Causality clubs: grouping countries with cluster causality detection

Manuel de Mier (), Fernando Delbianco () and Fernando Tohmé

International Journal of Computational Economics and Econometrics, 2025, vol. 15, issue 3, 294-312

Abstract: This paper explores the heterogeneity of causal structures of economic growth among countries by proposing a two-step procedure. First, we apply a causal discovery technique to uncover the underlying causal structure for each country. Second, we employ hierarchical clustering over these estimates to identify groups of similar countries in terms of their causal relationships. We obtain five 'causality clubs', each one associated with a different structure of causal determinations of the growth process. We find that the usual associations between income or geographical location and the nature of economic growth processes may not always hold true.

Keywords: causality clubs; cluster causality detection; causal structure; heterogeneity; economic growth. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=147779 (text/html)
Access to full text is restricted to subscribers.

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:ids:ijcome:v:15:y:2025:i:3:p:294-312

Access Statistics for this article

More articles in International Journal of Computational Economics and Econometrics from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().