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The American Economic Association's Data Editor has reviewed more than 1,000 empirical articles since July 2019, and worked with authors to improve the reproducibility of their research compendia (replication packages). Some lessons emerge from this work. In this presentation, I will focus on lessons for young scholars (students and young researchers), on possible lessons even for more seasoned researchers. Students and researchers are embedded within institutions, and I will discuss the kind of support that institutions (universities, data providers, compute services) should be providing to students, faculty, and researchers, for a robust, reproducible, and transparent science enterprise. This particular version was presented in the IMLS National Forums on Data Quality, The opinions expressed in this talk are solely the authors, and do not represent the views of the U.S. Census Bureau, the American Economic Association, or any of the funding agencies.

The typical README in social science journals serves the purpose of guiding a reader through the available material and a route to replicating the results in the research paper, including the description of the origins of data and/or description of programs. As such, a good README file should first provide a brief overview of the available material and a brief guide as to how to proceed from beginning to end, before then diving into the specifics. These template files structure such a README in a way that is compliant with the typical data and code workflow in the social sciences., The README is under a CC-BY-NC license. Usage by commercial entities is allowed, reselling it is not.

We record our decision tree on how to choose between two or one question for the survey.

Presentation at SOLE 2022.

Talk given at the 2022 Toronto Workshop on Reproducibility, The opinions expressed in this talk are solely the authors, and do not represent the views of the U.S. Census Bureau, the American Economic Association, or any of the funding agencies. Based on joint work with Harry Son, Meredith Welch, David Wasser, Michael Darisse, Leonel Borja Plaza.

Replicability is at the core of the scientific enterprise. In the past 30 years, recurring concerns about the extent of replicability (or lack thereof) of the research in various disciplines have surfaced, including in economics. I am the Data Editor responsible for pre-publication reproducibility for 8 journals, and will convey to participants practical recommendations for creating reproducible research, as a researcher, as a journal editor, and from an institutional perspective. The solutions to these problems will change the way research will be taught and conducted, in economics in particular, and in the social sciences more broadly. The implications affect undergraduate and graduate teaching, research infrastructure, and habits., The opinions expressed in this talk are solely the authors, and do not represent the views of the U.S. Census Bureau, the American Economic Association, or any of the funding agencies.

Replicability is at the core of the scientific enterprise. In the past 30 years, recurring concerns about the extent of replicability (or lack thereof) of the research in various disciplines have surfaced, including in economics. In this talk, I describe the context in which the current discussion in the social science is occurring: what are the definitions of replicability and reproducibility, what is failing, and to what extent. I discuss progess over the past 15 years. Finally, I discuss the concrete measures that have been implemented under my guidance at the American Economic Association, and the first preliminary outcomes from those measures. I conclude with some observations on how to integrate reproducibility into the scientific workflow in the social and statistical sciences. The solutions to these problems will change the way research will be taught and conducted, in economics in particular, and in the social sciences more broadly. The implications affect undergraduate and graduate teaching, research infrastructure, and habits. (Short version of talk - for longer versions, see f.i. https://doi.org/10.5281/zenodo.3666011) Presented at "Love Your Code" at ONS, London, UK on February 14, 2020.