Density forecasts of inflation: a quantile regression forest approach

Prévisions de densité de l'inflation: une approche par forêt de régressions quantile

Michele Lenza, Inès Moutachaker and Joan Paredes ()
Additional contact information
Michele Lenza: European Central Bank, CEPR - Center for Economic Policy Research
Inès Moutachaker: INSEE - Institut national de la statistique et des études économiques (INSEE)

Working Papers from HAL

Abstract: Density forecasts of inflation are a fundamental input for medium-term oriented forecasters, such as National Statistic Institutes or Central Banks. We show that a quantile regression forest, capturing a general non-linear relationship between euro area (headline and core) inflation and a large set of determinants, is competitive with state-of-the-art linear benchmarks and judgemental survey forecasts. The median forecasts of the quantile regression forest are very close to the ECB point inflation forecasts, displaying similar deviations from "linearity". Given that the ECB modelling toolbox is essentially linear, this finding suggests that the expert judgement embedded in the ECB forecast may be characterized by some mild non-linearity

Keywords: Inflation; Non-linearity; Quantile Regression Forest; non-linéarité; forêt de régression quantile (search for similar items in EconPapers)
Date: 2024-06-14
Note: View the original document on HAL open archive server: https://insee.hal.science/hal-05329662v1
References: Add references at CitEc
Citations:

Downloads: (external link)
https://insee.hal.science/hal-05329662v1/document (application/pdf)

Related works:
Journal Article: Density forecasts of inflation: A quantile regression forest approach (2025)
Working Paper: Density forecasts of inflation: a quantile regression forest approach (2023)
Working Paper: Density forecasts of inflation: a quantile regression forest approach (2023)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:hal-05329662

Access Statistics for this paper

More papers in Working Papers from HAL
Bibliographic data for series maintained by CCSD ().