Question about marginal data density "ms_compute_mdd"

BVAR
1

Dear all,
I am currently working on a replication of a paper where i should use a markov switching SBVAR, estimate it and compare models with marginal data densities.
The code structure is:

ms_estimation(datafile=testv016
,freq=4
,initial_year=1970
,final_year=2009
,nlags=4
,max_repeated_optimization_runs=1
,max_number_of_stages=0
);
ms_simulation(mh_replic=1000);
ms_compute_mdd;

The code is fine finding estimates of A0 and A+ however for the MDD part i am getting the following error. What should be the possible reason of it?

MS-SBVAR Marginal Data Density
Unable to open est_final_testv016.out
Processing posterior draws
Matrix not positive definite.

Thanks,

2

Is this the full error message? Which matrix is not positive definite? In which line of which function does the crash happen?

3

This is the error that i get:

Elapsed Time: 452 seconds
Burn-in period - 100 draws
Elapsed Time: 453 seconds
Simulating - 1000 draws
1000 * 1 iterations completed out of 1000 * 1
Elapsed Time: 469 seconds
Total Elapsed Time: 469 seconds
MS-SBVAR Marginal Data Density
Processing posterior draws
Matrix not positive definite.
Error in MS-SBVAR MEX file.
Error using mexErrCheck (line 41)
Error encountered in: ms_compute_mdd.
Error in ms_compute_mdd (line 55)
mexErrCheck(‘ms_compute_mdd’,err);
Error in testv016 (line 129)
[options_, oo_] = ms_compute_mdd(M_, options_, oo_);
Error in dynare (line 223)
evalin(‘base’,fname) ;

For further diagnosis I am providing the command window history so that it can be helpful.
Command Window.pdf (580.9 KB)

4

From what I can see, there is a problem with mode-finding. The objective values shown are so big that they can only be error codes. You need to find out why your VAR does not fit the data/where the problem lies. What happens if you just do OLS on your data without any Bayesian estimation or regime-switching?

5

First, one by one equation OLS and lower cholesky identification restrictions seems work fine.
The problem looks related with identification restrictions. The paper that I am trying to replicate is “Were There Regime Switches in U.S. Monetary Policy?” by Sims and Zha.
Additional to the exact zero restrictons, they have stated that they added a prior information as a correlation between two equations. More clearly, they use a prior that makes coefficients of two variables positively correlated with 0.8 in one equation and negatively correlated with -0.8 in another equations.
On their original code, they are providing this by creating a H0multi matrix while defining the priors. After that they are combining asymetric prior with linear restrictions.
Does Dynare support such a corrlation between variables in order to create a specific effect?
Thanks,

6

Unfortunately, I am not very familiar with this part of Dynare. Maybe @HoutanBastani knows more or who to ask.

1 Like