Economics Program

ECO_51633_EP: Mathematics, Probability, and Statistics for Economics

(end of August, beginning of September)

Mathematics, Optimization, Probability, and Statistical Inference - 36 hours
Nicolas Vieille, Michele Fabi 

• Basic calculus.
• Linear algebra.
• Static and dynamic optimization.
• Basic probability theory.
• Statistical inference.

ECO_51432_EP: Introduction to R for Economics

Introduction to R  - 8 hours

(end of August, beginning of September)

This crash course is intended to introduce students to the statistical software R. The goal is to teach students how to implement simple data science projects on R and where to look for for more advanced uses.

We will cover the basics of the software and focus on data wrangling, producing descriptive statistics and running regressions. If time permits, we will also learn how to use local and global variables.

At the end of the course the student will know:

• how to work with R
• where to look for for more advanced uses

and they will be able to:

• run some statistical analyses with R

ECO_52650_EP:  Microeconomics I

Individual decision-making and market equilibrium - 50 hours
Tristan Tomala, Bruno Biais, Johan Hombert

• Choice theory and introduction to welfare economics.
• Consumer theory.
• Social choice (preference aggregation and manipulability).
• Producer theory.
• Choice under uncertainty (expected utility, risk aversion).
• General equilibrium, fundamental welfare theorems.
• Asset markets and general equilibrium under uncertainty.
• Externalities and public goods.
• No trade theorem, rational expectations.

ECO_52651_EP: Macroeconomics I

Economic Growth - 50 hours

Antonin Bergeaud,  Alessandro Riboni

• Neoclassical growth model.
• Public policies in the neoclassical growth model.
• Structural transformation.
• Inequality, political economy of growth.
• The overlapping generations model.
• Public policies and bubbles in the overlapping-generations model.
• Product variety model.
• Schumpeterian growth.

ECO_52652_EP: Advanced Econometrics I

The Linear Regression Model and Extensions - 40 hours
Sebastien Roux, Thierry Kamionka

In this course we introduce the linear regression model and its theoretical foundations. We present and discuss the methods to estimate such models, i-e to define the parameters of interest, estimate them and test their statistical significance, under different sets of assumptions (homoskedasticity or heteroscedasticity, exogeneity or endogeneity), specifications (simple or multiple regression) or types of data (cross-sectional, panel data, time series).

Outline:
1. Introduction to econometrics
2. The Simple Regression Model
3. Multiple Regression Analysis:
A. Estimation
B. Inference
C. Asymptotics
4. Qualitative Information in Linear Regression
5. Heteroskedasticity
6. Repeated Cross Section and Panel Data
7. Instrumental Variables

Literature:
Angrist and Pischke: (2009): Mostly Harmless Econometrics, Princeton University Press.
Wooldridge (2013): Introductory Econometrics: A Modern Approach, 5th Edition, South-Western College Publishing.

ECO_52658_EP: Introduction to Time Series Econometrics

Jean-Michel Zakoian, 24h

• Generalities on univariate second-order stationary processes
• Autocovariances, partial autocorrelations
• Innovations
• Wold theorem
• Asymptotic properties of empirical moments.
• AR, MA, ARMA, SARIMA processes
• Canonical representation - Identification, estimation, tests and forecasting
• Model building
• Nonstationary models, Unit root tests.
• Stationary vector processes
• Multivariate AR models
• Statistical Inference
• Causality tests, impulse-response analysis.
• Non-stationary vector processes and definition of cointegration
• Cointegrated VAR models and error-correction models (ECM)
• Estimation of cointegrated VAR
• Testing for Cointegration.

ECO_52660_EP: Microeconomics II

Strategic Interactions and Information 50 hours
Yukio Koriyama, Yuki Tamura 

• Normal form games, pure and mixed strategies, equilibrium concepts (dominance, rationalizability, Nash).
• Imperfect competition (Cournot, Bertrand, Hotelling).
• Extensive form games with perfect information, backwards induction.
• Extensive form games with imperfect information (information sets), normal form representation.
• Bayesian games, auctions, adverse selection, signaling, screening.
• Equilibrium refinements (Perfect Bayesian equilibrium, sequential equilibrium).
• Social choice and introduction to mechanism design.
• Contract theory, principal agent models, risk sharing.

ECO_52661_EP: Macroeconomics II

Business cycles - 50 hours
Jean-Baptiste Michau

• Traditional macroeconomics: The IS-LM AD-AS model.
• Consumption.
• Investment; The ramsey model.
• Determination of the price level.
• Real business cycle theory.
• The new Keynesian framework.
• Asset pricing; The Aiyagari model.
• Search models of the labor market.
• International macroeconomics.
• The Great Recession.

ECO_52662_EP: Advanced Econometrics II

Nonlinear, Qualitative Data, and Panel Methods - 40 hours
Christian Belzil

• Extremum Estimators 1st part: M-Estimators (Maximum Likelihood, Nonlinear Least squares).
• Extremum Estimators 2nd part: GMM.
• Hypothesis Testing: Wald, Lagrange Multipliers, Likelihood Ratio Statistics.
• Instrumental Variables, 2SLS, Multiple-Equation GMM (if time).
• Dynamic Panel Data: Instrumental Variables and GMM.
• Binary Choice Models.
• Multinomial and Ordered Choice Models.
• Non-linear Panel Data Models.
• Censored Regressions.
• Duration Models.

ECO_50P11_EP: Applied Economics Project 

Over the whole year

Coordinators: Alessandro Riboni 

Students must work in groups of 2 or 3. They should rely on a statistical software, such as Stata, to apply econometric methods to a dataset. This work leads to the writing of a small dissertation and to an oral presentation.

Description