1) Goals : Provide students with the knowledge of the
foundations of the econometrics of linear models. Make them capable
of choosing and implementing the relevant estimation methods and
statistical tests given the model and data characteristics.
2) Course overview :
1.- Introduction : what is econometrics (questions,
methods, data) ?
2.- The linear model with several explanatory variables
(endogenous variable, exogenous variables, assumptions on the
residual terms, OLS, variance analysis, maximum likelihood
3.-Tests and confidence intervals (errors of first and second
kinds, unilateral and bilateral tests)
4.-The linear models with serially correlated and/or
heteroscedastic errors (properties of the OLS estimator, tests, GLS
and Feasible-GLS estimators).
5. Examples : applications to microeconomic and
- Ability to associate the properties of estimation methods with
the model assumptions
- Ability to properly interpret econometric results in order to
determine the relevant estimation method or test to be used in the
specific context under consideration
- Capability to answer a question by a proper use of econometric
methods when relevant
- Econometric Methods with Applications in Business and
Economics, C.Heij, P. de Boer, P.H. Franses, T. Kloek, H.K. van
Dijk, Oxford University Press, 2004.
- Introductory Econometrics : A Modern Approach, J.
Wooldridge, South Western College Publishing, 2003.
- Econometric Analysis, W.H. Greene, 7th edition, 2011, Pearson.
(Translated in French)
Basic knowledge of probability theory and statistics (usual
probability distributions, estimation and testing methods) as well
as basic knowledge in microeconomics and macroeconomics.