About Me

I am a PhD Candidate in Economics in a joint program between KU Leuven (at the Leuven Economics of Education Research center) and Pontificia Universidad Javeriana.

Status: I will defend my dissertation on March 12, 2026. I am currently available for positions starting immediately or in Fall 2026.

I am fortunate to be advised by Professor Gloria Bernal and Professor Kristof De Witte.

Jaime Polanco-Jimenez

My research lies at the intersection of Development Economics and the Economics of Education, with a focus on Artificial Intelligence. I combine causal inference with data science to study how frontier technologies can improve human capital accumulation in developing contexts.

Job Market Paper

The Tailoring Premium: How AI Design Unlocks Student Engagement and Learning

As schools increasingly adopt Artificial Intelligence, policymakers face a crucial trade-off between deploying inexpensive, general-purpose models and investing in tools tailored to the curriculum. We provide the first large-scale causal evidence on this choice. In a randomized control trial with 2,440 secondary students, we find that offering a curriculum-tailored chatbot increases immediate learning by 0.126 standard deviations (ITT), while a generic chatbot has no effect. This difference is driven entirely by student engagement: the tailored tool increased module completion by 15.5 percentage points. For students induced to complete the module by the tailored design, the effect is larger and more durable, increasing long-term knowledge retention by 0.23 standard deviations. Our results show that the learning gains from educational AI are unlocked by deep curricular integration, which succeeds by first solving the fundamental problem of student engagement.

View Paper (PDF)

Work in Progress: AI & Research Productivity

My research agenda extends beyond the classroom to academic production itself. I am currently running a new Randomized Controlled Trial (RCT) evaluating how AI tools affect the productivity and well-being of researchers.

Evaluating an AI-Powered Research Development Tool

Polanco-Jimenez, Jaime and Almudena Sevilla. 2026. AEA RCT Registry (17749-1.0).

This RCT evaluates the causal impact of an AI-powered Research Development Tool on the academic productivity and well-being of researchers. Participants, primarily PhD students and junior female economists, will be randomly assigned to one of two groups: a control group receiving feedback from a general-purpose AI, or a treatment group gaining access to a comprehensive AI-driven "Research Development Suite." This suite offers detailed, structured feedback on research papers and integrated workflow features. Over a 24-month intervention period, we will measure changes in objective productivity metrics (e.g., papers submitted/published, co-author networks) and subjective well-being (e.g., job satisfaction, work-life balance).

Interactive Demo: The Treatment Tool

Below is a demonstration of the Referee AI agent used in the treatment arm of the study. It simulates the rigorous peer review process of a top-tier economics journal.

Access Required: To test the tool or discuss the experimental design, please contact me at jaime.polancojimenez@kuleuven.be.

Research Interests

  • AI-Powered Learning Support: Investigating how AI can mitigate teacher shortages and enhance student learning outcomes.
  • Gender Dynamics: Analyzing the impact of gender ratios and peer effects in educational and professional settings.
  • Infrastructure & Resources: Evaluating the effectiveness of infrastructure improvements and natural resource allocation on human capital.