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Data and Code Guidance by Data Editors

Guidance for authors wishing to create data and code supplements, and for replicators.

Requested Information for Code

On this page:

Readings

Some scientists, including economists, have put together excellent guidance and tutorials. See

README and master script

All replication archives should have a README (in PDF, text, or a simple formatting language such as Markdown, like this document). The README should provide a sufficient description to understand the structure of the replication archive (directory structure, what is acquired from third parties, what is generated by scripts, how much output to expect). It should document each file or class of files that are included.

We strongly encourage the provision of a master script. The master script should run all programs necessary to provide the outputs, in the right sequence, robustly.

In some cases, the master script might also serve as a README (for instance, “README.bash”, “README.py”, “README.Rmd”), as long as it satisfies all conditions of the README as well (i.e., ample comments).

Configuration

Things not to do

xkcd-data-pipeline

Things to do

Versioning of packages

You should be precise about the relevant packages.

In R, you could fix things by installing specific versions, see Installing older versions of packages.

In Stata, making a distinction between Stata Journal and SSC versions can sometimes help. If the package license permits, distributing the package with the core code is also possible.

Some facts

Most economists in the late 2000s (through 2018) use either Stata or Matlab. Assume that replicators have not (yet) learned your preferred software if you are using something else, and provide some guidance how to use it.

software usage AER Figure: Software usage in the AER, 2000-2018 (Source: Baylis and Schrimpf, 2018)