Data-Driven Economics
Sapienza University of Rome · M.Sc. in Data Science
Overview
This course introduces the theoretical and practical foundations of econometric analysis.
It covers regression models (linear and non-linear), estimation and inference procedures, and the analysis of both cross-sectional and longitudinal data.
Main objectives
- Learn the basics of simple and multiple regression models
- Apply econometric models to analyze empirical economic problems
- Understand both linear and non-linear models
- Develop skills to establish causal relationships between economic variables
- Gain practical experience through laboratory sessions using real data
Learning outcomes
- Ability to design and estimate econometric models for empirical applications
- Critical evaluation of empirical studies in economics and management
- Communication of econometric results to both technical and non-technical audiences
- Independent capability to perform empirical analyses considering uncertainty and risk
My work in this course
- Notes & Materials
- Final project