No warning of singular system in ss computation

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No warning of singular system in ss computation

Postby Henrik111 » Fri Jan 10, 2014 2:20 pm

Hello,

I use Dynare v4.3, and during my reduction of one of my (erroneous) models I arrived at a simple 4 equaton dummy code,
2 eqs were actually algebraically (almost) equivalent. 4 variables - 4 equations, obviously singular system.

Dynare still computes steady state without issuing any warning or error message.
This is the same whether I use solve_algo = 0..2

I attached the code, and am curious whether I miss something, or this is a feature of Dynare that could be improved upon.


regards,
Henrik

AN_2b_ss.mod
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Re: No warning of singular system in ss computation

Postby jpfeifer » Fri Jan 10, 2014 5:28 pm

Why should singularity be a problem for the steady state? If your system is underdetermined, there will be infinitely many of them. The steady state that Dynare finds simply solves your system. A different issue is if your numerical solver need to invert the derivative matrix (Newton method). In this case, you will get a crash.

Note also that Dynare finds your problem. Model diagnostics will tell you:
model_diagnostic: the Jacobian of the static model is singular
there is 1 colinear relationships between the variables and the equations
Colinear variables:
Hh
Zh
W
Colinear equations
1 2

The presence of a singularity problem typically indicates that there is one
redundant equation entered in the model block, while another non-redundant equation
is missing. The problem often derives from Walras Law.
------------
Johannes Pfeifer
University of Cologne
https://sites.google.com/site/pfeiferecon/
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Re: No warning of singular system in ss computation

Postby Henrik111 » Sun Jan 12, 2014 11:45 am

Thank you for your reply!

model_diagnostics is the feature I was looking for.

Chosing an ss from multiple ss is of course valid in a technical sense, still it is rarely what people have in mind
when e.g. trying to linearise their model around one.
Having many ss and choosing arbitrarily (silently) from them may pose a problem because your results
may be less than robust in this case.

With regards,
Henrik
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