// --+ options: json=compute, stochastic +-- var x1 x2 x1bar x2bar z y x u v s; varexo ex1 ex2 ex1bar (used='estimationonly') ex2bar (used='estimationonly') ez ey ex eu ev es; parameters rho_1 rho_2 rho_3 rho_4 a_x1_0 a_x1_1 a_x1_2 a_x1_x2_1 a_x1_x2_2 a_x2_0 a_x2_1 a_x2_2 a_x2_x1_1 a_x2_x1_2 e_c_m c_z_1 c_z_2 c_z_dx2 c_z_u c_z_dv c_z_s cx cy beta lambda; rho_1 = .9; rho_2 = -.2; rho_3 = .4; rho_4 = -.3; a_x1_0 = -.9; a_x1_1 = .4; a_x1_2 = .3; a_x1_x2_1 = .1; a_x1_x2_2 = .2; a_x2_0 = -.9; a_x2_1 = .2; a_x2_2 = -.1; a_x2_x1_1 = -.1; a_x2_x1_2 = .2; beta = .2; e_c_m = .5; c_z_1 = .2; c_z_2 = -.1; c_z_dx2 = .3; c_z_u = .3; c_z_dv = .4; c_z_s = -.2; cx = 1.0; cy = 1.0; lambda = 0.5; // Share of optimizing agents. trend_component_model(model_name=toto, eqtags=['eq:x1', 'eq:x2', 'eq:x1bar', 'eq:x2bar'], targets=['eq:x1bar', 'eq:x2bar']); pac_model(auxiliary_model_name=toto, discount=beta, model_name=pacman); model; [name='eq:u'] s = .3*s(-1) - .1*s(-2) + es; [name='eq:diff(v)'] diff(v) = .5*diff(v(-1)) + ev; [name='eq:u'] u = .5*u(-1) - .2*u(-2) + eu; [name='eq:y'] y = rho_1*y(-1) + rho_2*y(-2) + ey; [name='eq:x'] x = rho_3*x(-1) + rho_4*x(-2) + ex; [name='eq:x1'] diff(x1) = a_x1_0*(x1(-1)-x1bar(-1)) + a_x1_1*diff(x1(-1)) + a_x1_2*diff(x1(-2)) + a_x1_x2_1*diff(x2(-1)) + a_x1_x2_2*diff(x2(-2)) + ex1; [name='eq:x2'] diff(x2) = a_x2_0*(x2(-1)-x2bar(-1)) + a_x2_1*diff(x1(-1)) + a_x2_2*diff(x1(-2)) + a_x2_x1_1*diff(x2(-1)) + a_x2_x1_2*diff(x2(-2)) + ex2; [name='eq:x1bar'] x1bar = x1bar(-1) + ex1bar; [name='eq:x2bar'] x2bar = x2bar(-1) + ex2bar; [name='zpac'] diff(z) = lambda*(e_c_m*(x1(-1)-z(-1)) + c_z_1*diff(z(-1)) + c_z_2*diff(z(-2)) + pac_expectation(pacman) + c_z_s*s + c_z_dv*diff(v) ) + (1-lambda)*( cy*y + cx*x) + c_z_u*u + c_z_dx2*diff(x2) + ez; end; shocks; var ex1 = 1.0; var ex2 = 1.0; var ex1bar = 1.0; var ex2bar = 1.0; var ez = 1.0; var ey = 0.1; var ex = 0.1; var eu = 0.05; var ev = 0.05; var es = 0.07; end; // Initialize the PAC model (build the Companion VAR representation for the auxiliary model). pac.initialize('pacman'); // Update the parameters of the PAC expectation model (h0 and h1 vectors). pac.update.expectation('pacman'); // Select a subset of the equations and print the equations, the list of parameters, endogenous // variables and exogenous variables in .inc files under ./simulation-files folder. Note that // innovations ex1bar and ex2bar will not appear in the equations. cherrypick('example', 'simulation-files', {'zpac', 'eq:x1', 'eq:x2', 'eq:x1bar', 'eq:x2bar'}, true);