Add unit tests for perfect foresight simulations with exogenous leads and lags
Closes #1616time-shift
parent
856fc060a2
commit
db0cf1b8ea
|
@ -280,6 +280,8 @@ MODFILES = \
|
|||
deterministic_simulations/multiple_lead_lags/ramst_augmented_histval.mod \
|
||||
deterministic_simulations/rbc_det.mod \
|
||||
deterministic_simulations/rbc_det_stack_solve_algo_7.mod \
|
||||
deterministic_simulations/rbc_det_stack_solve_algo_7_exo_lag.mod \
|
||||
deterministic_simulations/rbc_det_stack_solve_algo_7_exo_lead.mod \
|
||||
lmmcp/rbc.mod \
|
||||
lmmcp/sw_lmmcp.mod \
|
||||
lmmcp/sw_newton.mod \
|
||||
|
|
|
@ -17,7 +17,7 @@ sigma2 = 0;
|
|||
model;
|
||||
|
||||
// Eq. n°1:
|
||||
efficiency = rho*efficiency(-1) + EfficiencyInnovation(-2); // Use a lag of two to test the maximum_lag logic
|
||||
efficiency = rho*efficiency(-1) + EfficiencyInnovation;
|
||||
|
||||
// Eq. n°2:
|
||||
Efficiency = effstar*exp(efficiency);
|
||||
|
|
|
@ -0,0 +1,116 @@
|
|||
var Capital, Output, Labour, Consumption, Efficiency, efficiency, ExpectedTerm;
|
||||
|
||||
varexo EfficiencyInnovation;
|
||||
|
||||
parameters beta, theta, tau, alpha, psi, delta, rho, effstar, sigma2;
|
||||
|
||||
beta = 0.9900;
|
||||
theta = 0.3570;
|
||||
tau = 2.0000;
|
||||
alpha = 0.4500;
|
||||
psi = -0.1000;
|
||||
delta = 0.0200;
|
||||
rho = 0.8000;
|
||||
effstar = 1.0000;
|
||||
sigma2 = 0;
|
||||
|
||||
model;
|
||||
|
||||
// Eq. n°1:
|
||||
efficiency = rho*efficiency(-1) + EfficiencyInnovation(-2); // Use a lag of two to test the maximum_lag logic
|
||||
|
||||
// Eq. n°2:
|
||||
Efficiency = effstar*exp(efficiency);
|
||||
|
||||
// Eq. n°3:
|
||||
Output = Efficiency*(alpha*(Capital(-1)^psi)+(1-alpha)*(Labour^psi))^(1/psi);
|
||||
|
||||
// Eq. n°4:
|
||||
Capital = Output-Consumption + (1-delta)*Capital(-1);
|
||||
|
||||
// Eq. n°5:
|
||||
((1-theta)/theta)*(Consumption/(1-Labour)) - (1-alpha)*(Output/Labour)^(1-psi);
|
||||
|
||||
// Eq. n°6:
|
||||
(((Consumption^theta)*((1-Labour)^(1-theta)))^(1-tau))/Consumption = ExpectedTerm(1);
|
||||
|
||||
// Eq. n°7:
|
||||
ExpectedTerm = beta*((((Consumption^theta)*((1-Labour)^(1-theta)))^(1-tau))/Consumption)*(alpha*((Output/Capital(-1))^(1-psi))+(1-delta));
|
||||
|
||||
end;
|
||||
|
||||
steady_state_model;
|
||||
efficiency = EfficiencyInnovation/(1-rho);
|
||||
Efficiency = effstar*exp(efficiency);
|
||||
Output_per_unit_of_Capital=((1/beta-1+delta)/alpha)^(1/(1-psi));
|
||||
Consumption_per_unit_of_Capital=Output_per_unit_of_Capital-delta;
|
||||
Labour_per_unit_of_Capital=(((Output_per_unit_of_Capital/Efficiency)^psi-alpha)/(1-alpha))^(1/psi);
|
||||
Output_per_unit_of_Labour=Output_per_unit_of_Capital/Labour_per_unit_of_Capital;
|
||||
Consumption_per_unit_of_Labour=Consumption_per_unit_of_Capital/Labour_per_unit_of_Capital;
|
||||
|
||||
% Compute steady state share of capital.
|
||||
ShareOfCapital=alpha/(alpha+(1-alpha)*Labour_per_unit_of_Capital^psi);
|
||||
|
||||
% Compute steady state of the endogenous variables.
