Understanding and use of concepts and tools essential to the processing and analysis of empirical data using quantitative methods.
This course is dedicated to quantitative methods. It aims at studying the links between variables using the tools of (linear) regression. The objective is to understand the general principles of the discipline and its methods, and to master both the formal writings and the applications on real data.
Course outline (subject to change depending on time available) 1. Introduction and motivations 2. The simple linear regression model 3. The multiple linear regression model 4. Main deviations from the assumptions of good practice in MCOs 5. Introduction to discrete choice models 6. Introduction to time series and forecasting models
The evaluation is done through a written examination that counts for 70% of the final grade. The examination is based on the resolution of questions and exercises relating to both the course and the theoretical and practical exercises in an integrated manner. An assignment on R, to be completed in a small group, will be due at the end of the semester and will count for 30% of the final grade.
Brooks, C. (2019), Introductory Econometrics for Finance, Cambridge Univ. Press, 4th Ed. Crépon, B. and N. Jacquemet (2018), Econometrics: Methods and Applications, De Boeck, 2nd Ed. Heij, C., de Boer, P., Franses, P.H., Kloek, T., and H. K. van Dijk (2004), Economic Methods with Applications in Business and Economics, Oxford Univ. Press.
| Training | Study programme | Block | Credits | Mandatory |
|---|---|---|---|---|
| Bachelor in Business Engineering | Standard | 0 | 5 | |
| Bachelor in Business Engineering | Standard | 3 | 5 |