Unofficial guidance on various topics by the AEA Data Editor
These web pages provide unofficial and developing guidance on the implementation of the American Economic Association (AEA)’s Data and Code Availability Policy. We also provide links to generic guidance being developed by a loose collective (“guild”) of data editors and people in a similar role at various social science journals.
Order in which AEA authors should read these resources
- Start with the official Data and Code Availability Policy
- Look for general guidance at the Social Science Data Editors pages
- Read the AEA’s FAQ
- The Unofficial AEA Data and Code Guidance provides guidance specific to the AEA
- Have a look at the draft FAQ on this site for thorny issues
Comments are welcome, please file them as issues in our Github repo.
Guidance on creating replicable data and program archives
How should researchers create replicable data and program archives? How should such archives be structured, how documented, and where should they be located?
Guidance on data citation
Data citation is critical for documenting data provenance, and the AEA requires data citations. But data citations can also be hard.
- General guidance can be found on the Social Science Data Editor’s page on the topic
- Some particularly thorny issues can be found [on this website](https://social-science-data-editors.github.io/guidance/addtl-data-citation-guidance.html.
Guidance on depositing in the AEA Data and Code Repository
The AEA migrated to a new data and code repository in July 2019. See
Guidance on testing replicability of code
The code and data that have been archived should be reproducible and replicable. How do we test that?
- Generic guidance is provided at the Social Science Data Editors’ Guidance website.
- At the AEA,
- we use this template to guide our replicators.
- We assess
- software availability
- data availability
- code availability and clarity
- needed computational resources
- time needed to acquire or use all of the above, and conduct the reproducibility check
- When some of the conditions are not met with our own resources, we may ask others to conduct a reproducibility exercise for us.
- Our PROTOCOL is outlined here.
- Sample report 1
- We may ask others to do so because
- They are experts
- They have access to the software
- They have access to the data
- They have access to computational resources needed
- No reproducibility check is discarded out of hand
Frequently Asked Questions