Quantitative Foundations for Econometrics (ETS-620)

Statistics attempts to make evaluations concerned with uncertainty and numerical conjectures about perplexing questions. The focus of the course is upon understanding real-life statistical problems. The course Quantitative Foundations of Econometrics is all about how to deal with some interesting problems statistically, why these methods work, and what to watch out for when others use them. This course develops a foundational understanding of the quantitative tools essential for econometric analysis. It begins with descriptive statistical methods, probability theory, and progresses to random variables, distributions, and statistical inference. The course then transitions into econometric modeling frameworks, including linear regression, multivariate models, dynamic models, and simultaneous equation systems. The approach emphasizes real-world applications, data visualization, and critical interpretation of statistical results with statistical reasoning.

This course provides the essential mathematical and statistical foundations necessary for the study of econometrics. It is designed to prepare students for more advanced knowledge in econometric theory and applied empirical analysis. This unique course offers a deep learning experience to students who make an effort. It requires a lot of practical work from the students. More than teaching about manipulation of numbers, this course is meant to teach students how to construct arguments, and how to avoid being deceived by data. Therefore, practical examples from economics are extensively used throughout to illustrate key concepts.