Labour Economics and Policy Evaluation

A.Y. 2021/2022
Overall hours
Learning objectives
The main aims of this course are to provide students with advanced knowledge to understand the functioning of labour markets in all their aspects (labour supply, labour demand, wage setting, etc.) and to illustrate to students some applications of the empirical methods commonly used in labour economics research (e.g. counterfactual impact evaluation).
Expected learning outcomes
After completing the course students will have an understanding of how to numerically solve and simulate dynamic stochastic general equilibrium models used by academic and policy economists to tackle research questions in Macroeconomics.
Course syllabus and organization

Single session

Lesson period
First trimester
Lectures and classes will be delivered in Microsoft Teams in a dedicated channel named "Labour Economics and Policy Evaluation (DSE) - 2021/22". Teaching material will be posted on the ARIEL website of the course.

Written online exams will take place using the platform, with invigilation through Zoom.
Course syllabus
The neoclassical model of labor supply [chapter 1]
Household and female labor supply [chapter 1]
Estimation of labor supply [chapter 1 and academic articles]
Labor demand [chapter 2]
Estimation of labor demand [chapter 2 and academic articles]
Competitive equilibrium and compensating wage differentials and discrimination, with applications [chapters 3 and 8 and academic articles]
Education and Human capital [chapter 4]
Estimation of the returns to education [chapter 4 and academic articles]
Technological progress, globalization and inequalities, with applications [chapters 10-11 and academic articles]
Labor market policies [chapter 14]
Examples of evaluation of labor market policies and reforms [academic articles]
Prerequisites for admission
Students are expected to be already familiar with demand and production theory, acquired in the "Advanced Microeconomics and Macroeconomics" (DSE, MEF) or "Advanced Microeconomics" (EPS) courses, and with the main empirical strategies used to assess causality in econometrics (i.e. taught in the DSE course "Micro-econometrics, Causal Inference and Time Series Econometrics" or the EPS course "Empirical Methods for Economics and Policy Evaluation"). Knowledge of statistical/econometric software packages such as R or STATA is needed to complete the (voluntary) paper assignment and class assignments. (Some basic knowledge of the STATA software can be acquired through the EPS "Advanced Computer Skills" course, from the 2020-21 edition.)
Teaching methods
The course mainly consists of lectures in which theoretical models explaining the functioning of the labour market and econometric methodologies commonly used for research in the field of labour economics will be illustrated. The course will consist both of frontal lectures and of more applied sessions in which students will be shown some empirical applications and asked to replicate academic papers using econometric software.
Teaching Resources
Pierre Cahuc, Stéphane Carcillo, and André Zylberberg (2014), Labor Economics, Second Edition, The MIT Press. [Chapters specified in the syllabus]

Academic papers listed in the ARIEL course website.

c papers listed in the ARIEL course website.
Assessment methods and Criteria
The course is assessed for both attending and non-attending students through a final written exam, which mainly consists of open and multiple-choice questions. Attending students can also decide to write an empirical paper (either single-authored or in groups of 2-3 students) on labour market issues in which they use the theory and methodology learned during the course. In this latter case, the paper makes 1/2 of the total grade.
SECS-P/01 - ECONOMICS - University credits: 6
Lessons: 40 hours
Thursday 17.00-19.00 on MS Teams or in person unless stated differently in this website (please write to me for confirmation). This week office hours will be on Oct 19, 18-19.30. If slots are all occupied there will be an extra session on Oct. 20, same
MS Teams