Objectives
The goal of this course is to provide an introduction to econometric theory and methods. In particular, we discuss the most important estimator: ordinary least squares  OLS.
Contents
The course has three main objectives:
 The first objective is to understand the intuition, the mathematical basis, and the properties of the OLS estimator. We begin with a revision of the OLS estimator in the simple linear regression model, and we introduce two fundamental concepts: the asymptotic properties of the OLS estimator that provide the basis for hypothesis tests. We generalize these concepts to the multiple linear regression model. We also discuss extensions of the OLS estimator involving panel data and instrumental variables. A good understanding of the mathematical basis is important for more advanced courses and for independently applying the methods developed in this course.
 The second objective is to learn how to interpret the estimated results, how to translate an empirical hypothesis into a statistical model, and how to interpret the results of hypothesis tests. This knowledge is important for all advanced courses in management, finance, and economics that make reference to empirical studies.
 The third objective is to develop presentation skills: to prepare solutions for statistical and econometric problems sets and to present them in small groups. The ability to explain your reasoning, to communicate your theoretical and empirical results, and to interpret them in a concise way are three qualities that set you apart from graduates in other fields. For that reason, we will put a lot of emphasis on this third objective.
References
Stock, James and Mark Watson (2007, 2015), Introduction to Econometrics, Pearson Publishers.
Term project
 Type of project : Written report + empirical analysis  Maximum number of projects admitted for this course : 3  Deadline for applying to course professor for project : september 27, 2019  Deadline for submitting finished project : december 20, 2019  Method of evaluation (including resit options) : evaluation of the report and the empirical analysis. Retake: Evaluation of a revised version of the project.  Other information : 
Evaluation
First attempt
 Exam:

Written 2 hours
 Documentation:
 Not allowed
 Calculator:
 Not allowed
 Evaluation:
The evaluation consists of two parts: 70% of the final grade will be based on a written final exam. 30% will be based on group work in the exercise sessions.
The written final exam will last two hours. Documentation: not allowed. Calculator: not allowed.
The derivations, proofs, and calculations shown during class in addition to the slides are an integral part of this course and, consequently, are relevant for the exam. The same applies to all applications and exercises.
For the evaluation of the group work the following rule applies: Out of two groups that had to prepare the solutions for an exercise one will be randomly selected. The presentation of this randomly selected group will be evaluated with a score ranging from 0 to 10. The other group has to hand in its written solution which will also be evaluated with a score. Overall, the average score obtained for the group work contributes 30% of the final grade. The presence of the group members that had to prepare a presentation and a written solution will be verified. The score obtained for the presentation or the written solution only counts for the group members that are present. If all members of a group are absent, each of them gets a score of 0.
Retake
 Exam:

Written 2 hours
 Documentation:
 Not allowed
 Calculator:
 Not allowed
 Evaluation:
In the retake session, the same conditions apply for the written retake exam as for the written final exam. However, the grade obtained for the group work during the exercise sessions counts for 30% of the final grade only if it is above the grade obtained in the written retake exam. Otherwise, only the grade of the written retake exam counts. In other words, in the retake session, the group work only counts if it leads to a higher grade.
