How much is too much inflation? Classifying inflationary regimes

Manuel de Mier and Fernando Delbianco

EconomiA, 2025, vol. 26, issue 3, 335-357

Abstract: PurposeExisting classifications of inflationary regimes often rely on subjective judgments, hindering objectivity and accuracy. This study proposes a novel, data-driven approach to address this limitation.Design/methodology/approachWe combine unsupervised clustering and classification tree methods to analyze Argentine inflation data from 1943 to 2022. Two smoothing techniques are introduced: a measure of temporal contiguity and a rolling majority rule method. The resulting regimes are compared to existing classifications based on their explanatory power for inflation-relative price variability.FindingsOur method identifies distinct inflationary regimes, demonstrating significant improvement in objectivity and accuracy compared to existing literature. The regimes capture key historical periods and exhibit a strong association with inflation-relative price variability, providing valuable insights into Argentine inflation dynamics.Originality/valueThis study offers a novel methodological framework for constructing objective and accurate inflationary regimes, free from subjective biases. This approach holds potential for application to other contexts and contributes to a more nuanced understanding of inflation dynamics.

Keywords: Inflation; Periodization; Clustering; Classification trees (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.emerald.com/econ/article/26/3/335/1249 ... nflation-Classifying (text/html)
https://www.emerald.com/econ/article-pdf/26/3/335/ ... n-02-2024-0025en.pdf (application/pdf)

Related works:
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:eme:econpp:econ-02-2024-0025

DOI: 10.1108/ECON-02-2024-0025

Access Statistics for this article

EconomiA is currently edited by Professor Joaquim Andrade

More articles in EconomiA from Emerald Group Publishing Limited
Bibliographic data for series maintained by Emerald Support ().