Niko Hauzenberger, Michael Pfarrhofer
arXiv 31 Jul 2026 · Econometrics
arXiv:2607.29215 · PDF · Extracted main text
We develop fast methods for conditional forecasting and structural scenario analysis with high-dimensional Bayesian vector autoregressions (VARs). Our general framework features a factor structure on the reduced-form errors, which enables fast and order-invariant equation-by-equation estimation; suitably identified factors admit a structural interpretation. The scenarios are defined through separate distributional restrictions on observables, structural shocks and idiosyncratic components. The computational cost of our proposed algorithm is cubic only in the number of restrictions, while the dimension of the forecasted system enters linearly. In our application with $33$ macroeconomic and financial variables and ten set-identified structural shocks for the US, we compute counterfactual predictions for oil price scenarios in the context of the 2026 closure of the Strait of Hormuz. The same oil price path is consistent with outcomes ranging from a mostly benign episode to pronounced stagflation, depending on which structural and idiosyncratic shocks are allowed to deliver it.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Antolin-Diaz J, Petrella I, and Rubio-Ramŕez JF (2021) Structural scenario analysis with SVARs | 0.950 | 7 | 4 | 86% |
| 2 | Arias JE, Rubio-Ramŕez JF, Rudolf D, and Shin M (2026) Large SVARs | 0.737 | 4 | 3 | 50% |
| 3 | Chan J, Matthes C, and Yu X (2026) Large structural VARs with multiple sign and ranking restrictions | 0.737 | 4 | 3 | 50% |
| 4 | Crump RK, Eusepi S, Giannone D, Qian E, and Sbordonea A (2025) A Large Bayesian VAR of the US Economy | 0.737 | 3 | 3 | 67% |
| 5 | Korobilis D (2022) A new algorithm for structural restrictions in Bayesian vector autoregressions | 0.737 | 3 | 2 | 100% |
| 6 | Chan J, Eisenstat E, and Yu X (2022) Large Bayesian VARs with factor stochastic volatility: Identification, order invariance and structural analysis | 0.644 | 2 | 2 | 100% |
| 7 | Kilian L, Plante MD, Richter AW, and Zhou X (2026) The Impact of the 2026 Iran War on US Inflation: A Scenario Analysis | 0.644 | 2 | 2 | 100% |
| 8 | McKay A, and Wolf CK (2023) What can time-series regressions tell us about policy counterfactuals? | 0.644 | 2 | 2 | 100% |
| 9 | Prüser J (2024) A large non-Gaussian structural VAR with application to monetary policy | 0.644 | 2 | 2 | 100% |
| 10 | Waggoner DF, and Zha T (1999) Conditional forecasts in dynamic multivariate models | 0.585 | 5 | 3 | 20% |
Showing the top 10 of 38 scored citations.