American University, Washington DC, USA,
Labor Economics Seminar
PhD program in Economics
The course introduces the main topics of labor economics in relationship with Applied Microeconometrics. Each session focuses on conceptual problems, their methodological solutions and discussion of empirical research papers relevant to the session topics. The emphasis is given to empirical techniques allowing us to answer various questions of Labor Economics.
Applied Econometrics II
MA program in Economics
The course introduces policy evaluation terms and methods; considers various models with limited dependent variables such as multinomial probit/logit (ordered and unordered), tobit models and models of sample selection corrections; introduces models consisting of several equations; covers time series and panel data methods.
Applied Econometrics I
MA and BS programs in Economics
The course introduces the classical regression analysis. It covers the multiple regression model, some generalized linear models (probit/logit), nonlinear models that can be approached by the linear regression application. It also covers methods remedying from violation of the assumptions made regarding the basic regression model: instrumental variable estimation and panel data techniques (fixed and random effects models).
Université de Poitier, FRANCE
MA program in Applied Economics
MA program in Statistics and Actuarial Science
Non Parametric Estimation
Density Estimation; Local Polynomial Regression; Spline estimations
Simulation Methods
Monte Carlo simulations (management and scientific applications); Bootstrap method; Basics of Computing Integrals
Analysis of the Linear Generalized Models
Binary Probit/Logit Models; Ordered models; Multinomial Models; Models of Count Data; Goodness of fit tests
Qualitative Variables
Binary Probit/Logit Models; Ordered models; Multinomial Models; Logit Conditional Model; Tobit Model
Applied Statistics
Practical miscroeconometric applications using SAS
R
Introduction to matrices-based statistical software, R
Financial Mathematics
Université d'Evry, FRANCE
MA and BS in Mathematics and Economics
Financial Econometrics
Financial glossary ; Stylized facts; Models non linear in mean; CSS estimation; Models non linear in variance (ARCH/GARCH); ARCH/GARCH estimation (MLE with different distributions, GMM); Model diagnostic; Validation.; Forecasting (Forecasting Errors, Risk control); ARCH/GARCH extensions
Time Series
Time series concepts; MA Models; Exponential smoothing; ARMA Models; ARCH/GARCH Models
GAUSS
Introduction to the matrices-based statistical software, GAUSS
Econometrics I and II
University of Paris I Pantheon-Sorbonne, FRANCE
BS Economics
Probability
Introduction to Probability Theory
Statistics
Introduction to Statistics
Mathematical Economics
Basics of Mathematical Analysis, Algebra and Differential Equations