Data Availability Policy
Economics – The Open-Access, Open-Assessment E-Journal has adopted the policy on data availability first introduced by the American Economic Review. This policy applies to all new submissions, effective January 1, 2009.
It is the policy of Economics to publish papers as journal articles only if the data used in the analysis are clearly and precisely documented and are readily available to any researcher for purposes of replication. Authors of accepted articles that contain empirical work, simulations, or experimental work must provide to Economics, prior to publication as article, the data, programs, and other details of the computations sufficient to permit replication. These will be posted on the Economics Web site. The Economics Editorial Office should be notified at the time of submission if the data used in a paper are proprietary or if, for some other reason, the requirements above cannot be met.
As soon as possible after acceptance as journal article, authors are expected to send their data, programs, and sufficient details to permit replication, in electronic form, to the Editorial Office. Please send the files via e-mail to firstname.lastname@example.org, indicating the manuscript number. Questions regarding any aspect of this policy should be forwarded to the Editorial Office.
Our policies differ somewhat for econometric and simulation papers, and for experimental papers.
For econometric and simulation papers, the minimum requirement should include the data set(s) and programs used to run the final models, plus a description of how previous intermediate data sets and programs were employed to create the final data set(s). Authors are invited to submit these intermediate data files and programs as an option; if they are not provided, authors must fully cooperate with investigators seeking to conduct a replication who request them. The data files and programs can be provided in any format using any statistical package or software. Authors must provide a Readme PDF file listing all included files and documenting the purpose and format of each file provided, as well as instructing a user on how replication can be conducted.
If a request for an exemption based on proprietary data is made, authors should inform Editorial Office if the data can be accessed or obtained in some other way by independent researchers for purposes of replication. Authors are also asked to provide information on how the proprietary data can be obtained by others in their Readme PDF file. A copy of the programs used to create the final results is still required.
For experimental papers, we have a more detailed policy, including requirements for submitted papers as well as accepted papers. We normally expect authors of experimental articles to supply the following supplementary materials (any exceptions to this policy should be requested at the time of submission):
- The original instructions. These should be summarized as part of the discussion of experimental design in the submitted manuscript, and also provided in full as an appendix at the time of submission. The instructions should be presented in a way that, together with the design summary, conveys the protocol clearly enough that the design could be replicated by a reasonably skilled experimentalist. For example, if different instructions were used for different sessions, the correspondence should be indicated.
- Information about subject eligibility or selection, such as exclusions based on past participation in experiments, college major, etc. This should be summarized as part of the discussion of experimental design in the submitted manuscript.
- Any computer programs, configuration files, or scripts used to run the experiment and/or to analyze the data. These should be summarized as appropriate in the submitted manuscript and provided in full as an appendix when the final version of a manuscript is sent in. (Data summaries, intermediate results, and advice about how to use the programs are welcome, but not required.)
- The raw data from the experiment. These should be summarized as appropriate in the submitted manuscript and provided in full as an appendix when the final version of an accepted manuscript is sent in, with sufficient explanation to make it possible to use the submitted computer programs to replicate the data analysis.
Other information, such as applications to Institutional Review Boards, consent forms, or Web signup and disclosure forms, is not required or expected. If it desired to make this kind of information public, it should be posted on laboratory or authors' Web sites.
If the paper is accepted by Economics, the appendices containing instructions, the computer programs, configuration files, or scripts used to run the experiment and/or analyze the data, and the raw data will normally be archived in the repository of the E-Journal in the Dataverse Network ( http://dvn.iq.harvard.edu/dvn/dv/economics) when the paper appears.
Instructions for Sending Data, Appendices, Additional Materials, Final Manuscripts, and Figures
Please label your files before e-mailing them to email@example.com. Each file name should clearly indicate if the file is a "manuscript", "data", "appendix", "figures", or "additional materials". Each file should contain the manuscript number (which should also be included in the subject line of the e-mail).
- Data sets can either be submitted together with the manuscript via Editorial Express or be sent via e-mail to firstname.lastname@example.org.
- It is preferable to send each "group" of files (if there is more than one file for data, figures, additional materials, etc.) as a .zip file (for example, 20030002_data.zip or 20030002_addmaterials.zip).
- Please use underscores instead of spaces when creating file names.
- Appendices should be sent in PDF format.
- All data sets must include a PDF "Read me" file (clearly labeled, for example, ReadMe.pdf) containing a list of all files included and guiding a user on the types of files and how to use them to do replication. The PDF "Read Me" file should be included in the .zip file containing the data set.