Classification of Latin American and Caribbean Countries Based on Multidimensional Development Indicators: A Multivariate Empirical Analysis

Adel Mendoza-Mendoza (), Delimiro Visbal-Cadavid and Enrique De La Hoz-Domínguez
Additional contact information
Adel Mendoza-Mendoza: Industrial Engineering Program, Faculty of Engineering, Universidad del Atlántico, Barranquilla 080001, Colombia
Delimiro Visbal-Cadavid: Industrial Engineering Program, Faculty of Engineering, Universidad del Magdalena, Santa Marta 470004, Colombia
Enrique De La Hoz-Domínguez: Statistical and Quantitative Methods Research Group (GEMC), Universidad del Magdalena, Santa Marta 470004, Colombia

Economies, 2025, vol. 13, issue 6, 1-21

Abstract: This study develops a multidimensional classification of Latin American and Caribbean countries based on a multidimensional set of economic, social, technological, and environmental indicators. This study develops a multidimensional assessment of the performance of Latin American and Caribbean countries, taking into account the following indicators for the period 2017–2022: education expenditure (% of GDP), health expenditure (% of GDP), GDP per capita (constant USD), CO 2 emissions per capita (metric tons), energy consumption per capita (kWh), internet users (% of population), mobile phone subscriptions (per 100 inhabitants), and the Global Innovation Index (GII). Initially, through the application of principal component analysis (PCA), the objective was to reduce the complexity of the data set and reveal the main structural dimensions. Subsequently, cluster analysis was used to classify countries according to shared development patterns. To achieve this, the average of the indicators for the 2017–2022 period was used as a basis, which enabled the reduction in short-term distortions and the capture of structural trends. The results reveal the existence of distinct groups, with countries with higher levels of digital connectivity, investment in human capital, and economic dynamism experiencing more favorable development conditions.

Keywords: principal component analysis (PCA); cluster analysis; multidimensional assessment; socioeconomic indicators (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7099/13/6/178/pdf (application/pdf)
https://www.mdpi.com/2227-7099/13/6/178/ (text/html)

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:gam:jecomi:v:13:y:2025:i:6:p:178-:d:1680922

Access Statistics for this article

Economies is currently edited by Ms. Hongyan Zhang

More articles in Economies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().