Summer Internship with the AEA Data Editor

Together with collaborating institutions Wellesley College, Haverford College, University of Notre Dame, University of Colorado Boulder, and Hamilton College, I expand beyond the Cornell students who participate in the LDI Replication Lab. The internship is a 10-12 week, part-time (20 hours per week) paid position, and focuses on verifying the reproducibility of manuscripts submitted to the American Economic Association’s journals.

Interns do not apply independently at this time; rather they are recruited through the collaborating institutions. Previous rounds have been held in 2024 and 2025.

Description

Goal: Ensure that supplementary materials for articles in a journal with a replication policy are (a) accessible (b) reproduce the intended results, (c) document results and findings.

Work description:

The American Economic Association (AEA) monitors compliance with its Data and Code Availability Policy, under the leadership of the AEA Data Editor. LDI Replication Lab members will access pre-publication materials provided by authors, and assess how well these materials reproduce the results published in the manuscript or article. The provided materials and instructions will be assessed using a checklist. Authors’ instructions will be followed (if possible), and success or failure to (i) perform the analysis (ii) replicate the authors’ results will be documented. Other related activities, such as literature search or tabulation of results, may also be assigned. Team work is encouraged, and activity will be supervised by graduate student or faculty member. Team members must be at ease working in various computer environments (Windows Remote Desktop, local laptops) and software tools (statistical software, Git).

Examples of replication packages in economics can be found at the AEA Data and Code Repository.

What interns will learn:

Interns will learn and observe parts of the scientific publication process. They will learn and practice the details of the process of reproducibility checking, and will experience the challenges of ensuring that data and code are available and functional. At the end of their internship, they will have run and learned to debug code for multiple papers (typically around 5-6), reviewed output, prepared reports which will be read by senior economists throughout the world (after review by the Data Editor). They may encounter and learn about novel software and data sources, as well as how to run code on multiple platforms, including powerful Windows and Linux servers.

While the internship is new, the LDI Lab has been training undergraduate replicators for the past 6 years, and has employed more than 200 students. Students report that the experience is valuable in their future careers, including in the private sector, government, and as graduate students in academia.

Internship experience:

While interns will be working remotely, they will be part of a team of interns and regular (undergraduate) staff in the LDI Replication Lab, meeting at least twice a week. They will be mentored by academic staff at their own institution as well. They will have the opportunity to interact with other interns and staff, and to learn from each other. They will also have the opportunity to interact regularly with the AEA Data Editor and his staff.

Required Qualifications/Skills/Experience:

Some experience with empirical social science data analysis using statistical software is required. Knowledge of at least one of Stata, Matlab, R or SAS is required, as is familiarity with the Windows Desktop environment. Experience with Git and the command line (Linux, Mac, or Powershell) are assets. Applicants must be current students at a participating institution, residing in the United States.

Start and end dates:

The internship will broadly start after institution-specific final exams are over, and thus vary, but broadly, the internship will take place between mid-May and mid-August, for 10-12 weeks (depends on the institution).

Requirements:

Training is required as a condition of hiring. While employed, attendance (via Zoom) at two weekly meetings is required. Training takes place on an April weekend at one of the collaborating institutions (Wellesley for the 2024-2026 cycles), and on several subsequent days

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We describe a unique environment in which undergraduate students from various STEM and social science disciplines are trained in data provenance and reproducible methods, and then apply that knowledge to real, conditionally accepted manuscripts and associated replication packages. We describe in detail the recruitment, training, and regular activities. While the activity is not part of a regular curriculum, the skills and knowledge taught through explicit training of reproducible methods and principles, and reinforced through repeated application in a real-life workflow, contribute to the education of these undergraduate students, and prepare them for post-graduation jobs and further studies.

Description

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