Bayessian Estimation

Estimation ML/Bayesian estimation
1

hello,

I a doing a bayessian estimation, but for some reason the plots corresponding to posterior (green and gray lines) are not shown, then everything seems correct:
estimation(lik_init=2,plot_priors = 1,bayesian_irf,datafile=Data_import,conf_sig =.95,prefilter = 1,filtered_vars,smoother,first_obs=2,mode_check,mode_compute=6,moments_varendo,mh_nblocks=5,mh_replic=200000,mh_jscale=0.5,mh_init_scale=1) y x c pih q;

Thanks in advance for your helpbol.mod (6.1 KB) lala.m (14.5 KB)Data_import.m (181 Bytes)

2

You did not provide the data file needed to run the codes.

3

bol.mod (6.1 KB) Data_import.m (181 Bytes) lala.m (13.9 KB) LALA.xlsx (17.0 KB)

Thanks for your reply,
PD: first you need to run the m file lala,

4

You have a nograph-option in your file.

5

Thanks!
A couple of questions more please:
is it correct to “mix” a Bayessian estimation and a calibration? or do I need to necessarily estimate all the parameters?
Also,how can I improve the Bayessian estimation, because my graphs of prior and posterior distributions make no sense at all.

Thanks in advance!

6
  1. No, it is standard practice to calibrate some parameter (sometimes called dogmatic priors.
  2. If results do not make sense, first check your observation equations and identification.
7

Hello,
I am doing a Bayessian Estimation for two different countries in the period 2000-2020. But the data in 2020 is atypical, do you think is a good idea to run two different bayessian estimations, one for the period 2000-2019, and the second only for 2020?,

Myabe, a markov-switching method is better, but is it available in dynare?, where can I find an example?.

Thanks in advance

8
  1. Have a look at e.g. Including observable data during COVID19 period into DSGE model
    I would leave the last year out.
  2. No, Markov switching is not supported by Dynare. You want to use Junior Maih’s RISE toolbox for this.
9

Thanks a lot for your reply,
I had a look on the topic " Including observable data during COVID19 period into DSGE model", thus, I won´t include the data of 2020 in my bayessian estimation.
However, I found several papers that actually include these data (I attach one of them).

I am also doing a welfare analysis based on my estimation, and the ranking of monetary policy changes completely when I include 2020. So, I was thinking to make two different estimations, the first one taking into account 1966-2019, and the second one 1966-2020 and show both results. However, I am still not shure :frowning:
sustainability-13-03362-v2.pdf (1.2 MB)

10

I don’t think there is a strict right or wrong here. We simply don’t know whether there was indeed a problematic structural break. Views differ here. Reporting both alternatives seems like a sensible compromise.

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