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Regular version of the site

Times Series Econometrics

2026/2027
Academic Year
ENG
Instruction in English
3
ECTS credits
Course type:
Compulsory course
When:
2 year, 1 module

Instructor

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
    The 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.
Interim Assessment

Interim Assessment

  • 2026/2027 1st module
    0.4 * Midterm exam + 0.6 * Final exam
Bibliography

Bibliography

Recommended Core Bibliography

  • Time series econometrics : learning through replication, , 2019

Recommended Additional Bibliography

  • Econometrics by example, Gujarati, D., 2012
  • Time series analysis, Hamilton, J. D., 1994

Authors

  • Brodskaia Natalia Nikolaevna
  • Skorobogatov Aleksandr Sergeevich