Education is the future. Education is the only way for a country to start developing and reducing poverty. In countries with medium incomes like Peru, the resources to spend on education is not unlimited. Therefore, it is necessary to have quality in investment. However, risks and uncertainty can make a project surpass its initial budget. Therefore, statistic based methods like Monte Carlo simulation is a powerful tool to forecast possible events that might endanger the profitability and sustainability of a project. Although there is not plenty of academic literature about Monte Carlo empirical usage, many projects employ this method to manage the possible risks the project could have. In consequence, the current research analyzed both risk and sensitivity of an elementary school building project. Both analyses showed that this project had huge probabilities to surpass the current profit and return estimations. However, the sensitivity analysis portrayed that the project could be endangered because of infrastructure overspending. Moreover, it indicated that students’ attendance is also a critical factor to ensure the sustainability of the project.

Road accidents are an essential issue for every country in the world because their consequences are devastating for the people involved in all senses. Speeding has been considered one of the main reasons for these tragedies. Therefore, the current research analyzed the relationship between speeding and severe accidents on the Pan-American highway in Peru. Publicly available data kept in a Peruvian official agency was employed. Methodologically, the logit regression was harnessed since the data were categorical. After the analysis, the research found that it was riskier to have severe accidents than speeding in urban areas crossing the highway and driving or being inside a truck.