Problem with Bayesian estimation

[Andrew]

Dear all,
I’m trying to run my Bayesian estimation mod file, but I get error warnings:

"
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):

Error Using print_info (line 42)
Blanchard Kahn conditions are not satisfied: no stable equilibrium
Error print_info (line 42)
error([‘Blanchard Kahn conditions are not satisfied: no stable’ …
Error initial_estimation_checks (line 175)
print_info(info, DynareOptions.noprint, DynareOptions)
Error dynare_estimation_1 (line 165)
oo_ = initial_estimation_checks(objective_function,xparam1,dataset_,dataset_info,M_,estim_params_,options_,bayestopt_,bounds,oo_);
Error dynare_estimation (line 105)
dynare_estimation_1(var_list,dname);
Error rer_new_bayes (line 738)
oo_recursive_=dynare_estimation(var_list_);
Error dynare (line 235)
evalin(‘base’,fname) ;
"
But I can run my simulation file without “Blanchard Kahn conditions are not satisfied: no stable equilibrium”.
I don’t know how to solve the problem. I wiil appreciate all your help! Thank you all!

Simulation file:rer_new.mod (21.0 KB)
Bayesian file:rer_new_bayes.mod (21.5 KB)
data file:bayes.xls (31 KB)

[jpfeifer]

Why don’t you follow the advice to start with your calibration?
Use

estimated_params_init(use_calibration);
end;

[Andrew]

Dear jpfeifer,
Thanks for your help! I have solved my problem.
I have some other questions:

1.Variables in DSGE are always between 0 and 1, but my data from real world are large numbers, do I need to do something with my data of observed variable for Bayesian estimation?
2.How to choose prior mean and std? Are there some rules or habits?
3.std=0.01 or 0.05, which one is more convincing?

Thank you again, you really helped a lot！

[jpfeifer]

1. Please read Pfeifer (2013): “A Guide to Specifying Observation Equations for the Estimation of DSGE Models”
2. See

DSGE Estimation - Imposing prior mean and std

Please see [Choosing an appropriate standard deviation for prior) and if this does not answer your question, report back. Formal prior elicitation is done in Del Negro Schorfheide (2008) - Forming priors for DGSE models. Regarding the error message: you are using a beta distribution that implies the parameter is between 0 and 1. Given that no realizations can be bigger than 1 or smaller than 0, this limits the standard deviation that is possible. If you impose a mean of 0.86, the parameter can …

3. That depends on your model and process on hand.