Spurious convergence and Maxit reached

Perfect foresight simulations
1

Why the code results in Spurious convergence? Please Help!

var
c l k w r iv y
;

parameters

ALPHA
BETA
DELTA
b
rho
;

% parameters caliberation

ALPHA = 0.35;
BETA = 0.99;
DELTA = 0.025;
b = 2;
rho = -2;

model;
c (+1)/c= BETA * (1+ r (+1) - DELTA (+1));

1-l/c = b/w;

r = (1 - ALPHA) * k ^ (rho -1) * (ALPHA * l ^ rho + (1- ALPHA) * k ^ rho) * 1/rho -1;

w = ALPHA * l ^ (rho - 1) * (ALPHA * l ^ rho + (1- ALPHA) * k ^ rho) * 1/rho -1;

c = y - iv;

iv = (k (+1) - (1-DELTA) * k);

y = (ALPHA * l ^ rho + (1- ALPHA) * k ^ rho) * 1/rho;

end;

% computation
initval;

c = 0.3;
l = 0.2;
k = 4;
w = 1;
r = 1/BETA-1;
iv = 1;
y = 1;

end;

perfect_foresight_setup (periods = 10);
perfect_foresight_solver;

rplot c;
2

Fix your model. Why is it purely forward-looking? Shouldn’t you have

predetermined_variables k;

? Also, you don’t have a proper terminal condition.

3

After doing this still the shows spurious convergence. Please help!

var
c l k w r iv y
;

parameters

ALPHA
BETA
DELTA
b
rho
;

% parameters caliberation

ALPHA = 0.35;
BETA = 0.99;
DELTA = 0.025;
b = 2;
rho = -2;

model;
c (+1)/c= BETA * (1+ r (+1) - DELTA (+1));

1-l/c = b/w;

r = (1 - ALPHA) * k ^ (rho -1) * (ALPHA * l ^ rho + (1- ALPHA) * k ^ rho) * 1/rho -1;

w = ALPHA * l ^ (rho - 1) * (ALPHA * l ^ rho + (1- ALPHA) * k ^ rho) * 1/rho -1;

c = y - iv;

k (+1) = iv + (1-DELTA) * k;

y = (ALPHA * l ^ rho + (1- ALPHA) * k ^ rho) * 1/rho;

end;

% computation
initval;

c = 0.3;
l = 0.2;
k = 4;
w = 1;
r = 1/BETA-1;
iv = 1;
y = 1;

end;

endval;

c = 0.5;
l = 0.4;
k = 10;
w = 2;
r = 1/BETA-1;
iv = 2;
y = 2;

end;
perfect_foresight_setup (periods = 10);
perfect_foresight_solver;

rplot c;

4

The terminal condition needs to be a steady state and you need to have enough periods for the system to settle there.