Dynare writes following error message:
MJDGGES returns the following error code122
What does it mean? What could you recomend for solving this problem?
Hi,
The error comes from the (fortran) Lapack routine dgges.f (which performs the generalized schur decomposition needed to obtain the reduced form model). As you’ll understand by reading the header of the fortran routine (see below the section concerning the info variable) we cannot give you any hint if you don’t provide a mod file so that we can reproduce the problem.
Best,
Stéphane.
SUBROUTINE DGGES( JOBVSL, JOBVSR, SORT, DELCTG, N, A, LDA, B, LDB,
$ SDIM, ALPHAR, ALPHAI, BETA, VSL, LDVSL, VSR,
$ LDVSR, WORK, LWORK, BWORK, INFO )
*
* -- LAPACK driver routine (version 3.0) --
* Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
* Courant Institute, Argonne National Lab, and Rice University
* June 30, 1999
*
* .. Scalar Arguments ..
CHARACTER JOBVSL, JOBVSR, SORT
INTEGER INFO, LDA, LDB, LDVSL, LDVSR, LWORK, N, SDIM
* ..
* .. Array Arguments ..
LOGICAL BWORK( * )
DOUBLE PRECISION A( LDA, * ), ALPHAI( * ), ALPHAR( * ),
$ B( LDB, * ), BETA( * ), VSL( LDVSL, * ),
$ VSR( LDVSR, * ), WORK( * )
* ..
* .. Function Arguments ..
LOGICAL DELCTG
EXTERNAL DELCTG
* ..
*
* Purpose
* =======
*
* DGGES computes for a pair of N-by-N real nonsymmetric matrices (A,B),
* the generalized eigenvalues, the generalized real Schur form (S,T),
* optionally, the left and/or right matrices of Schur vectors (VSL and
* VSR). This gives the generalized Schur factorization
*
* (A,B) = ( (VSL)*S*(VSR)**T, (VSL)*T*(VSR)**T )
*
* Optionally, it also orders the eigenvalues so that a selected cluster
* of eigenvalues appears in the leading diagonal blocks of the upper
* quasi-triangular matrix S and the upper triangular matrix T.The
* leading columns of VSL and VSR then form an orthonormal basis for the
* corresponding left and right eigenspaces (deflating subspaces).
*
* (If only the generalized eigenvalues are needed, use the driver
* DGGEV instead, which is faster.)
*
* A generalized eigenvalue for a pair of matrices (A,B) is a scalar w
* or a ratio alpha/beta = w, such that A - w*B is singular. It is
* usually represented as the pair (alpha,beta), as there is a
* reasonable interpretation for beta=0 or both being zero.
*
* A pair of matrices (S,T) is in generalized real Schur form if T is
* upper triangular with non-negative diagonal and S is block upper
* triangular with 1-by-1 and 2-by-2 blocks. 1-by-1 blocks correspond
* to real generalized eigenvalues, while 2-by-2 blocks of S will be
* "standardized" by making the corresponding elements of T have the
* form:
* a 0 ]
* 0 b ]
*
* and the pair of corresponding 2-by-2 blocks in S and T will have a
* complex conjugate pair of generalized eigenvalues.
*
*
* Arguments
* =========
*
* JOBVSL (input) CHARACTER*1
* = 'N': do not compute the left Schur vectors;
* = 'V': compute the left Schur vectors.
*
* JOBVSR (input) CHARACTER*1
* = 'N': do not compute the right Schur vectors;
* = 'V': compute the right Schur vectors.
*
* SORT (input) CHARACTER*1
* Specifies whether or not to order the eigenvalues on the
* diagonal of the generalized Schur form.
* = 'N': Eigenvalues are not ordered;
* = 'S': Eigenvalues are ordered (see DELZTG);
*
* DELZTG (input) LOGICAL FUNCTION of three DOUBLE PRECISION arguments
* DELZTG must be declared EXTERNAL in the calling subroutine.
* If SORT = 'N', DELZTG is not referenced.
* If SORT = 'S', DELZTG is used to select eigenvalues to sort
* to the top left of the Schur form.
* An eigenvalue (ALPHAR(j)+ALPHAI(j))/BETA(j) is selected if
* DELZTG(ALPHAR(j),ALPHAI(j),BETA(j)) is true; i.e. if either
* one of a complex conjugate pair of eigenvalues is selected,
* then both complex eigenvalues are selected.
