Advancing Computational Reproducibility in Economics (ACRE)
Replication, robustness checks, and extension of published work are possible only to the extent that published findings are computationally reproducible. In other words, one must be able to reproduce tables and figures within a reasonable margin of error using the available data, code, and materials. In an effort to improve the computational reproducibility in economics, in 2019 the American Economic Association updated its Data and Code Availability Policy to mandate pre-publication verification of computational reproducibility by the AEA Data Editor.
In collaboration with AEA Data Editor Lars Vilhuber, BITSS launched the Advancing Computational Reproducibility in Economics (ACRE) initiative, which features two major components:
- Capacity-building for economics researchers to support compliance with journal policies that mandate pre-publication verification of computational reproducibility, including:
- Training events for participants of major association meetings in economics (e.g. Allied Social Sciences Association, the Association for Public Policy Analysis and Management). Learn about upcoming ACRE training events here.
- Guidance resources for improved workflow reproducibility for AEA authors.
- An online platform to facilitate the systematic sourcing, cataloging, and review of attempts to verify and improve the computational reproducibility of published work in economics. Its development will also include:
- Adaptable curricula and guidance for the conduct and reporting of verifications performed in graduate-level economics courses. Interested in using our teaching materials as part of your class? Get in touch!
- Criteria for assessing computational reproducibility and a standardized taxonomy of the reproduction process; and
- Measures of the computational reproducibility of economics sub-fields based on the meta-data of verifications logged on the platform.