Магистратура
2025/2026
Эконометрика временных рядов
Статус:
Курс обязательный (Аналитика данных для бизнеса и экономики)
Кто читает:
Департамент экономики
Где читается:
Санкт-Петербургская школа экономики и менеджмента
Когда читается:
2-й курс, 2 модуль
Охват аудитории:
для своего кампуса
Преподаватели:
Скоробогатов Александр Сергеевич
Язык:
английский
Кредиты:
3
Course Syllabus
Abstract
Time series analysis is one of the natural extensions of Econometrics I and other corresponding econometrics related courses. The focus of the course is adopting and extending techniques and results from the baseline econometrics courses to the case of time series related theoretical and empirical problems
Learning Objectives
- supposed to provide the students with a set of tools that are useful for both theoretical and empirical modeling of dynamic economic data coming in the form of both univariate and multivariate time series
- content covers (but not limited to) an overview of the crucial theoretical results of contemporary time series econometrics and of the approaches towards empirical application of these results to empirical data and tasks, including estimation of dynamic economic models and practical forecasting
Expected Learning Outcomes
- students will be able to statistically describe and analyze various dynamic economic data coming in the form of time series
- construct and analyze models of the corresponding economic processes, to construct relevant predictions of the data
Course Contents
- 1. Introduction
- 2. ARMA process
- 3. Unit root tests
- 4. Seasonality in ARIMA model
- 5. ARIMAX and SARIMAX models
Assessment Elements
- Midterm exam
- Final examThe exam lasts 80 minutes. The student has to solve 10 exercises where each exercise gives either 1 or 0 points. The sum of the points is the examination mark. If the script does not work, the student receives 0 for the whole exam. This is an open book test.
Bibliography
Recommended Core Bibliography
- Levendis, J. D. (2018). Time Series Econometrics : Learning Through Replication. Cham, Switzerland: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2016053
Recommended Additional Bibliography
- Gujarati, D. (2014). Econometrics by Example (Vol. 2nd ed). Basingstoke: Palgrave Macmillan. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1525312
- James Douglas Hamilton. (2020). Time Series Analysis. Princeton University Press.