33 lines
1.8 KiB
Matlab
33 lines
1.8 KiB
Matlab
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function e = euler_equation_error(y0,x,innovations,M,options,oo,pfm,nodes,weights)
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dynamic_model = str2func([M.fname '_dynamic']);
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ep = options.ep;
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[y1, info_convergence, endogenousvariablespaths] = extended_path_core(ep.periods, ...
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M.endo_nbr, M.exo_nbr, ...
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innovations.positive_var_indx, ...
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x, ep.init, y0, oo.steady_state, ...
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0, ep.use_bytecode, ...
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ep.stochastic.order, M, ...
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pfm, ep.stochastic.algo, ...
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ep.solve_algo, ...
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ep.stack_solve_algo, ...
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options.lmmcp, options, oo, ...
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[]);
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i_pred = find(M.lead_lag_incidence(1,:));
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i_fwrd = find(M.lead_lag_incidence(3,:));
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x1 = [x(2:end,:); zeros(1,M.exo_nbr)];
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for i=1:length(nodes)
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x2 = x1;
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x2(2,:) = x2(2,:) + nodes(i,:);
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[y2, info_convergence, endogenousvariablespaths] = ...
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extended_path_core(ep.periods, M.endo_nbr, M.exo_nbr, ...
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innovations.positive_var_indx, x2, ep.init, ...
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y1, oo.steady_state, 0, ep.use_bytecode, ...
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ep.stochastic.order, M, pfm, ep.stochastic.algo, ...
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ep.solve_algo, ep.stack_solve_algo, options.lmmcp, ...
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options, oo, []);
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z = [y0(i_pred); y1; y2(i_fwrd)];
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res(:,i) = dynamic_model(z,x,M.params,oo.steady_state,2);
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end
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e = res*weights;
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