Best practices for SVAR specification, structural identification, and formulating research questions without explicit single dependent variables

[u/Sirius0516]

Hi everyone,

I am working on an empirical research project using a Structural Vector Autoregression (SVAR) framework. Since all variables in the system are treated as endogenous, I want to ensure I properly frame my research question and avoid standard single-equation "dependent vs. independent" pitfalls.

1. Research Question Framing: What is the standard convention in applied literature to clearly state the core research objective when focusing on shock identification, transmission mechanisms, and impulse responses rather than single-equation regressions?
2. Identification Strategy: For those working with short-run and long-run zero restrictions (or sign restrictions), what are the most common pitfalls when defending the exclusion restrictions in the A and B matrices?
3. Diagnostics & Robustness: Beyond lag selection criteria (AIC/BIC), stability checks (roots within the unit circle), and bootstrap confidence bands for IRFs, what robustness checks do reviewers/econometricians typically expect to see (e.g., historical decompositions, alternative ordering, sign restrictions)?

Any recommended papers, book chapters or practical tips would be greatly appreciated!

[u/Simple_Resident8061]

I can’t speak to everything (I can’t remember some papers off the top of my head and I’m on my phone) but I will say to not do alternative ordering. The idea is that you’re violating your economic theory so don’t change it. If you say, want to study news -> oil prices -> inflation, don’t change the order because that’s specifically what you’re interested in. Hope this helps!

[u/wer08 → u/Simple_Resident8061]

Adding to this, to check robustness you can replace individual variables with similar ones rather than reorder. You could for example replace gdp with industrial production to check your baseline results.