47 lines
1.4 KiB
Modula-2
47 lines
1.4 KiB
Modula-2
// --+ options: stochastic,json=compute +--
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var foo z x y;
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varexo e_x e_y e_z;
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parameters a b c d e f beta ;
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a = .9;
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b = -.2;
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c = .3;
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f = .8;
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d = .5;
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e = .4;
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beta = 1/(1+.02);
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// Define a VAR model from a subset of equations in the model block.
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var_model(structural, model_name = toto, eqtags = [ 'X' 'Y' 'Z' ]);
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// Define a VAR_EXPECTATION_MODEL
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var_expectation_model(model_name = varexp, expression = diff(log(x)), auxiliary_model_name = toto, horizon = 1, discount = beta) ;
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model;
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[ name = 'X' ]
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diff(log(x)) = b*diff(z) + a*diff(log(x(-1))) + (1-a)*diff(log(x(-2))) + c*diff(z(-2)) + e_x;
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[ name = 'Z' ]
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diff(z) = f*(diff(z(-1))-diff(log(x)))+c*diff(z(-2)) + e_z;
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[ name = 'Y' ]
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log(y) = diff(log(x)) + d*log(y(-2)) + e*diff(z(-1)) + e_y;
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foo = var_expectation(varexp);
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end;
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[ar, a0] = example1.varmatrices('toto', M_.params);
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assert(isequal(diag(a0), ones(3,1)), 'Diagonal of a0 is wrong.')
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assert(a0(1,3)==-b, 'Element (1,3) in A0 is wrong.')
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assert(a0(1,2)==0, 'Element (1,2) in A0 is wrong.')
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assert(a0(2,1)==-1, 'Element (2,1) in A0 is wrong.')
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assert(a0(2,3)==0, 'Element (2,3) in A0 is wrong.')
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assert(a0(3,1)==f, 'Element (3,1) in A0 is wrong.')
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assert(a0(3,2)==0, 'Element (3,1) in A0 is wrong.')
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assert(isequal(ar(:,:,1), [a 0 0; 0 0 e; 0 0 f]), 'First autoregressive matrix is wrong');
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assert(isequal(ar(:,:,2), [1-a 0 c; 0 d 0; 0 0 c]), 'Second autoregressive matrix is wrong');
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