Enrolment in higher education has risen dramatically in Latin America, especially in Chile. Yet graduation and persistence rates remain low. One way to improve graduation and persistence is to use data and analytics to identify students at risk of dropout, target interventions, and evaluate interventions’ effectiveness at improving student success. We illustrate the potential of this approach using data from eight Chilean universities. Results show that data available at matriculation are only weakly predictive of persistence, while prediction improves dramatically once data on university grades become available. Some predictors of persistence are under policy control. Financial aid predicts higher persistence, and being denied a first-choice major predicts lower persistence. Student success programmes are ineffective at some universities; they are more effective at others, but when effective they often fail to target the highest risk students. Universities should use data regularly and systematically to identify high-risk students, target them with interventions, and evaluate those interventions’ effectiveness.

Current methods to estimate evacuation time during a natural disaster do not consider the socioeconomic and demographic characteristics of the population. This article develops the Response Time by Social Vulnerability Index (ReTSVI). ReTSVI combines a series of modules that are pieces of information that interact during an evacuation, such as evacuation rate curves, mobilization, inundation models, and social vulnerability indexes, to create an integrated map of the evacuation rate in a given location. We provide an example of the application of ReTSVI in a potential case of a severe flood event in Huaraz, Peru. The results show that during the first 5 min of the evacuation, the population that lives in neighborhoods with a high social vulnerability evacuates 15 % and 22 % fewer people than the blocks with medium and low social vulnerability. These differences gradually decrease over time after the evacuation warning, and social vulnerability becomes less relevant after 30 min. The results of the application example have no statistical significance, which should be considered in a real case of application. Using a methodology such as ReTSVI could make it possible to combine social and physical vulnerability in a qualitative framework for evacuation, although more research is needed to understand the socioeconomic variables that explain the differences in evacuation rate.

Chile has embraced the expansion of monoculture forest plantations of exotic Monterey pine and eucalyptus as part of its development strategy. While forestry is considered financially successful and meets sustainability objectives, the increase in forest plantations across southern Chile has received harsh critiques for exacerbating conflict over Indigenous land rights, producing negative environmental outcomes, and increasing poverty and inequality. There are also claims that forest plantation expansion has led to an abandonment of the countryside. Migration is viewed as a result of the socioeconomic challenges that forest plantations produce at the local level; however, the linkages have not been explored. We examine the linkages between forest plantations and migration through two questions: Is there a relationship between forest plantation cover change and out-migration from rural areas? If so, what are the factors that explain this process? We use a difference-in-differences method analyzing panel data from the Chilean census and from CONAF, the Chilean National Forest Corporation, complemented by interviews, mapping workshops, and focus groups to answer these questions. Results indicate a statistically significant relationship between expanding forest plantations and population decline in rural areas. Qualitative data show that this expansion led to displacement of residents, declines in employment opportunities, and agriculture difficulties.

Debates in education policy draw on different theories about how to raise children’s achievement. The school competition theory holds that achievement rises when students can choose among competing schools. The school resources theory holds that achievement rises with schools’ resources per student. The family resources theory holds that achievement rises as parents become more educated and earn higher incomes. We test all three theories in Chile between 2002 and 2013, when reading and math scores rose by 0.2 to 0.3 standard deviations, as school competition, school resources, and family resources all increased. We compare Chilean municipalities in a difference-in-differences analysis, asking whether test scores rose fastest in municipalities with greater increases in school competition, school resources, or family resources. We find that municipal test scores did not rise with school competition but did rise with family resources (parental education, not income) and, to a smaller extent, with school resources (as measured by class sizes). Results favor the family resource theory, and to a lesser extent the school resource theory, but not the school competition theory.