Dear Jpfeifer,
I use Bayesian to estimate some parameters of my model. However, when I use “mode_compute=4” and “mode_compute=5”, I get different results through variance decomposition, although the both mode computation command can get good convergence result and identification analysis. Which result should I trust? Does it mean that my model is not robust and may have some fundamental problems?
Regards,
It most probably means you did not get convergence to the same maximum/mode. Use the value of the posterior to see which mode was better.
Dear Jpfeifer,
Thanks for your answer. Could you explain a bit more in detail about how I can use the value of the posterior to check which mode was better? What is the criterion that mode is better?
Regards,
The posterior is like the likelihood. The higher the better. After some mode-finders, Dynare is going to display the objective function at the mode. As the objective is minus the posterior, the lower the better.
Dear Jpfeifer,
Thanks for your explaination. I know that dynare can simulate the posterior distribution at the mode after some mode-finders. But I am still confused. Do you mean that I can compare the log data density? If not, how can I check which mode was better? I mean is there an explicit way to check?
I am not talking about the log data density, but the posterior. If you are working with the unstable version, try using the file at github.com/JohannesPfeifer/dynare/commit/edca875d2a815ba7f98d68c64adc7ef18b69aaaf
Dear Jpfeifer,
I am not using the unstable version but the stable version 4.4.3. Do you mean than I can compare the value of “Objective function at mode” shown in the log file? However, I cannot find the corresponding value when I use “mode_compute=6”. When I use “mode_compute=6”, I can only find “Final value of the log posterior (or the likelihood)”. Hope to receive your help. Thanks!
Regards,
Those two things are the same. The objective function is minus the log-posterior. Note that mode_compute=6 also displays MINUS the log posterior.