Бакалавриат
2020/2021
Применение машинного обучения в экономике
Лучший по критерию «Новизна полученных знаний»
Статус:
Курс по выбору (Экономика)
Направление:
38.03.01. Экономика
Кто читает:
Департамент экономики
Где читается:
Санкт-Петербургская школа экономики и менеджмента
Когда читается:
4-й курс, 2, 3 модуль
Формат изучения:
с онлайн-курсом
Преподаватели:
Дуплинский Артем Александрович,
Жижин Леонид Алексеевич,
Фролова Виктория Александровна
Язык:
английский
Кредиты:
6
Контактные часы:
56
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
- Students 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
- Understand the concept of data generating process and how it is different to the concept of model
- Learn more details on hypotheses testing and concepts like stationarity, and ergodicity
Course Contents
- Opening and Intro to TS concepts
- Probability Models and Data Generating Processes
- Presentations and Questions
- Asymptotic Results for Unit-root processes
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