Michael Pfarrhofer, Anna Stelzer
arXiv 12 Feb 2025 · Econometrics · 1 citations (OpenAlex)
arXiv:2502.08440 · PDF · DOI · OpenAlex · Extracted main text
We present an econometric framework that adapts tools for scenario analysis, such as variants of conditional forecasts and generalized impulse responses, for use with dynamic nonparametric models. The proposed algorithms are based on predictive simulation and sequential Monte Carlo methods. Their utility is demonstrated with three applications: (1) conditional forecasts based on stress test scenarios, measuring (2) macroeconomic risk under varying financial stress, and estimating the (3) asymmetric effects of financial shocks in the US and their international spillovers. Our empirical results indicate the importance of nonlinearities and asymmetries in relationships between macroeconomic and financial variables.
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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 | Breitenlechner M, Georgiadis G, and Schumann B (2022) What goes around comes around: How large are spillbacks from US monetary policy? | 1.000 | 6 | 3 | 100% |
| 2 | Clark TE, Huber F, Koop G, Marcellino M, and Pfarrhofer M (2023) Tail forecasting with multivariate Bayesian additive regression trees | 1.000 | 5 | 3 | 100% |
| 3 | Antolin-Diaz J, Petrella I, and Rubio-Ramŕez JF (2021) Structural scenario analysis with SVARs | 0.956 | 8 | 3 | 88% |
| 4 | Chan JC, Pettenuzzo D, Poon A, and Zhu D (2025) Conditional Forecasts in Large Bayesian VARs with Multiple Equality and Inequality Constraints | 0.928 | 5 | 4 | 80% |
| 5 | Bańbura M, Giannone D, and Lenza M (2015) Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections | 0.928 | 5 | 3 | 80% |
| 6 | Chipman HA, George EI, and McCulloch RE (2010) BART: Bayesian additive regression trees | 0.843 | 4 | 3 | 75% |
| 7 | Crump RK, Eusepi S, Giannone D, Qian E, and Sbordonea A (2025) A Large Bayesian VAR of the US Economy | 0.843 | 4 | 3 | 75% |
| 8 | Goncalves S, Herrera AM, Kilian L, and Pesavento E (2024) State-dependent local projections | 0.843 | 3 | 3 | 100% |
| 9 | Hauzenberger N, Huber F, Marcellino M, and Petz N (2025) b), Gaussian process vector autoregressions and macroeconomic uncertainty | 0.843 | 3 | 3 | 100% |
| 10 | Huber F, Koop G, Onorante L, Pfarrhofer M, and Schreiner J (2023) Nowcasting in a pandemic using non-parametric mixed frequency VARs | 0.843 | 3 | 3 | 100% |
Showing the top 10 of 74 scored citations.