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Predictive Determinants of Migratory Intention in Honduras: Modeling by Logistic Regression and INE 2023 data. (#2322)

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Date of Conference

July 15-17, 2026

Published In

"Engineering without Borders: Artificial Intelligence, Knowledge, Innovation, and Alliances for a Future from the Americas"

Location of Conference

Santiago (Chile)

Authors

Martinez Avila, Jordan Steve

Cacho Arzu, Marvin Antonio

Rodríguez Rivera, Jesús Ricardo

Abstract

Summary - The migration of Hondurans to the United States is a complex phenomenon driven by economic, social, and security factors. This study analyzes the determinants of migratory intent using a sample of data from 7,616 households from the 2023 Permanent Survey of Multipurpose Households (EPHPM), integrated with the complementary migration and remittances module, selected from more than 42,000 valid records after applying inclusion criteria, such as the elimination of incomplete observations and the selection of households with migration projection to the United States. A logistic regression model was trained to evaluate the influence of sociodemographic variables, income levels, perception of insecurity, and family ties abroad. The SMOTE technique was applied to address the imbalance of the dependent variable. The results show that having relatives abroad is the strongest predictor (Odds Ratio ≈ 2.08), even surpassing perceived insecurity. Economic precariousness also increases the intention to migrate, but transnational links structure and facilitate mobility, reducing associated risks and costs. The study shows that the decision to migrate is multicausal, the result of the interaction between economic, social and family conditions, and provides relevant empirical inputs for the design of public policies aimed at addressing its structural causes and generating local opportunities.

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