|
||||
Labour=1/(1+Consumption_per_unit_of_Labour/((1-alpha)*theta/(1-theta)*Output_per_unit_of_Labour^(1-psi)));
|
||||
Consumption=Consumption_per_unit_of_Labour*Labour;
|
||||
Capital=Labour/Labour_per_unit_of_Capital;
|
||||
Output=Output_per_unit_of_Capital*Capital;
|
||||
ExpectedTerm=beta*((((Consumption^theta)*((1-Labour)^(1-theta)))^(1-tau))/Consumption)
|
||||
*(alpha*((Output/Capital)^(1-psi))+1-delta);
|
||||
end;
|
||||
|
||||
steady;
|
||||
|
||||
ik = varlist_indices('Capital',M_.endo_names);
|
||||
CapitalSS = oo_.steady_state(ik);
|
||||
|
||||
histval;
|
||||
Capital(0) = CapitalSS/2;
|
||||
end;
|
||||
|
||||
|
||||
perfect_foresight_setup(periods=200);
|
||||
|
||||
perfect_foresight_solver(stack_solve_algo=7,solve_algo=1);
|
||||
|
||||
if ~oo_.deterministic_simulation.status
|
||||
error('Perfect foresight simulation failed')
|
||||
end
|
||||
|
||||
rplot Consumption;
|
||||
rplot Capital;
|
||||
|
||||
D = load('rbc_det_results');
|
||||
|
||||
if norm(D.oo_.endo_simul(:,D.M_.maximum_lag+1:end-D.M_.maximum_lead) - oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead)) > 1e-30;
|
||||
disp(D.oo_.endo_simul(:,D.M_.maximum_lag+1:end-D.M_.maximum_lead) - oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead));
|
||||
error('rbc_det_stack_solve_algo_7 failed');
|
||||
end;
|
||||
|
||||
options_.dynatol.f=1e-10;
|
||||
@#define J = [0,1,2,3,4,9,10]
|
||||
@#for solve_algo_iter in J
|
||||
|
||||
perfect_foresight_setup(periods=200);
|
||||
perfect_foresight_solver(stack_solve_algo=7,solve_algo=@{solve_algo_iter});
|
||||
|
||||
if ~oo_.deterministic_simulation.status
|
||||
error('Perfect foresight simulation failed')
|
||||
end
|
||||
|
||||
rplot Consumption;
|
||||
rplot Capital;
|
||||
|
||||
D = load('rbc_det_results');
|
||||
if isoctave && options_.solve_algo==0
|
||||
%%acount for somehow weaker convergence criterion in Octave's fsolve
|
||||
tol_crit=1e-4;
|
||||
else
|
||||
tol_crit=1e-8;
|
||||
end
|
||||
if norm(D.oo_.endo_simul(:,D.M_.maximum_lag+1:end-D.M_.maximum_lead) - oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead)) > tol_crit;
|
||||
disp(D.oo_.endo_simul(:,D.M_.maximum_lag+1:end-D.M_.maximum_lead) - oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead));
|
||||
error(sprintf('rbc_det_stack_solve_algo_7 failed with solve_algo=%u',options_.solve_algo));
|
||||
end;
|
||||
@#endfor
|
|
@ -0,0 +1,116 @@
|
|||
var Capital, Output, Labour, Consumption, Efficiency, efficiency, ExpectedTerm;
|
||||
|
||||
varexo EfficiencyInnovation;
|
||||
|
||||
parameters beta, theta, tau, alpha, psi, delta, rho, effstar, sigma2;
|
||||
|
||||
beta = 0.9900;
|
||||
theta = 0.3570;
|
||||
tau = 2.0000;
|
||||
alpha = 0.4500;
|
||||
psi = -0.1000;
|
||||
delta = 0.0200;
|
||||
rho = 0.8000;
|
||||
effstar = 1.0000;
|
||||
sigma2 = 0;
|
||||
|
||||
model;
|
||||
|
||||
// Eq. n°1:
|
||||
efficiency = rho*efficiency(-1) + EfficiencyInnovation(+2); // Use a lead of two to test the maximum_lag logic
|
||||
|
||||
// Eq. n°2:
|
||||
Efficiency = effstar*exp(efficiency);
|
||||
|
||||
// Eq. n°3:
|
||||
Output = Efficiency*(alpha*(Capital(-1)^psi)+(1-alpha)*(Labour^psi))^(1/psi);
|
||||
|
||||
// Eq. n°4:
|
||||
Capital = Output-Consumption + (1-delta)*Capital(-1);
|
||||
|
||||
// Eq. n°5:
|
||||
((1-theta)/theta)*(Consumption/(1-Labour)) - (1-alpha)*(Output/Labour)^(1-psi);
|
||||
|
||||
// Eq. n°6:
|
||||
(((Consumption^theta)*((1-Labour)^(1-theta)))^(1-tau))/Consumption = ExpectedTerm(1);
|
||||
|
||||
// Eq. n°7:
|
||||
ExpectedTerm = beta*((((Consumption^theta)*((1-Labour)^(1-theta)))^(1-tau))/Consumption)*(alpha*((Output/Capital(-1))^(1-psi))+(1-delta));
|
||||
|
||||
end;
|
||||
|
||||
steady_state_model;
|
||||
efficiency = EfficiencyInnovation/(1-rho);
|
||||
Efficiency = effstar*exp(efficiency);
|
||||
Output_per_unit_of_Capital=((1/beta-1+delta)/alpha)^(1/(1-psi));
|
||||
Consumption_per_unit_of_Capital=Output_per_unit_of_Capital-delta;
|
||||
Labour_per_unit_of_Capital=(((Output_per_unit_of_Capital/Efficiency)^psi-alpha)/(1-alpha))^(1/psi);
|
||||
Output_per_unit_of_Labour=Output_per_unit_of_Capital/Labour_per_unit_of_Capital;
|
||||
Consumption_per_unit_of_Labour=Consumption_per_unit_of_Capital/Labour_per_unit_of_Capital;
|
||||
|
||||
% Compute steady state share of capital.
