---
title: Demand-Driven Inflation
url: https://www.ml-quant.com/papers/repec/nbr-nberwo-35980/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-11-14
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:nbr:nberwo:35980
source_url: https://econpapers.repec.org/RePEc:nbr:nberwo:35980
featured: 2026-11-13
citations: unknown
topic: Econometrics & Forecasting
---


# Demand-Driven Inflation

Structural VARs and a DSGE model establish that post-pandemic inflation in the US and Euro Area was predominantly driven by strong demand from fiscal expansion and accommodative policy.

- Source: https://econpapers.repec.org/RePEc:nbr:nberwo:35980
- Identifier: RePEc:nbr:nberwo:35980
- Released: 2026-11-09
- First featured: Quant Letter No. 139 (2026-11-13): https://www.ml-quant.com/issues/2026-11-13/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Econometrics & Forecasting
- Authors: Domenico Giannone, Giorgio Primiceri

## Related

- [The Federal Reserve’s Response to the Global Financial Crisis and Its Long-Term Impact: An Interrupted Time-Series Natural Experimental Analysis](https://www.ml-quant.com/papers/arxiv/2305.12318/): Quantitative easing positively affected US GDP but did not impact inflation.
- [Sector-Specific Household Inflation Uncertainty and Monetary Policy](https://www.ml-quant.com/papers/repec/awi-wpaper-0772/): The study links price dispersion in food and gasoline to household uncertainty and shows contractionary policy compresses this uncertainty, suggesting optimal policy should vary by sector.
- [Multivariate Economic Tail Risk and Scenario Analysis using the survey of Professional Forecasters](https://www.ml-quant.com/papers/repec/awi-wpaper-0771/): Incorporating professional forecasts into GARCH models improves predictions of joint tail risks for growth, inflation, and unemployment, enabling better scenario-based risk assessment.
- [Beyond the Numbers: Professional Forecasters’ Narratives About Inflation and Stock Market Performance](https://www.ml-quant.com/papers/repec/ces-ceswps-13076/): Professional forecasters hold heterogeneous narratives about inflation's impact on stocks, causing disagreement in expectations and divergent portfolio choices despite common signals.
- [Behind the curve: Reassessing inflation risks with a High-dimensional Distributional VAR (HiDVAR)](https://www.ml-quant.com/papers/repec/zbw-imfswp-344237/): 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.
- [Improving inflation forecasting by modeling expectation de-anchoring in low-inflation periods](https://www.ml-quant.com/papers/repec/zbw-imfswp-344239/): A model allowing expectations to shift to a low-inflation equilibrium cuts forecast errors roughly 50 percent versus central bank projections for euro area core inflation in the 2010s.