I am having an issue running baynesian estimation of a DSGE model. Dynare is displaying the following messages and I am unsure how to solve this issue. I have tried changing the mode_compute and priors, but doesn’t seem to offer a solution.

Any help on this issue is greatly appreciated. Thank you

POSTERIOR KERNEL OPTIMIZATION PROBLEM!
(minus) the hessian matrix at the “mode” is not positive definite!
=> posterior variance of the estimated parameters are not positive.
You should try to change the initial values of the parameters using
the estimated_params_init block, or use another optimization routine.
Warning: The results below are most likely wrong!

In dynare_estimation_1 at 694
In dynare_estimation at 89
In TRIAL_JP3_MATT at 351
In dynare at 180

Error using chol
Matrix must be positive definite.
Error in metropolis_hastings_initialization (line 68)
d = chol(vv);
Error in random_walk_metropolis_hastings (line 62)
ix2, ilogpo2, ModelName, MetropolisFolder, fblck, fline, npar, nblck, nruns, NewFile, MAX_nruns, d ] = …
Error in dynare_estimation_1 (line 782)
feval(options_.posterior_sampling_method,objective_function,options_.proposal_distribution,xparam1,invhess,bounds,dataset_,options_,M_,estim_params_,bayestopt_,oo_);
Error in dynare_estimation (line 89)
dynare_estimation_1(var_list,dname);
Error in TRIAL_JP3_MATT (line 351)
dynare_estimation(var_list_);
Error in dynare (line 180)
evalin(‘base’,fname) ; data.txt (9.1 KB) TRIAL_JP3_MATT.mod (5.33 KB)

One obvious problem is that your observation equations are wrong. You cannot estimate a model with mean 0 variables with data that is not mean 0. Please see Pfeifer(2013): “A Guide to Specifying Observation Equations for the Estimation of DSGE Models” sites.google.com/site/pfeiferecon/Pfeifer_2013_Observation_Equations.pdf.

Thank you for you help and quick reply. I have now demeaned the series, however still obtain the same error messages. Would you know what could still be causing this error?

Thank you very much for your reply. Seeing these red dots, would you suggest that the model is not correctly specified? Model calibrations work though?
I appreciate your time and response.

You need to understand where these dots come from, i.e. which economic mechanism gives rise to the model moving to the boundary of the uniqueness/stability region. It might be that there is a mistake in specifying the model, but there could also be an economic reason. Maybe you should start with a simpler model and then add features to it and see what drives the problem