Clustering a sample of major and emerging economies regarding their economic policy uncertainty

Francisco Venegas Martínez () and Ana Lorena Jimenez-Preciado
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Francisco Venegas Martínez: Instituto Politecnico Nacional. Mexico
Ana Lorena Jimenez-Preciado: Instituto Politecnico Nacional. Mexico
Authors registered in the RePEc Author Service: Francisco Venegas-Martínez

EconoQuantum, Revista de Economia y Finanzas, 2025, vol. 25, issue 1, 57-76

Abstract: Objective: this study carries out pattern identification in a sample of 16 major and emerging economies in function of their economic policy uncertainty. Methodology: this paper applies for the groping procedure K-Means, Agglomerative Hierarchical Clustering (AHC), and Clustering and Density-Based Spatial Clustering with Noise (DBSCAN). Data: This research uses the Economic Policy Uncertainty (EPU) Index calculated monthly by the EPU Agency for several countries. In particular, it examines EPU indexes for a sample 16 countries in five crisis periods between 2008 and 2024; the sample was chosen based on data availability. Results: global crises have created distinct country clusters transcending traditional economic groupings based on development status or geographical location. Notably, in the COVID-19 pandemic it generated an unprecedented global EPU homogeneity among countries. High-uncertainty clusters consistently emerge, often comprising large economies directly affected by crises. Limitations: there are possible biases in news-based com-ponent of EPU indices. Originality: to the best of the authors’ knowledge, multiple clustering techniques for various crisis periods have not been implemented before. Conclusion: global crises can equalize policy uncertainty, challenging conventional notions of economic resilience. The empirical findings emphasize the importance of considering EPU in a global context for those responsible for improving the design of economic policy.

Keywords: economic policy uncertainty; cluster analysis; K-means; DBSCAN; agglomerative hierarchical clustering. (search for similar items in EconPapers)
JEL-codes: C38 D80 F01 G01 (search for similar items in EconPapers)
Date: 2025
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