22*FF';
- AA=A11-BB*A21;
- CCCC=A11-A12*nmat; % F in new notation
- DD=K1-FF*A21; % H in new notation
- EE=K1-K2*nmat;
- RR=FF*UFT+VV;
- if ~any(RR)
- % if zero add some dummy measurement err. variance-covariances
- % with diagonals 0.000001. This would not be needed if we used
- % the slow solver, or the generalised eigenvalue approach,
- % but these are both slower.
- RR=eye(size(RR,1))*1.0e-6;
- end
- SS=BB*UFT;
- VKLUFT=VV+K2*I_L*UFT;
- ALUFT=A12*I_L*UFT;
- FULKV=FF*U22*I_L'*K2'+VV;
- FUBT=FF*U22*BB';
- nmat=nmat;
- % initialise pshat
- AQDS=AA*QQ*DD'+SS;
- DQDR=DD*QQ*DD'+RR;
- I_DQDR=inv(DQDR);
- AQDQ=AQDS*I_DQDR;
- ff=AA-AQDQ*DD;
- hh=AA*QQ*AA'-AQDQ*AQDS';%*(DD*QQ*AA'+SS');
- rr=DD*QQ*DD'+RR;
- ZSIG0=disc_riccati_fast(ff,DD,rr,hh);
- PP=ZSIG0 +QQ;
-
- exo_names=M_.exo_names(M_.exo_names_orig_ord,:);
-
- DPDR=DD*PP*DD'+RR;
- I_DPDR=inv(DPDR);
- PDIDPDRD=PP*DD'*I_DPDR*DD;
- GG=[CCCC (AA-CCCC)*(eye(ss-FL_RANK)-PDIDPDRD); zeros(ss-FL_RANK) AA*(eye(ss-FL_RANK)-PDIDPDRD)];
- imp=[impact(1:ss-FL_RANK,:); impact(1:ss-FL_RANK,:)];
-
- % Calculate IRFs of observable series
- I_PD=(eye(ss-FL_RANK)-PDIDPDRD);
- LL0=[ EE (DD-EE)*I_PD];
- VV = [ dr.PI_TT1 dr.PI_TT2];
- stderr=diag(M_.Sigma_e^0.5);
- irfmat=zeros(size(dr.PI_TT1 ,1),irfpers+1);
- irfst=zeros(size(GG,1),irfpers+1);
- irfst(:,1)=stderr(ii)*imp(:,ii);
- for jj=2:irfpers+1;
- irfst(:,jj)=GG*irfst(:,jj-1);
- irfmat(:,jj-1)=VV*irfst(NX+1:ss-FL_RANK,jj);
- end
- y=zeros(M_.endo_nbr,irfpers);
- y(:,:)=irfmat(:,1:irfpers);
-
- save ([M_.fname '_PCL_PtInfoIRFs_' num2str(ii) '_' deblank(exo_names(ii,:))], 'irfmat','irfst');
+function y=PCL_Part_info_irf( H, varobs, ivar, M_, dr, irfpers,ii)
+% sets up parameters and calls part-info kalman filter
+% developed by G Perendia, July 2006 for implementation from notes by Prof. Joe Pearlman to
+% suit partial information RE solution in accordance with, and based on, the
+% Pearlman, Currie and Levine 1986 solution.
+% 22/10/06 - Version 2 for new Riccati with 4 params instead 5
+
+% Copyright (C) 2006-2010 Dynare Team
+%
+% This file is part of Dynare.
+%
+% Dynare is free software: you can redistribute it and/or modify
+% it under the terms of the GNU General Public License as published by
+% the Free Software Foundation, either version 3 of the License, or
+% (at your option) any later version.
+%
+% Dynare is distributed in the hope that it will be useful,
+% but WITHOUT ANY WARRANTY; without even the implied warranty of
+% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+% GNU General Public License for more details.
+%
+% You should have received a copy of the GNU General Public License
+% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
+
+
+% Recall that the state space is given by the
+% predetermined variables s(t-1), x(t-1)
+% and the jump variables x(t).
+% The jump variables have dimension NETA
+
+
+ [junk,OBS] = ismember(varobs,M_.endo_names,'rows');
+ NOBS = length(OBS);
+
+ G1=dr.PI_ghx;
+ impact=dr.PI_ghu;
+ nmat=dr.PI_nmat;
+ CC=dr.PI_CC;
+ NX=M_.exo_nbr; % no of exogenous varexo shock variables.
+ FL_RANK=dr.PI_FL_RANK;
+ NY=M_.endo_nbr;
+ LL = sparse(1:NOBS,OBS,ones(NOBS,1),NY,NY);
+
+ ss=size(G1,1);
+ pd=ss-size(nmat,1);
+ SDX=M_.Sigma_e^0.5; % =SD,not V-COV, of Exog shocks or M_.Sigma_e^0.5 num_exog x num_exog matrix
+ if isempty(H)
+ H=M_.H;
+ end
+ VV=H; % V-COV of observation errors.
