Dear Professor, I have the following two problems when using Bayesian estimation. I hope you can help me.

There are 9 eigenvalue(s) larger than 1 in modulus for 8 forward-looking variable(s)

The rank condition ISN’T verified![gov.mod|attachment]

MODEL_DIAGNOSTICS: No obvious problems with this mod-file were detected.

Error in computing likelihood for initial parameter values。

Blanchard Kahn conditions are not satisfied: indeterminacy

The following si my code and data.

gov.mod (4.8 KB) fiscal_data.xls (33.5 KB)

Check your model again. While it is linear,

```
k=delta*i+(1-delta)*k(-1);
```

does not look like a correct linearization of the original equation, i.e. it holds in levels but not in log-levels.Or did you only linearize?

Generally, I recommend working with a simpler model, i.e. first do no government capital and lump-sum taxes, then do the fiscal rules and then government capital.

Thanks for your help.I found some mistakes.Then i changed.But,there is still a problem.

MODEL_DIAGNOSTICS: No obvious problems with this mod-file were detected.

initial_estimation_checks:: The forecast error variance in the multivariate Kalman filter became singular. This is often a sign of stochastic singularity, but can also sometimes happen by chance for a particular combination of parameters and data realizations. If you think the latter is the case, you should try with different initial values for the estimated parameters.

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

Search the forum. Usually this means that your observables form a linear combination.