ECO-4104 : Econometrics 1

ECO-4104 : Econometrics 1

Responsable(s) :
  • Sinan Sarpca
Enseignant(s) :
  • Mathias Silva Vazquez





1e semestre

Public externe (ouverts aux auditeurs de cours)

Informations générales sur le cours : ECO-4104

Content objectif

ECO-4104 : Econometrics 1 : Advanced linear models

Responsible teacher: 

Mathias SILVA VAZQUEZ  (mathias.silva_vazquez [at] ens-lyon.fr)


This course introduces regression methods needed for empirical research in economics. We emphasize both the theoretical and the practical aspects of applied statistical analysis, estimating a number of econometric models and testing various hypotheses of interest to economists. Each session comprises comprehensive theorising and mathematical formalisation but keeps a strong focus on intuition and effective implementation. In particular, we make extensive use the R programming language, both to illustrate abstract statistical concepts using simulated data, and to perform econometric analysis on actual research datasets. The first part of this course covers multiple regression, model selection, hypothesis testing and statistical inference. The second part of the course deals with a variety of estimation issues that arise in applied analysis, and affect the validity our estimated coefficients and test statistics. Examples include heteroscedasticity, autocorrelation, endogeneity or multicollinearity, among others. We learn to diagnose each problem, and use alternative estimators, such as generalised least squares or instrumental variables, in order to recover reliable estimates.


This course helps you develop a solid theoretical background in econometrics, as well as the ability to execute independent research projects. In particular, you will be able to understand, implement and interpret a variety of econometric models. Depending on the characteristics of your dataset, you will be capable of diagnosing and correcting common estimation issues. Last but not least, you will achieve greater proficiency in the R language, which enable you to handle data and estimate models with great efficiency and flexibility.