+ MM=impact*SDX; % R*(Q^0.5) in standard KF notation
+ % observation vector indices
+ % mapping to endogenous variables.
+
+ L1=LL*dr.PI_TT1;
+ L2=LL*dr.PI_TT2;
+
+ MM1=MM(1:ss-FL_RANK,:);
+ U11=MM1*MM1';
+ % SDX
+
+ U22=0;
+ % determine K1 and K2 observation mapping matrices
+ % This uses the fact that measurements are given by L1*s(t)+L2*x(t)
+ % and s(t) is expressed in the dynamics as
+ % H1*eps(t)+G11*s(t-1)+G12*x(t-1)+G13*x(t).
+ % Thus the observations o(t) can be written in the form
+ % o(t)=K1*[eps(t)' s(t-1)' x(t-1)']' + K2*x(t) where
+ % K1=[L1*H1 L1*G11 L1*G12] K2=L1*G13+L2
+
+ G12=G1(NX+1:ss-2*FL_RANK,:);
+ KK1=L1*G12;
+ K1=KK1(:,1:ss-FL_RANK);
+ K2=KK1(:,ss-FL_RANK+1:ss)+L2;
+
+ %pre calculate time-invariant factors
+ A11=G1(1:pd,1:pd);
+ A22=G1(pd+1:end, pd+1:end);
+ A12=G1(1:pd, pd+1:end);
+ A21=G1(pd+1:end,1:pd);
+ Lambda= nmat*A12+A22;
+ I_L=inv(Lambda);
+ BB=A12*inv(A22);
+ FF=K2*inv(A22);
+ QQ=BB*U22*BB' + U11;
+ UFT=U22*FF';
+ AA=A11-BB*A21;
+ CCCC=A11-A12*nmat; % F in new notation
+ DD=K1-FF*A21; % H in new notation
+ EE=K1-K2*nmat;
+ RR=FF*UFT+VV;
+ if ~any(RR)
+ % if zero add some dummy measurement err. variance-covariances
+ % with diagonals 0.000001. This would not be needed if we used
+ % the slow solver, or the generalised eigenvalue approach,
+ % but these are both slower.
+ RR=eye(size(RR,1))*1.0e-6;
+ end
+ SS=BB*UFT;
+ VKLUFT=VV+K2*I_L*UFT;
+ ALUFT=A12*I_L*UFT;
+ FULKV=FF*U22*I_L'*K2'+VV;
+ FUBT=FF*U22*BB';
+ nmat=nmat;
+ % initialise pshat
+ AQDS=AA*QQ*DD'+SS;
+ DQDR=DD*QQ*DD'+RR;
+ I_DQDR=inv(DQDR);
+ AQDQ=AQDS*I_DQDR;
+ ff=AA-AQDQ*DD;
+ hh=AA*QQ*AA'-AQDQ*AQDS';%*(DD*QQ*AA'+SS');
+ rr=DD*QQ*DD'+RR;
+ ZSIG0=disc_riccati_fast(ff,DD,rr,hh);
+ PP=ZSIG0 +QQ;
+
+ exo_names=M_.exo_names(M_.exo_names_orig_ord,:);
+
+ DPDR=DD*PP*DD'+RR;
+ I_DPDR=inv(DPDR);
+ PDIDPDRD=PP*DD'*I_DPDR*DD;
+ GG=[CCCC (AA-CCCC)*(eye(ss-FL_RANK)-PDIDPDRD); zeros(ss-FL_RANK) AA*(eye(ss-FL_RANK)-PDIDPDRD)];
+ imp=[impact(1:ss-FL_RANK,:); impact(1:ss-FL_RANK,:)];
+
+ % Calculate IRFs of observable series
+ I_PD=(eye(ss-FL_RANK)-PDIDPDRD);
+ LL0=[ EE (DD-EE)*I_PD];
+ VV = [ dr.PI_TT1 dr.PI_TT2];
+ stderr=diag(M_.Sigma_e^0.5);
+ irfmat=zeros(size(dr.PI_TT1 ,1),irfpers+1);
+ irfst=zeros(size(GG,1),irfpers+1);
+ irfst(:,1)=stderr(ii)*imp(:,ii);
+ for jj=2:irfpers+1;
+ irfst(:,jj)=GG*irfst(:,jj-1);
+ irfmat(:,jj-1)=VV*irfst(NX+1:ss-FL_RANK,jj);
+ end
+ y = irfmat(:,1:irfpers);
+
+ save ([M_.fname '_PCL_PtInfoIRFs_' num2str(ii) '_' deblank(exo_names(ii,:))], 'irfmat','irfst');
diff --git a/matlab/partial_information/PCL_Part_info_moments.m b/matlab/partial_information/PCL_Part_info_moments.m
index f0e42ea18dbfe68aa1a3582d1acaf597fcba6a9d..0dea34f3a7baad561bda7af976b640c08a70e072 100644
--- a/matlab/partial_information/PCL_Part_info_moments.m
+++ b/matlab/partial_information/PCL_Part_info_moments.m
@@ -5,7 +5,7 @@ function AutoCOR_YRk=PCL_Part_info_irmoments( H, varobs, dr,ivar)
% Pearlman, Currie and Levine 1986 solution.
