# Econometrics

lecge1316  2020-2021  Louvain-la-Neuve

Econometrics
Due to the COVID-19 crisis, the information below is subject to change, in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
5 credits
30.0 h + 15.0 h
Q1
Teacher(s)
Dejemeppe Muriel;
Language
French
Prerequisites

The prerequisite(s) for this Teaching Unit (Unité d’enseignement – UE) for the programmes/courses that offer this Teaching Unit are specified at the end of this sheet.
Main themes
The course covers the basic instruments of econometric analysis at an intermediate (for subjects introduced in previous courses) or introductory level (for new subjects). Examples of how these methods are applied to management problems are given. An important aspect of the course is learning econometric modelling: students are taught how to take a theoretical, abstract and general relation between variables and apply it to the formulation and estimation of a particular concrete form that relation might take in a given context. They will also be introduced to econometric software during the course.
Aims
 At the end of this learning unit, the student is able to : 1 This course is intended to give students a background in the theory and practice of Econometrics. The emphasis is on understanding the methods and their relevance to the solution of management problems. By the end of the course, students should be able to use these methods for simple question solving and to interpret the results of an econometric analysis while being aware of the limitations of the methods.
Content
Regression analysis with cross-sectional data
Chapter 1. General introduction
Chapter 2. The simple regression model
Chapter 3. Multiple Regression Analysis: Estimation
Chapter 4. Multiple Regression Analysis: Inference
Chapter 5. Multiple Regression Analysis: OLS Asymptotics
Chapter 6. Multiple Regression Analysis: Advanced issues
Chapter 7. Multiple Regression Analysis with qualitative information
Chapter 8. Multiple Regression Analysis: Heteroscedasticity
Chapter 9. Multiple Regression Analysis: Specification and data issues
+ Introduction to the statistical software STATA
Teaching methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

The non-French speaking students are expected to learn the course content by themselves based on the reference book in English (see below). For these students, two sessions of practical work with STATA (in English) are organized in a computer room or online during the quarter. Students are invited to learn the STATA software online at the beginning of the quarter.
Evaluation methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

The exam consists in a written exam in English on 20 points. The exam can be taken in January 2021 and/or August 2021.
If the health situation deteriorates, this evaluation method may evolve into an exclusively online evaluation.
Other information
Prerequisites:
1) Mathematics in economics and management
2) Statistics in economocmis and management
Online resources
See Moodle UCL (http://moodleucl.uclouvain.be/).
Bibliography
Livre de référence (reference book) :
Jeffrey Wooldridge (2016), Introductory Econometrics: A Modern Approach6th Edition, Cengage Learning.
Faculty or entity
ESPO

#### Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Aims
Mineure en statistique et science des données

Bachelor in Philosophy, Politics and Economics
5

Bachelor in Economics and Management

Minor in Economics

Master [120] in Agriculture and Bio-industries