What will you learn ?

This degree is divided in 6 courses :

Micro-econometrics

Many empirical questions in economics depend on the causal effects of programs or policies. In the last two decades, new tools have been developed on the econometric and statistical analysis of the effects of such programs or treatments.

Thus the purpose of the course is threefold: 

First, it aims at providing students an understanding of econometric issues that arise in the program evaluation and equip them with the analytical skills for how to approach econometric issues in general using microeconomic data.

Second, the course will teach students the skills that are necessary for applying the most important approaches of program evaluation to address a variety of policy relevant questions, while developing their awareness of limitations. 

Third, students will be provided the opportunity to gain a first-hand working knowledge of the econometric issues and statistical methods of program evaluation by going over real-life applications using the STATA statistical software.

Teacher : Ahmed Tritah

Macroeconomics

This course put emphasizes on frictional approaches of the labor market and potential implications for macroeconomics analysis. This includes matching problems and non competitive determination of wages, as developed by Peter Diamond, Dale Mortensen and Christophe Pissarides (DMP) who got the Nobel Prize for their works on unemployment theory in 2010.

After presenting the benchmark DMP model, extensions allowing to addressing wage dispersion and life cycle issues are also proposed. This deals on the one hand with on-the-job search of workersn and wage posting strategies, and on the other hand with human capital accumulation and pure horizon dynamics of job creations and job destructions related to retirement exit. We lastly focus on policy oriented questions, such as the impact of employment protection, unemployment insurance and retirement age.

The course combines both theoretical developments and numerical simulations using Octave software to quantitatively address both issues.

Teacher : Arnaud Chéron

Experimental economics

Experimental economics consists in putting the typical features of a model into the laboratory in order to evaluate its relevance. In particular, the subjects recruited are paid on the basis of the economic decisions they make under controlled protocols which allows to disentangle the impact of isolated variables that would otherwise covary in the real world.

Experimental economics is now widely recognized as one of the main quantitative methods used to valid or contradict theoretical approaches, which in turn paves the way for refinements of the theory and consequently for more accurate recommendations to public authorities or private decision makers.

The Nobel Prizes of the last decade, successively awarded to Daniel Kahneman and Vernon Smith (2002) and Alvin Roth (2012) demonstrate the crucial role played by experiments in modern economics. Specifically, in the recent years, labor economics has made dramatic advances on the basis of the regularities gathered in the lab. More precisely, experiments have permitted a better understanding of the internal organization of firms and has emphazised a number of important implications in terms of economic policies for the labor market.

The objective of this course is to give a more precise insight into the developments made possible by experimental methods in labor economics through the analysis of selected topics.

Teacher: Jonathan Vaksmann

Research Methodology for Applied Economics

Focused attention on how to organize and conduct research can increase the efficiency of the research process and its outcomes. This course will cover the basics of applied research in economics and give some guidelines to instruct students in the research process. We will cover how we use economic theory to formulate a hypothesis to test and how we use data to test our hypothesis.By the end of the module the student should be able to understand how economists approach questions, in particular, how they construct hypotheses and use data to discriminate between alternate explanations for events or patterns; describe data and present it in a meaningful manner. In doing this student will gain skills in the use of computer software including statistical and/or mathematical modelling software; conduct individual research and investigate topics under their own initiative; present their research to an audience; present their research conclusions in a written form. Students will read and discuss papers published in professional journals and perform data analysis as part of the course requirements.

Teacher : Salima Bouayad Agha

Macro-econometrics

The main motivation of this course is to present empirical counterparts of the recent developments of the microeconomics of the labor market:

  1. rational choices in a market without frictions (hours worked, retirement, education)
  2. the impacts of the search fictions on these choices (unemployment, employment and unemployment durations, wage distributions), and
  3. the interactions between the financial and the labor markets (precautionary saving, wealth distribution, acceptance or rejection of a job offer, retirement).

A first step is to learn how to solve rational expectation models. These models are useful because they allow us to go beyond the statistical evaluation of an existing policy. Indeed, the policy maker asks the optimal design of the policy and not only the impact of the old reforms. To adress the Lucas critique we must find micro-foundations to the equilibrium in order to identify both the structural parameters and the policy parameters. This is necessary to forecast the implications of a policy change. A second step is to learn how to estimate these models prior to an unexpected policy reform.

We will mainly focus on moments based estimation approaches. We can then use these models to predict the impact of new policy rules and evaluate what would be the design of the optimal policies.

Teacher: François Langot

Dsge modeling

This course is about the simulation and estimation of DSGE (Dynamic Stochastic General Equilibrium) models, which explain aggregate business cycles (and/or growth) phenomena by aggregating microeconomic behaviours of agents (households, firms, banks, ...).

Because it relies on optimizing behaviors this approach, in principle, respond to the well known Lucas critique, and allows to think about the positive and normative consequences of different economic policies (fiscal, monetary,...). These merits largely explain the recent widespread use of DSGE models at central banks (or other institutions) around the world.

The first part of the course deals with the methods used to simulate such models. We will focus on the perturbation approach and on solvers for the perfect foresight models (which also allows to solve OLG models). The second part introduces the Bayesian estimation approach of these models (linear and nonlinear filters). All these aspects will be explored using Matlab/Octave or Python and the Dynare toolbox.

Teacher: Stéphane Adjemian