Machine Learning in Economics

2025/2026

Учебный год

ENG

Обучение ведется на английском языке

Кто читает:

Департамент экономики

Статус:

Курс обязательный

Когда читается:

2-й курс, 1, 2 модуль

Преподаватель

Сысоев Дмитрий Сергеевич

Course Syllabus

Abstract

Economists use time-series methods in many circumstances. They estimate economic models, build policy analyses and forecast economic variables. In this course we will cover some crucial concepts to establish a solid background for diving deeper in the world of time-series econometrics. For some of the methods we will go into details to learn why and how they work. We will revisit concepts like stationarity, consistency, asymptotic normality.

Learning Objectives

• tudents will feel comfortable orienting among different statistical methods and develop a feeling of why these methods work and how to extend them

Expected Learning Outcomes

• Learn more details on hypotheses testing and concepts like stationarity, and ergodicity
• Understand different methods for supervised learning such as linear regression, logistic regression, classification tools
• Understand different methods for unsupervised learning such as principal component analysis, k-means clustering
• Understand the concept of data generating process and how it is different to the concept of model

Course Contents

• Opening and Intro to TS concepts
• Probability Models and Data Generating Processes
• Practical differences between machine learning and statistical approaches
• Presentations and Questions

Assessment Elements

• Exam
• Assignment
• Kaggle competition

Interim Assessment

• 2025/2026 2nd module
  0.3 * Assignment + 0.5 * Exam + 0.2 * Kaggle competition

Bibliography

Recommended Core Bibliography

• Brockwell, P. J., & Davis, R. A. (2002). Introduction to Time Series and Forecasting (Vol. 2nd ed). New York: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=108031

Recommended Additional Bibliography

• Ragnar Nymoen. (2019). Dynamic Econometrics for Empirical Macroeconomic Modelling. World Scientific Publishing Co. Pte. Ltd. https://doi.org/10.1142/11479

Authors

• BRODSKAYA NATALYA NIKOLAEVNA