• A
  • A
  • A
  • АБB
  • АБB
  • АБB
  • А
  • А
  • А
  • А
  • А
Обычная версия сайта
Магистратура 2024/2025

Эконометрика временных рядов

Статус: Курс обязательный (Аналитика данных для бизнеса и экономики)
Направление: 38.04.01. Экономика
Когда читается: 2-й курс, 2 модуль
Формат изучения: без онлайн-курса
Охват аудитории: для своего кампуса
Прогр. обучения: Аналитика данных для бизнеса и экономики
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

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

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

Course Contents

  • 1. Introduction
  • 2. ARMA process
  • 3. Unit root tests
  • 4. Seasonality in ARIMA model
  • 5. ARIMAX and SARIMAX models
Assessment Elements

Assessment Elements

  • non-blocking Midterm exam
  • non-blocking Final exam
Interim Assessment

Interim Assessment

  • 2024/2025 2nd module
    0.6 * Final exam + 0.4 * Midterm exam
Bibliography

Bibliography

Recommended Core Bibliography

  • Makridakis, S., Wheelwright, S. C., & Hyndman, R. J. (1998). Forecasting: Methods and Applications. Cyprus, Europe: John Wiley & Sons, Inc. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.F848CE7

Recommended Additional Bibliography

  • Hamilton, J. D. . (DE-588)122825950, (DE-576)271889950. (1994). Time series analysis / James D. Hamilton. Princeton, NJ: Princeton Univ. Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.038453134

Authors

  • BRODSKAYA NATALYA NIKOLAEVNA