---
title: Behind the curve: Reassessing inflation risks with a High-dimensional Distributional VAR (HiDVAR)
url: https://www.ml-quant.com/papers/repec/zbw-imfswp-344237/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-11-06
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:zbw:imfswp:344237
source_url: https://econpapers.repec.org/RePEc:zbw:imfswp:344237
featured: 2026-11-06
citations: unknown
topic: Econometrics & Forecasting
---


# Behind the curve: Reassessing inflation risks with a High-dimensional Distributional VAR (HiDVAR)

HiDVAR, a data-rich distributional framework, improves inflation tail-risk assessment by 28% in CRPS relative to standard benchmarks and performs well in real-time evaluation.

- Source: https://econpapers.repec.org/RePEc:zbw:imfswp:344237
- Identifier: RePEc:zbw:imfswp:344237
- Released: 2026-11-02
- First featured: Quant Letter No. 138 (2026-11-06): https://www.ml-quant.com/issues/2026-11-06/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Econometrics & Forecasting
- Authors: Schmitz, Luca

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