My doctoral research focuses on complex learning, with a focus on human capital investment (read education) of young people. I use diverse econometric, algorithmic and experimental methods to analyse how students interact with themselves, systems and technology, and the economic implications of such actions. I am especially interested in the confluence of students’ peer networks, technological innovations and non-cognitive skills, and the study of these in resource-scarce settings, i.e. Low and Middle-Income Countries. Some of the applied work that I do happens in Mexico, my home country.
In collaboration with the International Labour Organisation, we revised and proposed a new framework with which to understand young people’s aspirations as determinants of their future economic outcomes, and complements to succesful employment policies. The paper, Youth aspirations and the future of work was jointly written with Drew Gardiner and Micheline Goedhuys.
In related work, I design a video-intervention to affect aspirations of high school students in Mexico. The Randomised Controlled Trial was carried out during the 2018-2019 school year, with 45 participating schools from the Midwestern region of Mexico. We show that low-cost technological interventions, paired with a social network-driven approach, are effective policy tools to decrease information asymmetries and optimise student-decision making, through their aspirations.
I am also interested in ethics, equity and redistribution. With Chinasa T. Okolo and Juba Ziani, we design an ethics and empathy driven approach to evaluate the use of Artificial Intelligence on patients in healthcare settings. The paper ACIPS: A Framework for Evaluating Patient Perception in the Introduction of AI-Enabled Healthcare is available at Arxiv. With Stefania Merone, Edwin Lock, and Simon Finster, we are currently working on understanding how exposure to self-interest & altruistic narratives and peer behaviour affects reource-rich country citizens’ willingness to donate to resource-poor countries, within the context of the COVID-19 pandemic and the Russo-Ukrainian war. You can find the pre-analysis plan for the first of two experiments online.
More recently, Edwin Lock, Simon Finster, Francisco Marmolejo-Cossío and I developed an algorithmic mechanism to safely reopen educational institutions during a pandemic and mitigate learning losses. You can visit the web application for the COVID-19 Safe Education Framework for more details on the project. Alternatively, you can download the pre-analysis plan for the RCT, or visit the GitHub for the open source code for the web application. With Ariel Procaccia, Evi Micha, Francisco Marmolejo, Edwin Lock, and Simon Finster, we have worked on a more generalised institutional reopening approach within the context of a pandemic. The paper Welfare-Maximizing Pooled Testing is available at Ariel’s website.