Replicating Adolfson(2007) bayesian open economy DSGE model

I am replicating Adolfson (2007). My dynare code has a problem is that

''Error using print_info (line 98)
Likelihood is not a number (NaN) or a complex number

Error in print_info (line 98)
error(‘Likelihood is not a number (NaN) or a complex number’);

Error in initial_estimation_checks (line 69)
print_info(info, DynareOptions.noprint, DynareOptions)

Error in dynare_estimation_1 (line 179)
oo_ = initial_estimation_checks(objective_function,xparam1,dataset_,M_,estim_params_,options_,bayestopt_,oo_);

Error in dynare_estimation (line 89)

Error in allv (line 1697)

Error in dynare (line 180)
evalin(‘base’,fname) ;’’

I would like to upload all my file as below

anyone can help me
VARDATA.xls (60.5 KB)
allv_steadystate.m (3.45 KB)
allv.mod (27.7 KB)

I don’t get that same error message, but rather a different one that comes from the fact that you forgot the


Dear Prof. Pfeifer

yes I got it by adding your suggested command. My model and data are not stationary yet

Your data should be stationary. Some of the model variables will not be stationary.

Dear Pfeifer

Yes sir, In this case, when I need a stationary data?

and another question is that

I have read your paper, titled: ‘‘a guide to sepcifying observation equations for the estimation of DSGE model’’

I know that I have to match the observable variables with the theoretical model variables before estimation

However, there are some complicated models with many variables. Then do we have a general solution to match the observable variables with the theoretical model variables .

In particular, I am working on the paper, titled: ‘‘Optimal monetary policy in an operational medium-sized DSGE model’’ ( … x/abstract)

Then I read their Technical appendix as the attached file. I have difficulty to derive the measurement equation systems (Section 3.1. Difference Specification, page. 28)

I mean How to derive this measurement equation system?

would you kindly give me some advices about this

Thank you so much indeed
ALLS1TechnAppx.pdf (325 KB)

Check time series books that describe Kalman Filter. From Hamilton to Nelson, Kim, and more recently published texts.

Please do not cross-post. See my answer at [Bayesian DSGE model)