File: rlrprior.m

package info (click to toggle)
dynare 4.5.7-1
  • links: PTS, VCS
  • area: main
  • in suites: buster
  • size: 49,408 kB
  • sloc: cpp: 84,998; ansic: 29,058; pascal: 13,843; sh: 4,833; objc: 4,236; yacc: 3,622; makefile: 2,278; lex: 1,541; python: 236; lisp: 69; xml: 8
file content (55 lines) | stat: -rw-r--r-- 3,054 bytes parent folder | download | duplicates (8)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
function [Ptld,H0invtld,Hpinvtld] = rlrprior(Ui,Vi,Pi,H0multi,Hpmulti,nvar)
% [Ptld,H0invtld,Hpinvtld] = rlrprior(Ui,Vi,Pi,H0multi,Hpmulti,nvar)
%
%    Exporting random Bayesian prior with linear restrictions
%    See Waggoner and Zha's Gibbs sampling paper
%
% Ui: nvar-by-1 cell.  In each cell, nvar-by-qi orthonormal basis for the null of the ith
%           equation contemporaneous restriction matrix where qi is the number of free parameters.
%           With this transformation, we have ai = Ui*bi or Ui'*ai = bi where ai is a vector
%           of total original parameters and bi is a vector of free parameters. When no
%           restrictions are imposed, we have Ui = I.  There must be at least one free
%           parameter left for the ith equation.  Imported from dnrprior.m.
% Vi: nvar-by-1 cell.  In each cell, k-by-ri orthonormal basis for the null of the ith
%           equation lagged restriction matrix where k (ncoef) is a total number of RHS variables and
%           ri is the number of free parameters. With this transformation, we have fi = Vi*gi
%           or Vi'*fi = gi where fi is a vector of total original parameters and gi is a
%           vector of free parameters. There must be at least one free parameter left for
%           the ith equation.  Imported from dnrprior.m.
% Pi: ncoef-by-nvar matrix for the ith equation under random walk.  Same for all equations
% H0multi: nvar-by-nvar-by-nvar; H0 for different equations under asymmetric prior
% Hpmulti: ncoef-by-ncoef-by-nvar; H+ for different equations under asymmetric prior
% nvar:  number of endogenous variables
% --------------------
% Ptld: cell(nvar,1), linear transformation for random walk prior for the ith equation
% H0invtld: cell(nvar,1), transformed inv covaraince for free parameters in A0(:,i).
% Hpinvtld: cell(nvar,1), transformed inv covaraince for free parameters in A+(:,i);
%
% Tao Zha, February 2000
%
% Copyright (C) 1997-2012 Tao Zha
%
% This 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.
%
% It 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.
%
% If you did not received a copy of the GNU General Public License
% with this software, see <http://www.gnu.org/licenses/>.
%

Ptld = cell(nvar,1); % tld: tilda
H0invtld = cell(nvar,1);  % H0 for different equations under linear restrictions
Hpinvtld = cell(nvar,1);  % H+ for different equations under linear restrictions

for n=1:nvar       % one for each equation
   Hpinvtld{n} = Vi{n}'*(Hpmulti(:,:,n)\Vi{n});
   Ptld{n} = (Hpinvtld{n}\Vi{n}')*(Hpmulti(:,:,n)\Pi)*Ui{n};
   H0invtld{n} = Ui{n}'*(H0multi(:,:,n)\Ui{n}) + Ui{n}'*Pi'*(Hpmulti(:,:,n)\Pi)*Ui{n} ...
                      - Ptld{n}'*Hpinvtld{n}*Ptld{n};
end