Teaching Reproducibility and Replicability while Teaching Econometrics in the Classroom
With Anson T. Y. Ho, Kim P. Huynh, David T. Jacho-Chavez, and Carson H. Rea [Forthcoming - Advances in Econometrics]
This research discusses how reproducibility and replicability can be taught to economists and social scientists while learning Econometrics. Instructors can utilize standard tools from Data Science and Machine Learning to teach classical undergraduate Econometrics curriculum. This paper emphasizes the usage of self-contained computing environments for students to complete and submit their Econometric practice exercises using open-source software. The demonstration centers around how instructors can create computer-based assignments that can be distributed electronically to students. The assignments are accompanied by code that automatically deploys a computing environment in the cloud where the assignment can be completed without the need for further software installation or a hardware upgrade. This teaches students how to prepare their work to be reproducible and replicable.