113 lines
2.8 KiB
Matlab
113 lines
2.8 KiB
Matlab
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function y = var_forecast(M_, options_, name, h, y, fcv)
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% name : filename
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% M_
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% options_
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% name string name of var model, provided in var statement
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% h int number of steps-ahead forecast
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% y matrix rows: realizations of endogenous variables in declaration order; cols: realizations in t, t-1, t-2 ... order of VAR
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% fcv string name of variable we want forecast for
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% returns the h-step-ahead VAR(order) forecast for fcv
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% example calling:
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% In Matlab:
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% >> coefficients{1} = [0.5000 0.1000; 0.4000 0.5000];
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% >> coefficients{2} = [0 0 ; 0.2500 0 ];
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% >> mu = [0.0200; 0.0300];
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% >> save('m1.mat', 'mu','coefficients');
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% In .mod file:
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% var a b c d;
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% ...
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% var(model_name=m1,order=2) a c;
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% From Matlab backend:
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% >> yt = [0.0600; 33.0000; 0.0300; 22.0000];
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% >> ytm1 = [0.0550; 11.0000; 0.0300; 88.0000];
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% >> var_forecast(M_, options_, 'm1', 1, [yt ytm1])
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% >> var_forecast(M_, options_, 'm1', 2, [yt ytm1], ['a'])
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%% Find var in options_
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order = '';
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var_list = '';
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for i=1:length(options_.var)
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if strcmp(options_.var(i).name, name)
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order = options_.var(i).order;
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var_list = options_.var(i).var_list_;
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break;
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end
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end
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if isempty(order)
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error([name ' not found in var specification declared in .mod file']);
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end
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%% construct y
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assert(length(y) == length(M_.endo_names));
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endo_names = cellstr(M_.endo_names);
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yidx = zeros(size(endo_names));
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for i=1:length(var_list)
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yidx = yidx | strcmp(strtrim(var_list(i,:)), endo_names);
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end
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y = y(yidx,:);
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if nargin == 6
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fvidx = strcmp(fcv, endo_names);
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end
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%% load .mat file and rewrite as VAR(1)
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load(name, 'coefficients', 'mu');
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if ~exist('coefficients', 'var') || ~exist('mu', 'var')
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error([name ' : must contain the variables coefficients and mu']);
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end
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assert(h >= 1);
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lm = length(mu);
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lc = length(coefficients);
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assert(lc == order);
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if size(y,1) ~= lm || size(y,2) ~= order
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error('The dimensions of y are not correct. It should be an nvars x order matrix');
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end
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A = zeros(lm*lc, lm*lc);
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for i=1:lc
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if any([lm lm] ~= size(coefficients{i}))
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error('The dimensions of mu and coefficients are off');
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end
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col = lm*(i-1)+1:lm*i;
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A(1:lm, col) = coefficients{i};
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if i ~= lc
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A(lm*i+1:lm*i+lm, col) = eye(lm, lm);
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end
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end
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mu = [mu; zeros(lm,1)];
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%% Calculate Forecast
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% New Introduction to Multiple Time Series Analysis
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% Helmut Lutkepohl
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% page 34
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%
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% An = eye(size(A));
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% for i=1:h-1
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% An = An + A^i;
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% end
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% y = An*mu + A^h*y(:);
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for i=1:h
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y = mu + A*y(:);
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end
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y = y(1:lm);
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if nargin == 6
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retidx = find(fvidx & yidx == 1);
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if isempty(retidx)
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return;
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elseif retidx == 1
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y = y(1);
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else
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y = y(sum(yidx(1:retidx-1))+1);
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end
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end
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end
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