How To Make A Pie: Reproducible Research for Empirical Economics & Econometrics

Valérie Orozco (1) , Christophe Bontemps (1) , Élise Maigné (2) , Virginie Piguet (3) , Annie Hofstetter (4) , Anne Marie Lacroix (5) , Fabrice Levert (6) , Jean-Marc Rousselle (4)

1 TSE-R - Toulouse School of Economics
2 US ODR - Observatoire des Programmes Communautaires de Développement Rural
3 CESAER - Centre d'Economie et de Sociologie Rurales Appliquées à l'Agriculture et aux Espaces Ruraux
4 LAMETA - Laboratoire Montpelliérain d'Économie Théorique et Appliquée
5 GAEL - Laboratoire d'Economie Appliquée de Grenoble
6 SMART-LERECO - Structures et Marché Agricoles, Ressources et Territoires

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.

Mots clés: workflow; replication; literate programming; software; reproducibility

Domaines: Economies et finances

Valérie Orozco, Christophe Bontemps, Élise Maigné, Virginie Piguet, Annie Hofstetter, et al.. How To Make A Pie: Reproducible Research for Empirical Economics & Econometrics. 2019. ⟨hal-02025843⟩