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on Central and South America |
| By: | Eduardo Levy Yeyati; Virginia Robano; Emiliano Pereiro; Camila Porto; Víctor Koleszar |
| Abstract: | Generative Artificial Intelligence (AI) has the potential to help educators tackle persistent challenges—such as complex problem-solving and personalized mentoring—while preserving the essential human elements of judgment and empathy. Focusing on Latin American classrooms, this study explores how AI-powered chatbots can complement teachers in elementary and secondary education. Drawing on quantitative and qualitative evidence, we identify strategies to minimize gender gaps, strengthen teacher preparedness, and maximize student engagement. The study proposes actionable policies, including targeted teacher training, gender-inclusive AI adoption strategies, and scalable hybrid teaching models, as well as a blueprint for testing chatbot effectiveness. By incorporating a gender lens and a phased AI adoption strategy, our study not only outlines best practices for AI deployment but also offers empirical insights into how chatbots impact learning engagement, teacher preparedness, and student equity. Our framework serves as a guide for policymakers aiming to integrate AI tools in a way that supports—not replaces—educators while addressing disparities in access and usage. |
| Keywords: | artificial intelligence, education, ChatGPT, complementarity, LLM, automated tutor, chatbot, classroom, teaching |
| JEL: | C9 I21 J24 O33 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:udt:wpgobi:pp_gob_2025_35 |
| By: | Samuel Berlinski (Inter-American Development Bank); Michele Giannola (University of Naples Federico II, CSEF and the Institute for Fiscal Studies); Alessandro Toppeta (SOFI, Stockholm University) |
| Abstract: | We study the relative effectiveness, cost-effectiveness, and interaction of family-and school-based learning interventions using a randomized controlled trial in Colombia that assigns children to a parental engagement program, a teacher professional development program, both, or a control group. Both interventions are grounded in a child-centered learning approach that emphasizes active engagement and the progression from informal to formal mathematical understanding. Each intervention independently generates sizable and statistically similar gains in early numeracy (0.17‡and 0.20‡). Combining them produces noadditional learning gains, suggesting that the two interventions act as substitutes over thetime horizon and skill domain we study. When benefits accruing to future cohorts are takeninto account, the teacher development program becomes at least as cost-effective as, andpotentially more cost-effective than, the parental engagement intervention. Our results sug-gest that, in this setting, strategically concentrating resources on a single binding constraint– either at home or in school – maximizes the short-run learning gains per dollar spent. |
| Keywords: | numeracy, childhood development, teacher development, parental engagement, randomized control trial, Colombia |
| JEL: | I21 I25 O15 J13 C93 |
| Date: | 2026–05–05 |
| URL: | https://d.repec.org/n?u=RePEc:sef:csefwp:781 |
| By: | Eduardo Levy Yeyati |
| Abstract: | Artificial intelligence (AI) is increasingly shaping economic structures, governance, and global power dynamics. Yet existing AI readiness indexes often provide a distorted view of countries’ capabilities—rewarding formal strategies and patents while overlooking deployment-first innovations, informal economies, and adaptive governance capacities. These biases particularly disadvantage Latin America and the Caribbean (LAC). This paper makes two contributions to the AI readiness agenda. First, it empirically documents the divergence and conceptual inconsistencies across leading AI readiness and preparedness indexes. Second, it proposes a two-tier measurement framework: a Composite Readiness–Preparedness Index (CoRPI), providing a transparent baseline diagnostic, and an Adaptive AI Readiness Index (AARI), capturing context-specific capacities and policy learning. Together, these frameworks aim to balance comparability with relevance. By piloting the AARI in LAC, the region can serve as a testbed for a model of AI governance and measurement with global applicability. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:udt:wpgobi:wp_gob_2025_2 |
| By: | Martínez, Claudia; Perticará, Marcela; Puentes, Esteban; Vásquez, Javier |
| Abstract: | This paper studies how disability onset and subsequent administrative registration affect labor market trajectories in Chile, a middle-income country with a large informal sector. Using panel survey data linked to administrative records, we estimate dynamic employment and earnings effects around disability events. Disability onset generates sharp and persistent losses: Full-year employment falls by about 11 percentage points at onset and by 20 to 25 percentage points within six years, while formal wages decline by approximately 6% initially and by more than 30% five years later. Among those who remain employed, the probability of working informally rises over time while formal employment probability falls, indicating adjustment along the margin of employment quality. Registration is clearly endogenous: Individuals who certify display preexisting employment deterioration, which prevents a causal interpretation of the effects of registration. |
| Keywords: | Disability |
| JEL: | J14 J21 J24 |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:idb:brikps:14575 |