110 lines
3.6 KiB
Modula-2
110 lines
3.6 KiB
Modula-2
// Example of optimal simple rule using opt_algo=2
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var y inflation r dummy_var;
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varexo y_ inf_;
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parameters delta sigma alpha kappa gammax0 gammac0 gamma_y_ gamma_inf_;
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delta = 0.44;
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kappa = 0.18;
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alpha = 0.48;
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sigma = -0.06;
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model(linear);
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y = delta * y(-1) + (1-delta)*y(+1)+sigma *(r - inflation(+1)) + y_;
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inflation = alpha * inflation(-1) + (1-alpha) * inflation(+1) + kappa*y + inf_;
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dummy_var=0.9*dummy_var(-1)+0.01*y;
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r = gammax0*y(-1)+gammac0*inflation(-1)+gamma_y_*y_+gamma_inf_*inf_;
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end;
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shocks;
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var y_;
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stderr 0.63;
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var inf_;
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stderr 0.4;
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end;
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options_.nograph=1;
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options_.nocorr=1;
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osr_params gammax0 gammac0 gamma_y_ gamma_inf_;
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optim_weights;
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inflation 1;
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y 1;
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dummy_var 1;
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end;
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gammax0 = 0.2;
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gammac0 = 1.5;
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gamma_y_ = 8;
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gamma_inf_ = 3;
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osr(opt_algo=8);
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%compute objective function manually
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objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'));
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if abs(oo_.osr.objective_function-objective)>1e-8
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error('Objective Function is wrong')
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end
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%redo computation with covariance specified
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optim_weights;
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inflation 1;
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y 1;
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dummy_var 1;
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y,inflation 0.5;
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end;
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osr;
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%compute objective function manually
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objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
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if abs(oo_.osr.objective_function-objective)>1e-8
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error('Objective Function is wrong')
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end
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gammax0=1.35533;
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gammac0=1.39664;
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gamma_y_=16.6667;
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gamma_inf_=9.13199;
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%redo computation with double weight on one covariance
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optim_weights;
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inflation 1;
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y 1;
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dummy_var 1;
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y,inflation 1;
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end;
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osr;
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%compute objective function manually
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objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+1*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
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if abs(oo_.osr.objective_function-objective)>1e-8
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error('Objective Function is wrong')
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end
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oo_covar_single=oo_;
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%redo computation with single weight on both covariances
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optim_weights;
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inflation 1;
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y 1;
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dummy_var 1;
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y,inflation 0.5;
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inflation,y 0.5;
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end;
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osr;
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%compute objective function manually
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objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'));
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if abs(oo_.osr.objective_function-objective)>1e-8
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error('Objective Function is wrong')
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end
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if abs(oo_.osr.objective_function-oo_covar_single.osr.objective_function)>1e-8
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error('Objective Function is wrong')
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end
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if max(abs((cell2mat(struct2cell(oo_.osr.optim_params))-cell2mat(struct2cell(oo_covar_single.osr.optim_params)))./cell2mat(struct2cell(oo_.osr.optim_params))))>1e-4
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error('Parameters should be identical')
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end
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