# Bayesian Estimation Questions

**URL:** <https://forum.dynare.org/t/bayesian-estimation-questions/26798>\
**Category:** General DSGE Modeling\
**Created:** [26 November 2024 23:29 UTC](https://forum.dynare.org/t/bayesian-estimation-questions/26798 "2024-11-26T23:29:22Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![yw3864a](https://forum.dynare.org/letter_avatar_proxy/v4/letter/y/71c47a/32.png) [@yw3864a](https://forum.dynare.org/u/yw3864a)\
**Post date:** [26 November 2024 23:29 UTC](https://forum.dynare.org/t/bayesian-estimation-questions/26798/1 "2024-11-26T23:29:22Z")

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Hi everyone,

I’ve shortened my earlier questions for clarity and would really appreciate your input:

- I have **5 shocks** and **5 observables** , and I’ve introduced a **correlation** between two shocks. Does this correlation count as an additional shock for estimation, allowing me to add a 6th observable?
- Historical decomposition depends on the chosen observables. If the number of shocks limits the observables I can include, how can I ensure the results are robust? I’ve noticed that while the decomposition looks strong for included observables, it often appears weaker for excluded ones.
- My dataset spans **1980Q1–2024Q2** , with a major shock (e.g., COVID-19) assumed in **2019Q4**. I’m considering using the `heteroskedastic_shocks` block to account for time-varying shock variances. Does this approach make the model deterministic (like perfect foresight), and how does it differ from standard stochastic models? Also, how are periods defined under `heteroskedastic_shocks`—do they align with the presample, estimation, or another timeline? If I mix heteroskedastic and non-heteroskedastic shocks, how does the `heteroskedastic_filter` option affect estimation?
- Finally, I plan to treat **1980–2019Q3** as presample data and **2019Q4–2024Q2** for likelihood calculation, assuming the economic structure differs during the shock period. Is this approach reasonable? Do DSGE models typically include data from shock periods in estimation, or are there cases where excluding such periods provides better results? Or is this assumption subjective?
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Thanks in advance for your help!

Best,  
Yamoi

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**Author:** ![jpfeifer](https://forum.dynare.org/user_avatar/forum.dynare.org/jpfeifer/32/5044_2.png) [@jpfeifer](https://forum.dynare.org/u/jpfeifer)\
**Post date:** [28 November 2024 10:39 UTC](https://forum.dynare.org/t/bayesian-estimation-questions/26798/2 "2024-11-28T10:39:59Z")

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1. No, correlation between shocks does not mean there is effectively a 6th shock.
2. See e.g.

> [@Problems with the results of Bayesian estimation?](https://forum.dynare.org/t/problems-with-the-results-of-bayesian-estimation/16067/2):
>
> See e.g.

3. The `heteroskedastic_shocks` allows for unforeseen structural breaks in the shock variances. It does not make the model deterministic. It simply allows you to have periods where bigger shocks are considered to be more likely.  
4. That assumption is always subjective. After all, we don’t know which process generated the data.