Statistics and Applied Econometrics : Introduction

Description

This course aims to introduce students to the practical application of econometric methods discussed in the Statistics and Econometrics I course. The core focus of the course is on distinguishing between correlation and causality, and it presents econometric methods that allow for the evaluation of the causal impact of an intervention. This course has three main objectives: Understand the usefulness of statistics and econometrics in providing causal answers to various questions. Learn how to use Python for data analysis and econometrics, while leveraging current generative AI tools to support learning and Python code development. Learn to apply the concepts of causal inference in everyday life to make better decisions. Course structure : The course consists of theory and application classes complemented by laboratory sessions that allow students to learn how to use Python. Laboratory sessions : In the laboratory sessions, we do applied econometrics and reproduce the results of the theory sessions. To do this, we use Python and Generative AI to help us code. Q&A sessions: Every week, starting in week 2, we offer Q&A sessions. You can ask questions about the course, the lab sessions and later in the semester about the project. To encourage you to get together and exchange ideas, we have reserved rooms for these sessions. FAQ on moodle. We also have FAQ (frequently asked questions) on the Moodle page. You should consult it before asking any questions. We update it with the questions we receive during the semester. Assessment Information: Final exam: Yes Evaluation Methods The course evaluation consists of a final exam and a group project, which must be submitted at the end of the semester. 1. Written Exam Duration: 2 hours Documentation allowed 2. Group Project Groups of 3 to 4 students 8 weeks to complete the project (see the detailed schedule at the end of the syllabus) Required submissions (5 files): Do-file Log-file Database file Excel file PDF document Important : If any of these five files is missing, the group will receive no grade for the project. Final Grade Calculation Final Grade=(0.2×Project)+(0.8×Exam) Retake Exam If you need to take a retake exam, only the resit exam grade will count. The project grade will not be included. Retake Exam : 2-hour written exam, documentation allowed.