51 lines
1.6 KiB
Matlab
51 lines
1.6 KiB
Matlab
function [nonsing,b] = SPReduced_form(q,qrows,qcols,bcols,neq,condn)
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% [nonsing,b] = SPReduced_form(q,qrows,qcols,bcols,neq,b,condn);
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%
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% Compute reduced-form coefficient matrix, b.
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% Original author: Gary Anderson
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% Original file downloaded from:
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% http://www.federalreserve.gov/Pubs/oss/oss4/code.html
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% Adapted for Dynare by Dynare Team.
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%
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% This code is in the public domain and may be used freely.
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% However the authors would appreciate acknowledgement of the source by
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% citation of any of the following papers:
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%
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% Anderson, G. and Moore, G.
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% "A Linear Algebraic Procedure for Solving Linear Perfect Foresight
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% Models."
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% Economics Letters, 17, 1985.
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%
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% Anderson, G.
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% "Solving Linear Rational Expectations Models: A Horse Race"
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% Computational Economics, 2008, vol. 31, issue 2, pages 95-113
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%
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% Anderson, G.
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% "A Reliable and Computationally Efficient Algorithm for Imposing the
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% Saddle Point Property in Dynamic Models"
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% Journal of Economic Dynamics and Control, 2010, vol. 34, issue 3,
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% pages 472-489
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b=[];
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%qs=SPSparse(q);
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qs=sparse(q);
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left = 1:qcols-qrows;
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right = qcols-qrows+1:qcols;
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nonsing = rcond(full(qs(:,right))) > condn;
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if(nonsing)
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qs(:,left) = -qs(:,right)\qs(:,left);
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b = qs(1:neq,1:bcols);
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b = full(b);
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else %rescale by dividing row by maximal qr element
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%'inverse condition number small, rescaling '
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themax=max(abs(qs(:,right)),[],2);
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oneover = diag(1 ./ themax);
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nonsing = rcond(full(oneover *qs(:,right))) > condn;
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if(nonsing)
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qs(:,left) = -(oneover*qs(:,right))\(oneover*(qs(:,left)));
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b = qs(1:neq,1:bcols);
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b = full(b);
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end
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end
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