// --+ options: json=compute, stochastic +-- var y x z v; varexo ex ey ez ; parameters a_y_1 a_y_2 b_y_1 b_y_2 b_x_1 b_x_2 d_y; // VAR parameters parameters beta e_c_m c_z_1 c_z_2; // PAC equation parameters a_y_1 = .2; a_y_2 = .3; b_y_1 = .1; b_y_2 = .4; b_x_1 = -.1; b_x_2 = -.2; d_y = .5; beta = .9; e_c_m = .1; c_z_1 = .7; c_z_2 = -.3; @#include "example1/model/pac-expectations/pacman-parameters.inc" model; [name='eq:y'] y = a_y_1*y(-1) + a_y_2*diff(x(-1)) + b_y_1*y(-2) + b_y_2*diff(x(-2)) + ey ; [name='eq:x'] diff(x) = b_x_1*y(-2) + b_x_2*diff(x(-1)) + ex ; [name='eq:v'] v = x + d_y*y ; [name='eq:pac'] diff(z) = e_c_m*(x(-1)-z(-1)) + c_z_1*diff(z(-1)) + c_z_2*diff(z(-2)) + @#include "example1/model/pac-expectations/pacman-expression.inc" + @#include "example1/model/pac-expectations/pacman-growth-neutrality-correction.inc" + ez; end; shocks; var ex = 1.0; var ey = 1.0; var ez = 1.0; end; // Set initial conditions to zero. Please use more sensible values if any... initialconditions = dseries(zeros(10, M_.endo_nbr+M_.exo_nbr), 2000Q1, vertcat(M_.endo_names,M_.exo_names)); // Simulate the model for 20 periods set_dynare_seed('default'); TrueData = simul_backward_model(initialconditions, 20); verbatim; set_dynare_seed('default'); y = zeros(M_.endo_nbr,1); y(1:M_.orig_endo_nbr) = rand(M_.orig_endo_nbr, 1); x = randn(M_.exo_nbr,1); y = substitution.set_auxiliary_variables(y, x, M_.params); y = [y(find(M_.lead_lag_incidence(1,:))); y]; example1 = load('example1.mat'); [residual, g1] = substitution.dynamic(y, x', M_.params, oo_.steady_state, 1); if max(abs(example1.TrueData.data(:)-TrueData.data(:)))>1e-9 error('Simulations do not match.') end if ~isequal(length(residual), length(example1.residual)) || max(abs(example1.residual-residual))>1e-8 warning('Residuals do not match!') end if ~isequal(length(g1(:)), length(example1.g1(:))) || max(abs(example1.g1(:)-g1(:)))>1e-8 warning('Jacobian matrices do not match!') end end;