Multivariate analysis of homicide and intentional crime rates in South America: An application of the HJ biplot

Abstract

This study aims to analyze the rates of homicide and other intentional crimes in various South American countries using the HJ Biplot multivariate analysis technique. The goal is to identify regional crime patterns and examine correlations with socioeconomic factors such as poverty, inequality, and unemployment. The research is a quantitative, descriptive, and exploratory study using data from the United Nations Data Portal for the year 2020. It employs the HJ Biplot to jointly represent variables and countries in a two-dimensional space, allowing for the visualization of crime patterns and identifying clusters of countries with similar crime profiles. The HJ Biplot reveals three clusters of South American countries based on crime characteristics. Countries like Brazil, Venezuela, and Colombia are associated with high homicide rates, while Ecuador, Peru, and Chile face higher rates of sexual violence and kidnapping. Socioeconomic factors such as economic inequality and lack of job opportunities are strongly correlated with higher crime rates in these regions. The study confirms that socioeconomic disparities contribute significantly to crime in South America, with specific countries displaying unique crime patterns that align with their social and economic contexts. These findings suggest that tailored public policies focusing on social inclusion and crime prevention are needed to address the distinct crime challenges in each country. Policymakers in South America should consider implementing targeted strategies that address the underlying socioeconomic causes of crime, such as promoting education and employment opportunities. Strengthening public security institutions and focusing on community-specific crime prevention efforts could reduce violence and improve safety in the region.