Introduction to econometrics with STATA and R

This course aims to provide a brief introduction to econometrics using two leading softwares, Stata and R. The course begins by a brief overview of the commonly used statistical and econometric tools that can be used with Stata and R. The course then covers the key skills needed to conduct quantitative analysis from scratch on the two softwares, e.g. loading and browsing a dataset, data manipulation/restructuring, running programs, writing code. The course also provides students with real-life applications by replicating econometric studies on Stata and R. Whenever necessary, a reminder of econometric concepts and methods is done. The course’s main purpose is to provide students with the necessary basics to independently conduct statistical and econometric analyses with two leading softwares, and pave the way towards more advanced self-training.

Session 1 :
Formule standard : La note finale est composée d’une note de contrôle continu (50%) et d’une note d’examen terminal (50%) consistant en épreuve sur table de 2 heures.
Formule dérogatoire : Une épreuve sur table de 2 heures.

Session 2 Une épreuve sur table de 2 heures.

Prise en compte de la situation sanitaire :
Si, pour tenir compte de la situation sanitaire, des restrictions ou des contraintes sont imposées à l'Université Paris Nanterre ou à l'UFR SEGMI, tout ou partie des épreuves, contrôles de connaissances et examens terminaux de la session 1 et de la session 2, ainsi que des sessions de rattrapages, pourront se dérouler en mode distancié.

This course trains students to (1) master two leading econometric softwares ; (2) conduct replicable statistical and econometric analyses ; (3) extract information from large amounts of data. Such skills are a prerequisite to conduct empirical research in the social sciences, and are increasingly valuable on the job market to gather sound information from raw data.

• Cameron, C. & Trivedi, P. (2010) : Microeconometrics using Stata, Stata Press
• Cunningham, S. (2018) : Causal Inference, the Mixtape, free ebook
• McDermotth, G. & Rubin, E. (2019) : R Intro – Regression Intro, free ebook