Will the real populists please stand up? A machine learning index of party populism

Andrea Celico, Martin Rode and Ignacio Rodriguez-Carreño

European Journal of Political Economy, 2024, vol. 82, issue C

Abstract: The existing literature on populism has seen numerous attempts to empirically quantify this somewhat ambiguous concept. Despite notable advances, continuous measures of populism with a clear theoretical background and a considerable coverage are still hard to come by. This paper proposes a novel approach to measuring party populism by combining several different expert-surveys via supervised machine learning techniques. Employing the random forest regression algorithm, we greatly expand the geographical and temporal coverage of two well-known populism indicators, which are based on the discursive and the ideational approach, respectively. The resulting multidimensional measures capture party-level populism on a continuous 0–10 scale, covering 1920 parties in 169 countries from 1970 to 2019. Our measures accurately replicate both definitions of populism, although the indicators may be more suitable for predicting populist outcomes in Western countries, as compared to non-Western ones.

Keywords: Populism; Political parties; Machine learning (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0176268024000314
Full text for ScienceDirect subscribers only

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:eee:poleco:v:82:y:2024:i:c:s0176268024000314

DOI: 10.1016/j.ejpoleco.2024.102529

Access Statistics for this article

European Journal of Political Economy is currently edited by J. De Haan, A. L. Hillman and H. W. Ursprung

More articles in European Journal of Political Economy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().