dynare/matlab/forcst.m

function [yf,int_width]=forcst(dr,y0,horizon,var_list)

% function [yf,int_width]=forecst(dr,y0,horizon,var_list)
%   computes mean forecast for a given value of the parameters
%   computes also confidence band for the forecast    
%
% INPUTS:
%   dr:          structure containing decision rules
%   y0:          initial values
%   horizon:     nbr of periods to forecast
%   var_list:    list of variables (character matrix)
%
% OUTPUTS:
%   yf:          mean forecast
%   int_width:   distance between upper bound and
%                mean forecast
%
% SPECIAL REQUIREMENTS
%    none
%  
% part of DYNARE, copyright Dynare Team (2003-2008)
% Gnu Public License.
    
    global M_  oo_ options_ 
    
    make_ex_;
    yf = simult_(y0,dr,zeros(horizon,M_.exo_nbr),1);
    nstatic = dr.nstatic;
    npred = dr.npred;
    nc = size(dr.ghx,2);
    endo_nbr = M_.endo_nbr;
    inv_order_var = dr.inv_order_var;
    [A,B] = kalman_transition_matrix(dr,nstatic+(1:npred),1:nc,dr.transition_auxiliary_variables,M_.exo_nbr);
    
    nvar = size(var_list,1);
    if nvar == 0
	nvar = M_.endo_nbr;
	ivar = [1:nvar];
    else
	ivar=zeros(nvar,1);
	for i=1:nvar
	    i_tmp = strmatch(var_list(i,:),M_.endo_names,'exact');
	    if isempty(i_tmp)
		disp(var_list(i,:));
		error (['One of the variable specified does not exist']) ;
	    else
		ivar(i) = i_tmp;
	    end
	end
    end

    ghx1 = dr.ghx(inv_order_var(ivar),:);
    ghu1 = dr.ghu(inv_order_var(ivar),:);

    sigma_u = B*M_.Sigma_e*B';
    sigma_u1 = ghu1*M_.Sigma_e*ghu1';
    sigma_y = 0;
    
    for i=1:horizon
	sigma_y1 = ghx1*sigma_y*ghx1'+sigma_u1;
	var_yf(i,:) = diag(sigma_y1)';
	if i == horizon
	    break
	end
	sigma_u = A*sigma_u*A';
	sigma_y = sigma_y+sigma_u;
    end

    fact = qnorm((1-options_.conf_sig)/2,0,1);
    
    int_width = zeros(horizon,M_.endo_nbr);
    for i=1:nvar
	int_width(:,i) = fact*sqrt(var_yf(:,i));
    end

    yf = yf(ivar,:);