The aim of this class is three-fold: to give students a first experience in applied econometrics based on applications of the tools covered in the Introduction to econometrics class; to introduce students to the practice of softwares used in data analysis in academic and professional research; last, to give examples of real world public policies issues on which economics and psychology provide relevant answers.

Software

The software used in class is Stata (https://www.stata.com/) which has been introduced in the Introduction to econometrics class. For an introduction to the software, refer to:

• Cameron and Trivedi (2010). Microeconometrics Using Stata, Stata Press, Revised Edition, Chapter 1.
• https://www.stata.com/links/resources-for-learning-stata/

Students are more than welcome to implement the programs shown in class using R, based e.g. on this tutorial: https://www.princeton.edu/~otorres/RStata.pdf

Outline

• Syllabus.
• Recommended textbook is the same as Introduction to econometrics class.
• French speaking students can also have a look to chapters 1-8 of Crépon B., Jacquemet N. (2018). Econométrie : Méthodes et Applications, 2eme édition. De Boeck Universités, Collection « Ouvertures ».

Chap. 1. OLS estimation in the linear classical model: a refresher and an application.

• Application based on Aeberhardt, Coudin, Rathelot (2017). The Heterogeneity of Ethnic Unemployment Gap, Journal of Population Economics. [pdf] [dataset] [do file]

Chap. 2. Randomization as a source of identification – measuring labor market discrimination.

• Application based on Edo, Jacquemet, Yannelis C. Language Skills and Homophilous Hiring Discrimination: Evidence from Gender- and Racially-Differentiated Applications, Review of Economics of the Household. [dataset] [do file]

Chap. 3. Statistical tests and inference.

References