# Blanchard / Kahn Conditions

Hello there,

I am currently using Dynare to estimate the parameters of an DSGE model with financial frictions. When I use calibrations from the literature I get a stable solution and are able to conduct simulations. Now I want to estimate the parameter using ML and I get the following error (Blanchard & Kahn conditions are not satisfied: no stable equilibrium.):

Error in computing likelihood for initial parameter values

ESTIMATION_CHECKS: There was an error in computing the likelihood for initial parameter values.
ESTIMATION_CHECKS: If this is not a problem with the setting of options (check the error message below),
ESTIMATION_CHECKS: you should try using the calibrated version of the model as starting values. To do
ESTIMATION_CHECKS: this, add an empty estimated_params_init-block with use_calibration option immediately before the estimation
ESTIMATION_CHECKS: command (and after the estimated_params-block so that it does not get overwritten):

Blanchard & Kahn conditions are not satisfied: no stable equilibrium.

How do I deal with this error since the base model should be stable due to the simulations with calibrated values?

Thank you very much!

Addendum: running the model_diagnostic command returns the following error message

model_diagnostics(M_,options_,oo_)
MODEL_DIAGNOSTICS: The Jacobian of the static model is singular
MODEL_DIAGNOSTICS: there is 2 colinear relationships between the variables and the equations
Relation 1
Colinear variables:
p
h
AUX_ENDO_LAG_11_1
Relation 2
Colinear variables:
p
h
AUX_ENDO_LAG_11_1
Relation 1
Colinear equations
Columns 1 through 16

`````` 1     3     4     5     6     7     8     9    10    11    12    14    15    17    20    21
``````

Column 17

``````22
``````

Relation 2
Colinear equations
3

MODEL_DIAGNOSTICS: The singularity seems to be (partly) caused by the presence of a unit root
MODEL_DIAGNOSTICS: as the absolute value of one eigenvalue is in the range of ±1e-6 to 1.
MODEL_DIAGNOSTICS: If the model is actually supposed to feature unit root behavior, such a warning is expected,
MODEL_DIAGNOSTICS: but you should nevertheless check whether there is an additional singularity problem.
MODEL_DIAGNOSTICS: The presence of a singularity problem typically indicates that there is one
MODEL_DIAGNOSTICS: redundant equation entered in the model block, while another non-redundant equation
MODEL_DIAGNOSTICS: is missing. The problem often derives from Walras Law.

If there is a unit root, you need to use the `diffuse_filter` option to `estimation`.

Hello Professor,

thank you very much, this solved my problem!

Best regards,