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

Author

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  • Valérie Orozco

    (TSE - Toulouse School of Economics - EHESS - École des hautes études en sciences sociales - INRA - Institut National de la Recherche Agronomique - CNRS - Centre National de la Recherche Scientifique - UT1 - Université Toulouse 1 Capitole - Université Fédérale Toulouse Midi-Pyrénées)

  • Christophe Bontemps

    (TSE - Toulouse School of Economics - EHESS - École des hautes études en sciences sociales - INRA - Institut National de la Recherche Agronomique - CNRS - Centre National de la Recherche Scientifique - UT1 - Université Toulouse 1 Capitole - Université Fédérale Toulouse Midi-Pyrénées)

  • Elise Maigne

    (US ODR - Observatoire des Programmes Communautaires de Développement Rural - INRA - Institut National de la Recherche Agronomique)

  • Virginie Piguet

    (CESAER - Centre d'Economie et de Sociologie Rurales Appliquées à l'Agriculture et aux Espaces Ruraux - AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement - INRA - Institut National de la Recherche Agronomique)

  • Annie Hofstetter

    (LAMETA - Laboratoire Montpelliérain d'Économie Théorique et Appliquée - UM1 - Université Montpellier 1 - UPVM - Université Paul-Valéry - Montpellier 3 - INRA - Institut National de la Recherche Agronomique - Montpellier SupAgro - Centre international d'études supérieures en sciences agronomiques - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement)

  • Anne Marie Lacroix

    (GAEL - Laboratoire d'Economie Appliquée de Grenoble - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - INRA - Institut National de la Recherche Agronomique - CNRS - Centre National de la Recherche Scientifique - UGA [2016-2019] - Université Grenoble Alpes [2016-2019])

  • Fabrice Levert

    (SMART-LERECO - Structures et Marché Agricoles, Ressources et Territoires - INRA - Institut National de la Recherche Agronomique - AGROCAMPUS OUEST - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement)

  • Jean-Marc Rousselle

    (LAMETA - Laboratoire Montpelliérain d'Économie Théorique et Appliquée - UM1 - Université Montpellier 1 - UPVM - Université Paul-Valéry - Montpellier 3 - INRA - Institut National de la Recherche Agronomique - Montpellier SupAgro - Centre international d'études supérieures en sciences agronomiques - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement)

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.

Suggested Citation

  • Valérie Orozco & Christophe Bontemps & Elise Maigne & Virginie Piguet & Annie Hofstetter & Anne Marie Lacroix & Fabrice Levert & Jean-Marc Rousselle, 2019. "How To Make A Pie: Reproducible Research for Empirical Economics & Econometrics," Working Papers hal-02025843, HAL.
  • Handle: RePEc:hal:wpaper:hal-02025843
    Note: View the original document on HAL open archive server: https://hal.archives-ouvertes.fr/hal-02025843
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    References listed on IDEAS

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    Keywords

    literate programming; replication; workflow; software; reproducibility;
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