Econometrics 2

Objective

This course aims to complement the first-semester econometrics class in the field of statistical analysis of individual-level data.

The first part of the course covers extensions of linear models introduced in Econometrics I. These extensions are designed to address the problem of endogeneity, which lies at the core of modern microeconometrics. The course provides an in-depth treatment of instrumental variables, including issues of heteroskedasticity and weak instruments. It also considers the use of panel data, even in cases where model dynamics are complex. Methodologically, this section relies on the generalized method of moments (GMM).

The second part of the course focuses on models with limited dependent variables. This includes discrete variables (e.g., unemployment indicators, loan repayment, health status, transport choices), as well as censored variables such as consumption, which takes strictly positive but potentially zero values. Selection problems (e.g., labor supply, endogenous sample selection) are also addressed. For these nonlinear models, the primary estimation method studied is maximum likelihood.

Learning Outcomes
By the end of the course, students will be able to:

• Master the theory and practice of instrumental variables, and understand their limitations.

• Distinguish among different panel data methods, and evaluate the advantages and limitations of each approach.

• Identify situations with limited dependent variables and choose the appropriate model (logit/probit, multinomial or conditional logit, tobit, …), understand the estimation method, and the specificities of each model.

• Understand and apply the generalized method of moments (GMM) and maximum likelihood estimation in contexts similar to those studied in class.

• For all models and methods covered: conduct a complete econometric analysis with real data using STATA (model specification, choice of estimation method, testing, etc.) and interpret the results.

Assessment

• Final written exam (2/3)

• Midterm exam (1/3)

Planning

1. Generalised moments method -Definition, convergence, optimality, specification tests, applications to instrumental variables in the heteroscedastic case.
2. Introduction to panel econometrics- Random effects model, fixed effects model, random effects test. Estimation with weak endogeneity: GMM estimation, overidentification tests, application to autoregressive panels.
3. Evaluation of public policy -Natural experience. Causal model. Difference in difference estimator.
4. Binary dependent variable models -Logit and probit models: identification, estimation, model quality, heteroscedasticity and endogeneity problems.
5. Extension of the dichotomic model- Ordered and unordered polytomics, count models (Poisson models).
6. Limited dependent variable models- Simple tobic model, selection models: exogenous selection, truncation, generalised selection.

References

AMEMIYA, T. Advanced Econometrics, Basil Blackwell, Oxford, 1989 [28 AME 00 A]
CREPON B et N. JACQUEMET Econométrie : Méthode et Applications, de Boeck
GOURIEROUX C. Econométrie des variables qualitatives, 2ème éd., Economica, 1989 [28 GOU 00 A]
WOOLDRIDGE, J. Econometric Analysis of Cross Section and Panel Data, 1ère ou 2ème éd., MIT Press, 2002 ou 2010 [28 WOO 00 B]