Econometrics

This course aims at providing a comprehensive understanding of the theoretical foundations of econometrics, including key statistical concepts and their application in economic modeling. Fundamental methods and concepts in econometrics, such as linear regression and endogeneity, will be introduced and discussed throughout the course.
The course will promote a critical assessment of the assumptions underlying econometric analysis of real-world data, fostering ability to connect theory and applications, enabling students to apply their knowledge to answer empirically relevant questions.

At the end of the course students are expected to be able to:
- Define and comprehend key concepts in econometrics, including basic assumptions underlying econometric models.
- Apply fundamental statistical techniques, such as regression analysis, to analyze economic data and draw meaningful conclusions.
- Develop proficiency in using econometric software (e.g., STATA) for data analysis, model estimation, and interpretation, with a focus on real-world applications.
- Critically assess the appropriateness of econometric models, considering issues such as multicollinearity, heteroscedasticity, and endogeneity, and be able to provide remediation.
- Interpret and communicate the results of empirical analyses in a coherent and meaningful way, taking into account the economic and statistical significance of the findings.