% 22/10/06 - Version 2 for new Riccati with 4 params instead 5
-% Copyright (C) 2001-20010 Dynare Team
+% Copyright (C) 2006-2010 Dynare Team
%
% This file is part of Dynare.
%
@@ -32,6 +32,7 @@ function AutoCOR_YRk=PCL_Part_info_irmoments( H, varobs, dr,ivar)
warning off
[junk,OBS] = ismember(varobs,M_.endo_names,'rows');
+ NOBS = length(OBS);
G1=dr.PI_ghx;
impact=dr.PI_ghu;
@@ -40,16 +41,7 @@ function AutoCOR_YRk=PCL_Part_info_irmoments( H, varobs, dr,ivar)
NX=M_.exo_nbr; % no of exogenous varexo shock variables.
FL_RANK=dr.PI_FL_RANK;
NY=M_.endo_nbr;
- if isempty(OBS)
- NOBS=NY;
- LL=eye(NY,NY);
- else %and if no obsevations specify OBS=[0] but this is not going to work properly
- NOBS=length(OBS);
- LL=zeros(NOBS,NY);
- for i=1:NOBS
- LL(i,OBS(i))=1;
- end
- end
+ LL = sparse(1:NOBS,OBS,ones(NOBS,1),NY,NY);
if exist( 'irfpers')==1
if ~isempty(irfpers)
@@ -156,7 +148,7 @@ function AutoCOR_YRk=PCL_Part_info_irmoments( H, varobs, dr,ivar)
if options_.nomoments == 0
z = [ sqrt(diagCovYR0(ivar)) diagCovYR0(ivar) ];
- title='MOMENTS OF SIMULATED VARIABLES';
+ title='THEORETICAL MOMENTS';
headers=strvcat('VARIABLE','STD. DEV.','VARIANCE');
dyntable(title,headers,labels,z,size(labels,2)+2,16,10);
end
@@ -164,7 +156,7 @@ function AutoCOR_YRk=PCL_Part_info_irmoments( H, varobs, dr,ivar)
diagSqrtCovYR0=sqrt(diagCovYR0);
DELTA=inv(diag(diagSqrtCovYR0));
COR_Y= DELTA*COV_YR0*DELTA;
- title = 'CORRELATION OF SIMULATED VARIABLES';
+ title = 'MATRIX OF CORRELATION';
headers = strvcat('VARIABLE',M_.endo_names(ivar,:));
dyntable(title,headers,labels,COR_Y(ivar,ivar),size(labels,2)+2,8,4);
else
@@ -185,7 +177,7 @@ function AutoCOR_YRk=PCL_Part_info_irmoments( H, varobs, dr,ivar)
oo_.autocorr{k}=AutoCOR_YRkMAT(ivar,ivar);
AutoCOR_YRk(:,k)= diag(COV_YRk)./diagCovYR0;
end
- title = 'AUTOCORRELATION OF SIMULATED VARIABLES';
+ title = 'COEFFICIENTS OF AUTOCORRELATION';
headers = strvcat('VARIABLE',int2str([1:ar]'));
dyntable(title,headers,labels,AutoCOR_YRk(ivar,:),size(labels,2)+2,8,4);
else
diff --git a/matlab/stoch_simul.m b/matlab/stoch_simul.m
index 63a47e10aab17a5f3a0f49c976ea13bed585c4d4..333230549e243b1fa66e05dbd0b6a38fb6d115da 100644
--- a/matlab/stoch_simul.m
+++ b/matlab/stoch_simul.m
@@ -1,6 +1,6 @@
function info=stoch_simul(var_list)
-% Copyright (C) 2001-2009 Dynare Team
+% Copyright (C) 2001-2010 Dynare Team
%
% This file is part of Dynare.
%
@@ -80,14 +80,14 @@ if ~options_.noprint
dyntable(my_title,headers,labels,M_.Sigma_e,lh,10,6);
if options_.partial_information
disp(' ')
- disp(' SOLUTION UNDER PARTIAL INFORMATION')
+ disp('SOLUTION UNDER PARTIAL INFORMATION')
disp(' ')
if isfield(options_,'varobs')&& ~isempty(options_.varobs)
PCL_varobs=options_.varobs;
- disp(' OBSERVED VARIABLES')
+ disp('OBSERVED VARIABLES')
else
- PCL_varobs=var_list;
+ PCL_varobs=M_.endo_names;
disp(' VAROBS LIST NOT SPECIFIED')
disp(' ASSUMED OBSERVED VARIABLES')
end
@@ -304,3 +304,5 @@ end
options_ = options_old;
+% temporary fix waiting for local options
+options_.partial_information = 0;
\ No newline at end of file