*
* Note that in the ill-conditioned case, a selected complex
* eigenvalue may no longer satisfy DELZTG(ALPHAR(j),ALPHAI(j),
* BETA(j)) = .TRUE. after ordering. INFO is to be set to N+2
* in this case.
*
* N (input) INTEGER
* The order of the matrices A, B, VSL, and VSR. N >= 0.
*
* A (input/output) DOUBLE PRECISION array, dimension (LDA, N)
* On entry, the first of the pair of matrices.
* On exit, A has been overwritten by its generalized Schur
* form S.
*
* LDA (input) INTEGER
* The leading dimension of A. LDA >= max(1,N).
*
* B (input/output) DOUBLE PRECISION array, dimension (LDB, N)
* On entry, the second of the pair of matrices.
* On exit, B has been overwritten by its generalized Schur
* form T.
*
* LDB (input) INTEGER
* The leading dimension of B. LDB >= max(1,N).
*
* SDIM (output) INTEGER
* If SORT = 'N', SDIM = 0.
* If SORT = 'S', SDIM = number of eigenvalues (after sorting)
* for which DELZTG is true. (Complex conjugate pairs for which
* DELZTG is true for either eigenvalue count as 2.)
*
* ALPHAR (output) DOUBLE PRECISION array, dimension (N)
* ALPHAI (output) DOUBLE PRECISION array, dimension (N)
* BETA (output) DOUBLE PRECISION array, dimension (N)
* On exit, (ALPHAR(j) + ALPHAI(j)*i)/BETA(j), j=1,...,N, will
* be the generalized eigenvalues. ALPHAR(j) + ALPHAI(j)*i,
* and BETA(j),j=1,...,N are the diagonals of the complex Schur
* form (S,T) that would result if the 2-by-2 diagonal blocks of
* the real Schur form of (A,B) were further reduced to
* triangular form using 2-by-2 complex unitary transformations.
* If ALPHAI(j) is zero, then the j-th eigenvalue is real; if
* positive, then the j-th and (j+1)-st eigenvalues are a
* complex conjugate pair, with ALPHAI(j+1) negative.
*
* Note: the quotients ALPHAR(j)/BETA(j) and ALPHAI(j)/BETA(j)
* may easily over- or underflow, and BETA(j) may even be zero.
* Thus, the user should avoid naively computing the ratio.
* However, ALPHAR and ALPHAI will be always less than and
* usually comparable with norm(A) in magnitude, and BETA always
* less than and usually comparable with norm(B).
*
* VSL (output) DOUBLE PRECISION array, dimension (LDVSL,N)
* If JOBVSL = 'V', VSL will contain the left Schur vectors.
* Not referenced if JOBVSL = 'N'.
*
* LDVSL (input) INTEGER
* The leading dimension of the matrix VSL. LDVSL >=1, and
* if JOBVSL = 'V', LDVSL >= N.
*
* VSR (output) DOUBLE PRECISION array, dimension (LDVSR,N)
* If JOBVSR = 'V', VSR will contain the right Schur vectors.
* Not referenced if JOBVSR = 'N'.
*
* LDVSR (input) INTEGER
* The leading dimension of the matrix VSR. LDVSR >= 1, and
* if JOBVSR = 'V', LDVSR >= N.
*
* WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK)
* On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
* LWORK (input) INTEGER
* The dimension of the array WORK. LWORK >= 8*N+16.
*
* If LWORK = -1, then a workspace query is assumed; the routine
* only calculates the optimal size of the WORK array, returns
* this value as the first entry of the WORK array, and no error
* message related to LWORK is issued by XERBLA.
*
* BWORK (workspace) LOGICAL array, dimension (N)
* Not referenced if SORT = 'N'.
*
* INFO (output) INTEGER
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value.
* = 1,...,N:
* The QZ iteration failed. (A,B) are not in Schur
* form, but ALPHAR(j), ALPHAI(j), and BETA(j) should
* be correct for j=INFO+1,...,N.
* > N: =N+1: other than QZ iteration failed in DHGEQZ.
* =N+2: after reordering, roundoff changed values of
* some complex eigenvalues so that leading
* eigenvalues in the Generalized Schur form no
* longer satisfy DELZTG=.TRUE. This could also
* be caused due to scaling.