|
||||
ShareOfCapital=alpha/(alpha+(1-alpha)*Labour_per_unit_of_Capital^psi);
|
||||
|
||||
% Compute steady state of the endogenous variables.
|
||||
Labour=1/(1+Consumption_per_unit_of_Labour/((1-alpha)*theta/(1-theta)*Output_per_unit_of_Labour^(1-psi)));
|
||||
Consumption=Consumption_per_unit_of_Labour*Labour;
|
||||
Capital=Labour/Labour_per_unit_of_Capital;
|
||||
Output=Output_per_unit_of_Capital*Capital;
|
||||
ExpectedTerm=beta*((((Consumption^theta)*((1-Labour)^(1-theta)))^(1-tau))/Consumption)
|
||||
*(alpha*((Output/Capital)^(1-psi))+1-delta);
|
||||
end;
|
||||
|
||||
steady;
|
||||
|
||||
ik = varlist_indices('Capital',M_.endo_names);
|
||||
CapitalSS = oo_.steady_state(ik);
|
||||
|
||||
histval;
|
||||
Capital(0) = CapitalSS/2;
|
||||
end;
|
||||
|
||||
|
||||
perfect_foresight_setup(periods=200);
|
||||
|
||||
perfect_foresight_solver(stack_solve_algo=7,solve_algo=1);
|
||||
|
||||
if ~oo_.deterministic_simulation.status
|
||||
error('Perfect foresight simulation failed')
|
||||
end
|
||||
|
||||
rplot Consumption;
|
||||
rplot Capital;
|
||||
|
||||
D = load('rbc_det_results');
|
||||
|
||||
if norm(D.oo_.endo_simul(:,D.M_.maximum_lag+1:end-D.M_.maximum_lead) - oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead)) > 1e-30;
|
||||
disp(D.oo_.endo_simul(:,D.M_.maximum_lag+1:end-D.M_.maximum_lead) - oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead));
|
||||
error('rbc_det_stack_solve_algo_7 failed');
|
||||
end;
|
||||
|
||||
options_.dynatol.f=1e-10;
|
||||
@#define J = [0,1,2,3,4,9,10]
|
||||
@#for solve_algo_iter in J
|
||||
|
||||
perfect_foresight_setup(periods=200);
|
||||
perfect_foresight_solver(stack_solve_algo=7,solve_algo=@{solve_algo_iter});
|
||||
|
||||
if ~oo_.deterministic_simulation.status
|
||||
error('Perfect foresight simulation failed')
|
||||
end
|
||||
|
||||
rplot Consumption;
|
||||
rplot Capital;
|
||||
|
||||
D = load('rbc_det_results');
|
||||
if isoctave && options_.solve_algo==0
|
||||
%%acount for somehow weaker convergence criterion in Octave's fsolve
|
||||
tol_crit=1e-4;
|
||||
else
|
||||
tol_crit=1e-8;
|
||||
end
|
||||
if norm(D.oo_.endo_simul(:,D.M_.maximum_lag+1:end-D.M_.maximum_lead) - oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead)) > tol_crit;
|
||||
disp(D.oo_.endo_simul(:,D.M_.maximum_lag+1:end-D.M_.maximum_lead) - oo_.endo_simul(:,M_.maximum_lag+1:end-M_.maximum_lead));
|
||||
error(sprintf('rbc_det_stack_solve_algo_7 failed with solve_algo=%u',options_.solve_algo));
|
||||
end;
|
||||
@#endfor
|
Loading…
Reference in New Issue