Programa del congreso

— Gross Domestic Product or GDP is still considered to be the known go-to yardstick for determining how the economy of a country is doing, and that is still accountable for the economy of Honduras as well. Yet the country has only seen a handful of data-driven econometric studies, which limits the congress’ ability to rely on hard evidence when crafting their future economic plans. With that gap in mind, this project uses two different econometric techniques: a log-log model run through Ordinary Least Squares (OLS) and a Vector Autoregression (VAR) approach-to tease insights from the numbers. It pulls together yearly data from 2000 to 2023, looking at the different macroeconomic variables such as private and public spending, gross fixed investment, exports, imports, foreign direct investment, and the remittances that so many families and households depend on. Standard checks such as the Augmented Dickey-Fuller or ADF unit root test, Granger causality, lag length selection, inverse root stability, and a battery of residual diagnostics-were all run to make sure the results were trustworthy and stable. These tests show that GDP moves tightly with both domestic and international drivers, backing up the models forecast power.

This study evaluates, from a cost and entrepreneurial opportunity perspective, the viability of maintaining a university cluster composed of ten HP ProDesk 600 G1 nodes (40 cores, 60 GB RAM) versus contracting equivalent capacity on Amazon EC2 (C6i.2xlarge instances). A detailed total cost of ownership (TCO) model was developed, incorporating capital investment, maintenance, electricity (USD 0.22/kWh), internet connectivity (200 Mbps), and cloud tariffs under both On-Demand and three-year Savings Plan modalities. At 30% utilization, the local cluster achieves a unit cost of USD 0.025/core-hour, while EC2 ranges from USD 0.048 to 0.105/core-hour. Sensitivity curves indicate that the cloud only becomes cost-effective when utilization exceeds 65% or electricity surpasses USD 0.45/kWh. The analysis further explores implications for deep-tech startups, university spin-offs, and incubator programs: while the cloud provides elasticity and access to advanced hardware, it may erode early-stage margins. The study proposes a reproducible decision-making framework tailored to emerging innovation ecosystems in Latin America, highlighting the strategic value of hybrid infrastructures for balancing cost, flexibility, and regional value retention.

Credit card default represents a critical challenge for Peruvian banking due to its direct impact on the profitability and sustainability of financial institutions. In this context, this study aimed to develop an explainable machine learning-based predictive model to anticipate credit default risk using financial data obtained through web scraping from official portals of institutions such as BBVA, BCP, Interbank, and Scotiabank.
The methodology involved the automated collection of monthly interest rate data by credit type and the processing of key credit variables, including credit line utilization, payment history, monthly income, and card usage frequency. Several machine learning models were trained and evaluated, with LightGBM outperforming the others by achieving an accuracy of 89.4%, a recall of 86.7%, and an area under the ROC curve of 0.94.
To ensure model interpretability, SHAP (SHapley Additive exPlanations) was applied, identifying high credit usage and accumulated delinquency as the most impactful predictors. The findings suggest that the integration of explainable models can significantly enhance decision-making in credit risk management. Their adoption is recommended as a strategic support tool for real-time financial profile evaluation

Among the young population of Metropolitan Lima, there is a clear tendency to prioritize savings over investment. One possible cause of this predominance is their low tolerance for risk, which leads them to avoid investment decisions. Over time, Peru has improved in terms of financial literacy, as indicated by the results of the Organization for Economic Cooperation and Development (OECD) tests; however, these efforts have not been sufficient to modify this behavior in the younger generations. Therefore, the present research aimed to determine the existence of a relationship between financial literacy and risk tolerance in the Lima population aged 18 to 39, an objective that was successfully achieved by proving a direct relationship between both variables.

Musculoskeletal symptoms in coffee producers in Honduras are caused by uncomfortable postures, repetitive movements, long working hours on sloping terrain, and limited training in ergonomics. This study evaluated the perception of ergonomic risks and the adoption of preventive measures through a literature review and a survey of 41 workers from small and medium-sized farms. Data were collected on age, experience, education, and common symptoms such as lower back pain (26.8%), wrist pain, and shoulder pain. Sixty-six percent work on steep slopes, only 17.1% take frequent breaks, and 14.6% never do. Young people under the age of 25 adjust their posture less frequently than those over 55. Although workers are aware of the risks, ergonomics remains underdeveloped in the sector. Ninety-seven percent have not completed secondary education, which limits access to preventive training. It is recommended to design age-appropriate educational programs, implement mandatory breaks, promote good ergonomic practices, and offer monthly training sessions. These measures could reduce injuries and improve well-being in coffee farming work.

This study examines the implementation of the Ideation-Creation-Implementation (ICI) methodology in the Generation of Enterprises I and II courses at UNITEC, Honduras, aimed at enhancing entrepreneurial competencies among university students. Employing a mixed-methods approach, the research combined qualitative analysis of focus groups with a comprehensive literature review on entrepreneurial education and active methodologies such as Design Thinking and Lean Startup. The sample included nine students from diverse academic backgrounds who participated in the pilot experience from October 2024 to March 2025. Results indicate that the ICI methodology fosters practical, interdisciplinary learning focused on solving real-world problems, developing skills such as teamwork, empathy, critical thinking, and digital tool utilization. Challenges identified include technical limitations in digital prototyping, group coordination issues, and lack of continuity between courses. Participants especially valued early idea validation and feedback during exhibition events, which helped refine their projects. Recommendations include expanding technical workshops, improving infrastructure, and integrating curricular content to support a more comprehensive learning experience. This study provides evidence of the ICI methodology’s effectiveness as an innovative educational strategy to strengthen entrepreneurial training in structurally limited contexts, contributing to sustainable social and economic development in Honduras.