ECON 4440

Time Series in Economics

Lec 01 selected

This is a course in econometrics that focuses on time series models. The topics cover estimation and inference procedures for univariate and multivariate time series models with stationary and nonstationary data, including vector autoregressive models and Markov switching models.

Sections

Lecture

From the syllabus

From the Winter 2026 syllabus by Christos Ntantamis. Winter 2027 is taught by Kotlyarova Y., so details may differ. Open the PDF

Grading

25%Data assignments (5)Lowest assignment dropped
25%Midterm examFebruary 23; tentative
50%Final examMust score at least 40% to pass; closed book

Textbooks

  • Introduction to Econometrics, 4th Edition, James H. Stock and Mark W. Watson
  • Introductory Econometrics: A Modern Approach, 7th Edition, Jeffrey M. Wooldridge
  • Time Series Analysis, Hamilton (optional)
  • The Econometric Modeling of Financial Time Series, Mills and Markellos (optional)

Course rules

Late assignments
Assignments are marked down 20% per day late; exceptions require a legitimate reason under university regulations.
Missed assignment
Contact the instructor before the deadline and submit an SDA; the missed assignment weight is redistributed across other assignments.
Missed midterm
Contact the instructor before the exam and submit an SDA; the midterm weight is added to the final exam.
Missed final
For a valid reason, notify the instructor immediately and arrange a makeup exam.
Exams
Exams are closed book, and there is no supplemental privilege.
Assignments
Assignments are individual; copying or cooperation is not permitted, and students should refrain from using generative AI.
SDA limit
The Student Declaration of Absence form may be used only twice during the term.

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