It still can run but the rank condition isn't verified! why?
Posted: Tue May 09, 2017 2:15 pm
Dear Pro. Pfeifer,
I wrote a dynare code about the housing market. I've already know which parameter(miu) cause indeterminacy or multiple equilibrium. But the interesting thing is that although the rank condition isn't verified, the estimation could still work. Could you please explain the reason.
"....EIGENVALUES:
Modulus Real Imaginary
0 0 0
7.659e-16 7.659e-16 0
0.4437 0.3961 0.1999
0.4437 0.3961 -0.1999
0.4893 0.4893 0
0.6 0.6 0
0.6 0.6 0
0.6 0.6 0
0.6 0.6 0
0.6 0.6 0
0.6223 0.6223 0
0.9449 0.9445 0.02866
0.9449 0.9445 -0.02866
1.002 -1.002 0
1.011 1.011 0
1.046 1.046 0
1.079 1.079 0
1.581 1.581 0
2.069 2.069 0
3.93 3.93 0
1.333e+16 1.333e+16 0
3.308e+17 -3.308e+17 0
There are 9 eigenvalue(s) larger than 1 in modulus
for 8 forward-looking variable(s)
The rank condition ISN'T verified!
Loading 72 observations from china_data.m
Initial value of the log posterior (or likelihood): -909.1994
Gradient norm 23658.2118
Minimum Hessian eigenvalue 0.10647
Maximum Hessian eigenvalue 25801699.2611
Iteration 1
Correct for low angle: 0.000547277
Predicted improvement: 209.449621809
lambda = 1; f = 909.1996753
lambda = 0.33333; f = 909.1993733
lambda = 0.11111; f = 866.9606148
lambda = 0.2148; f = 909.1993606
lambda = 0.14463; f = 857.1288476....."
Here are the attachments including code and data.
Best!
Thank you
Zixiang Zhu
I wrote a dynare code about the housing market. I've already know which parameter(miu) cause indeterminacy or multiple equilibrium. But the interesting thing is that although the rank condition isn't verified, the estimation could still work. Could you please explain the reason.
"....EIGENVALUES:
Modulus Real Imaginary
0 0 0
7.659e-16 7.659e-16 0
0.4437 0.3961 0.1999
0.4437 0.3961 -0.1999
0.4893 0.4893 0
0.6 0.6 0
0.6 0.6 0
0.6 0.6 0
0.6 0.6 0
0.6 0.6 0
0.6223 0.6223 0
0.9449 0.9445 0.02866
0.9449 0.9445 -0.02866
1.002 -1.002 0
1.011 1.011 0
1.046 1.046 0
1.079 1.079 0
1.581 1.581 0
2.069 2.069 0
3.93 3.93 0
1.333e+16 1.333e+16 0
3.308e+17 -3.308e+17 0
There are 9 eigenvalue(s) larger than 1 in modulus
for 8 forward-looking variable(s)
The rank condition ISN'T verified!
Loading 72 observations from china_data.m
Initial value of the log posterior (or likelihood): -909.1994
Gradient norm 23658.2118
Minimum Hessian eigenvalue 0.10647
Maximum Hessian eigenvalue 25801699.2611
Iteration 1
Correct for low angle: 0.000547277
Predicted improvement: 209.449621809
lambda = 1; f = 909.1996753
lambda = 0.33333; f = 909.1993733
lambda = 0.11111; f = 866.9606148
lambda = 0.2148; f = 909.1993606
lambda = 0.14463; f = 857.1288476....."
Here are the attachments including code and data.
Best!
Thank you
Zixiang Zhu