Clustering a Sample of Major and Emerging Economies in Function of their Economic Policy Uncertainty: K-means, Agglomerative Hierarchical Clustering and Density-Based Spatial Clustering with Noise

Autores/as

DOI:

https://doi.org/10.18381/eq.v22i1.7355

Palabras clave:

Incertidumbre de la política económica, análisis de agrupamiento, K-means, DBSCAN, agrupación jerárquica aglomerativa

Resumen

Objetivo: Este estudio lleva a cabo la identificación de patrones en una muestra de 16 economías desarrolladas y emergentes en función de la incertidumbre de su política económica. Metodología: Este artículo para el procedimiento de agrupación aplica K-Medias, agrupación jerárquica por aglomerados (AHC) y agrupación espacial basada en densidad con ruido (DBSCAN). Datos: Esta investigación utiliza el Índice de Incertidumbre de Política Económica (EPU) calculado mensualmente por la Agencia EPU para varios países. En particular, se examinan los índices EPU para una muestra de 16 países en cinco períodos de crisis entre 2008 y 2024; la muestra se eligió en función de la disponibilidad de datos. Resultados: Las crisis globales han creado distintos grupos de países que trascienden las agrupaciones económicas tradicionales basadas en el nivel de desarrollo o en la ubicación geográfica. Cabe destacar que en la pandemia de COVID-19 se generó una homogeneidad global sin precedente de EPU entre países. De manera constante, surgen grupos de alta incertidumbre, que a menudo comprenden grandes economías directamente afectadas por las crisis. Limitaciones: Puede haber posibles sesgos en el componente de las noticias en periódicos de los índices EPU. Originalidad: Hasta donde saben los autores, no se han aplicado múltiples técnicas de agrupamiento para varios períodos de crisis anteriormente. Conclusión: Las crisis globales pueden igualar la incertidumbre política, desafiando las nociones convencionales de resiliencia económica. Los hallazgos empíricos enfatizan la importancia de considerar la EPU en un contexto global para un mejor diseño de la política económica.

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Publicado

2024-12-17

Cómo citar

Venegas Martínez, F., & Jiménez-Preciado, A. L. (2024). Clustering a Sample of Major and Emerging Economies in Function of their Economic Policy Uncertainty: K-means, Agglomerative Hierarchical Clustering and Density-Based Spatial Clustering with Noise . EconoQuantum, 22(1), 57–76. https://doi.org/10.18381/eq.v22i1.7355

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