* =N+3: reordering failed in DTGSEN.
*
* =====================================================================
I’m trying to create large scale DSGE. I’m feeling that model includes unit root. So, there is not steady state (without detrending). I’m finding point which is approximately steady state. Parameters aren’t calibrated.
If you need any additional details, I’ll be happy to provide it.
model_steadystate.m (85 KB)
model_steadystate.m (471 KB)
model.mod (12.9 KB)
Hi, Your example is not running on my laptop… Are you sure your steady state file is correct ? I get the following error message.
Best, Stéphane.
??? Subscripted assignment dimension mismatch.
Error in ==> model_steadystate>sub_ono_0 at 251
U(1,1)=exp(-c)*(1+exp(z_H)*y^psi-bbb*exp(z_H)*y^psi)-limda;
Error in ==> fminunc at 243
[f,GRAD(:)] = feval(funfcn{3},x,varargin{:});
Error in ==> model_steadystate at 9
[X_X_X,fval]=fminunc(@sub_ono_0,X_X_X,optimset('MaxFunEvals',40000,'MaxIter',10^9,'GradObj','on','TolFun',1.0e-7,'Display','iter'));
Error in ==> steady_ at 33
[oo_.steady_state,check] = feval([M_.fname '_steadystate'],...
Error in ==> steady at 52
steady_;
Error in ==> model at 822
steady;
Error in ==> dynare at 125
evalin('base',fname) ;
Caused by:
Failure in initial user-supplied objective function evaluation. FMINUNC cannot continue.
It’s really strange. My steady file is running on my PC.
I have only 2 ideas about possible reasons.
- I’m using dynare 3. You could use dynare 4 which have different syntaxes for steady state file. Then my steady state file doesn’t take parameters (“global …” create zero dimensional variables).
- You have message: “??? Subscripted assignment dimension mismatch.” It means that “exp(-c)*(1+exp(z_H)y^psi-bbbexp(z_H)*y^psi)-limda” isn’t single dimension value. Variables (z_H, c, limda, y) are declared as single dimension (line 159, 178, 196, 244). Thus, one of parameters (psi or bbb) isn’t single dimension. It’s possible that your version of matlab reserves “psi” (by the same way as “pi”, but value is multidimensional). My version is 7.3.0.267
Sorry. I will try with dynare version 3… But note that this version of dynare is not maintained anymore.
Best, Stéphane.
I finally found some time to run your file with Dynare version 3… But your steadystate files do not seem to find the steady state. Dynare evaluates the jacobian around a point which is far from the steady state. After the command steady; you can use the command resid(1); and Dynare will print the residuals of the static equation evaluated at the point given by your steady state file.
I see that in the steady state file you minimize a function. I don’t understand how you could find a steady state by minimizing a function… The steadystate file has to provide the steady state to Dynare, not an initial guess.
Best, Stéphane.
I’m sure that model doesn’t have steady state. I’m feeling that model includes unit root.
My steady file minimize sum of squared errors (“steady restrictions”). This sum is about 0.029. This means that some of restrictions doesn’t fit (resides isn’t equal to zero). But I think that I could ignore this divergence.
When I used worse optimisation (sum was about 0.04) dynare was able to calculate eigenvalues (check procedure). But after modification of steady file, dynare shows error code122.
When I force dynare to use sims algorithm instead of MJDGGES, I have seen NaN instead of some eigenvalues. I can’t understand what it means. And I don’t know what error code122 means.
I don’t know what I could say more.
Concerning the error code:
122 is equal to 120 (the number of generalized eigenvalues to be computed) + 2
So the interpretation of the error code as given by lapack is :
I think that the problem of scaling is due to your steadystate file, which defines the point where the jacobian of the model is evaluated. If you look at the values in matrices e and d (in dr1.m), which are built from the jacobian, you will see very huge crazy numbers. For instance, in matrix e the ratio between the maximum element and the minimum element is of order 10^9 !
I don’t know if there is really (and where) a unit root in your model… But even if you have a unit root (or more than one) you should have some long term relationships between the non stationary variables. The steady state provided to Dynare should be consistent with these cointegration relationships… But your routine doesn’t ensure that these relationships are satisfied.
Stéphane.
Thank you.
Scaling problem is real big one for this model. I’ll try to use analitycal linearisation.