Dans le cadre de ce cours, nous passons une ou deux séances sur l’estimation des différences salariales hommes/femmes. Durant ces séances, les étudiants utilisent des données pour essayer de quantifier cette différence et interpréter les résultats.

Contenu

The main objective is to learn how to apply econometrics techniques studied so far to inform managerial decisions, from investment selection by companies to the selection of public policies by the state. These skills are an essential part of economists' toolbox, and very useful for both public and private employers. The course will cover the following topics:

  1. Using econometrics to inform decisions
  2. Causal inference: Counterfactual outcomes
  3. Randomization and selection bias
  4. Regression as a model for conditional averages
  5. Multiple regression: omitted variable bias and control variables
  6. Non-linear models: Interpretations
  7. Models for binary (or categorical) outcomes
  8. Interaction terms: Heterogeneous treatment effects
  9. Repeated observations and panel data models
  10. Panel data application: Difference-in-differences

Each week we will hold one session in the classroom and one session in the computer lab. In the classroom we will introduce concepts and review a number of important econometric tools for data analysis. In the lab we will learn to implement these tools with data and build up software skills. By the end of the class, students will have acquired skills to manipulate data in Excel (matching datasets, pivot tables) and use Stata to run a set of regression models. Students will also get to read high-quality peer-reviewed articles on different topics in economics to understand how empirical results are presented and interpreted. As such, one additional objective is to understand how peer-reviewed works for academic publications, and what it means for the interpretation of the results of published articles vs. reports and other document that do not go through a peer-review process.

Important note: The language for the course is English, and this for two reasons. First, you need to build up the relevant vocabulary to read and interpret the scientific literature (which is almost exclusively in English). Second, this class prepares you for good master programs and job opportunities in international environments, where a good command of English is usually a pre-requisite. However, in-class interactions are often in French.

Forme de l'évaluation

Students will be graded according to the following scheme:

(i) A 2-page report replicating / extending the results of a published article, followed by a short presentation to the class (30%) ;
(ii) An 1-page assessment report on the work of one of your peers (10%) ;
(iii) a final written exam (duration: 2h) during the exam session (60%).

For the re-take exam, the results obtained from the exercise series are not taken into account (written exam, duration: 2h, 100% of the final grade).

During the written exams, documents, calculators, or connected devices are not allowed. In case of violation of these rules, the students are in situation of fraud and the unauthorized items will be removed. The exam could be deemed as failed.

Documentation

The course uses a variety of relevant sources which will be made available as pdfs on Moodle.

First, we will use selected chapters of the book by Angrist and Pischke for their non-technical coverage of empirical research in social sciences: Joshua D. Angrist & Jörn-Steffen Pischke (2014) Mastering Metrics: The Path from Cause to Effect, Princeton University Press.

For some parts of the class, we will follow part of the econometric textbook by Wooldridge: Jeffrey Wooldridge (5th ed., 2016) Introductory Econometrics: A Modern Approach, Cengage Learning.

Finally, the book by Cameron and Trivedi (2010) is a useful resource for the application of econometric techniques with Stata: A. Colin Cameron and Pravin K. Trivedi (2010) Microeconometrics Using Stata: Revised Edition, Stata Press.

Software: We will use Stata and Excel, which will be available in the computer lab, or on personal computers through remote desktop (see https://www.unine.ch/sitel/logiciel). You can also ask sitel to install Stata directly on your personal computer.

Pré-requis

Before taking this class, students are required to complete the course "Statistical inference".

This is a 3rd year BA class mainly geared towards students in economics (économie politique), although many good students in the past have been quantitatively-inclined students in other orientations.

Forme de l'enseignement

Weekly 2-hour in-class lectures and 2-hour computer lab sessions. In the lab students work on their own under supervision of the instructor

Objectifs d'apprentissage

Au terme de la formation l'étudiant·e doit être capable de:

  • Prepare empirical evidence for decision-making purposes
  • Interpret regression results
  • Analyse data with econometric software
  • Evaluate the quality of empirical work performed by others
  • Present in plain language the results of an academic article
  • Recommend policy design on the basis of empirical results
  • Write a memo summarizing concisely results from a research article
  • Discuss the limitations of regressions

Compétences transférables

  • Communicate in a second language
  • Manage priorities
  • Intellectual rigor and curiosity

Semesters:

Stufe:

BA

ETCS:

6

Domaines:

Wirtschaftswissenschaft

Type de haute école:

UH