Problems with Blanchard Kahn conditions

Dear all.

I know this topic has been covered in numerous topics on the forum, but as I still have problems after revising the timing of my model, I thought it might be worth a shot to see if anyone out there could help me.

Basically, I’m trying to construct a model with financial frictions in terms of collateral constraints, following Iacoviello (2005), with extensions in terms of long-term debt (approximating a 30-year annuity, following Kydland et. al. 2012), a banking sector with imperfect competition on the loan side (following Gerali et. al. 2009) including a Calvo setup on setting the market interest rate, to proxy the coexistence of adjustable and fixed-rate debt. Furthermore, the policy interest rate is set exogenously for the time being. The model has not yet been fully calibrated.

When running the .mod file I run into the problem:
“Blanchard Kahn conditions are not satisfied: indeterminacy”

In deriving the price setting scheme(see attached file), I have followed the procedure in:

(Thanks to Johannes Pfeifer for the thorough derivation, it is greatly appreciated!)

The problem of the retailer is identical to that in Iacoviello (2005).

I can’t shake the feeling that I might be missing something blatantly obvious, either in the timing of my model or in deriving the price setting.

Any help would be greatly appreciated!

Derivation of Calvo pricing.pdf (151.0 KB)
Model1.mod (16.9 KB)

Another, more general question: If the error of: “Blanchard Kahn conditions are not satisfied: indeterminacy” is not due to a timing error in the model block, but rather there being multiple equilibria, would a loglinearization of the model in any way help to alleviate the problem?

A couple of thoughts:

  1. No, linearization would not solve any problems.
  2. It is almost always a timing problem.
  3. Are you sure the timing on the housing is correct?
  4. Your model is too complex. You should start with a working version and only then add features to it. Currently, this is searching for a needle in a haystack.
    An finally. some gratuitous advice_
  5. Bachelor students are not supposed to work on models that complicated without intense supervision. I have seen too many cases like this miserably fail. Most of the time, the goals set are too unrealistic given the prior training and the time frame envisioned.