Advanced Econometrics III
Master Analyse et politique économiqueParcours Statistique et économétrie
Credits5 crédits
Description
This unit of teaching comprises of two parts:
- Advanced Econometric Theory III
This part covers advanced econometric methods that are not covered in the M1. It is a core method course of the M2 and significantly enhances the method portfolio of the students.
- Resampling Methods (Bootstrap, wild bootstrap, block bootstrap, bias corrections, subsampling)
- Quasi Maximum Likelihood
- Simulation Based Methods (simulated ML and Moment estimation, Indirect Inference)
- Bayesian Methods
- EM Algorithm
- Measurement Error and Missing Data Problems
- Econometric Evaluation of Public Policies
This part covers important methods for treatment evaluation. It introduces the concept of counterfactual outcomes, treatment effects and self-selection and presents various approaches for the identification and estimation of the treatment effects:
- (Double-)Difference in Differences
- Regression Discontinuity (Sharp&Fuzzy)
- Propensity score weighting
- Inverse Probability weighting
- Matching methods
- IV methods (Local average treatment effects)
- Synthetic control groups
Compétences visées
On completing the course a student will be able to:
- Choose econometric model specifications which are suitable, both to the data and to the economic models;
- Understand estimation and inference methods which are appropriate for different econometric problems;
- Estimate the model and be able to interpret the estimation results, using appropriate software (part 2).
- Gather practical work experience with a statistical package as preparation of an empirical master dissertation (part 2).
- Conduct independent empirical work and present the results to an audience (part 2).
Disciplines
- Sciences économiques