Abstract
Empirical economics and econometrics (EEE) research now relies primarily on the application of code to datasets. Handling the workflow linking datasets, programs, results and finally manuscript(s) is essential if one wish to reproduce results, which is now increasingly required by journals and institutions. We underline here the importance of “reproducible research” in EEE and suggest three simple principles to follow. We illustrate these principles with good habits and tools, with particular focus on their implementation in most popular software and languages in applied economics.
Keywords
Reproducibility; workflow; replication; literate programming; software;
Replaced by
Valérie Orozco, Christophe Bontemps, Elise Maigné, V. Piguet, A. Hofstetter, Anne Lacroix, F. Levert, and J.M Rousselle, “How to make a pie: reproducible research for empirical economics and econometrics”, Journal of Economic Surveys, vol. 34, n. 5, December 2020, pp. 1134–1169.
Reference
Valérie Orozco, Christophe Bontemps, Elise Maigné, V. Piguet, A. Hofstetter, Anne Lacroix, F. Levert, and J.M Rousselle, “How To Make A Pie: Reproducible Research for Empirical Economics & Econometrics”, TSE Working Paper, n. 18-933, July 2018.
See also
Published in
TSE Working Paper, n. 18-933, July 2018