Kaisa_2012_3_photo by Veikko Somerpuro

Enrol
12.12.2019 at 09:00 - 16.1.2020 at 23:59

Timetable

Here is the course’s teaching schedule. Check the description for possible other schedules.

DateTimeLocation
Thu 16.1.2020
14:15 - 15:45
Fri 17.1.2020
12:15 - 13:45
Thu 23.1.2020
14:15 - 15:45
Fri 24.1.2020
12:15 - 13:45
Thu 30.1.2020
10:15 - 11:45
Thu 30.1.2020
14:15 - 15:45
Fri 31.1.2020
12:15 - 13:45
Thu 6.2.2020
14:15 - 15:45
Fri 7.2.2020
12:15 - 13:45
Thu 13.2.2020
10:15 - 11:45
Thu 13.2.2020
14:15 - 15:45
Fri 14.2.2020
12:15 - 13:45
Thu 20.2.2020
10:15 - 11:45
Thu 20.2.2020
14:15 - 15:45
Fri 21.2.2020
12:15 - 13:45
Thu 27.2.2020
10:15 - 11:45
Fri 6.3.2020
10:00 - 12:00
Wed 29.4.2020
10:00 - 12:00

Description

Master’s Programme in Economics (Research track). Open also to doctoral students in economics.

Advanced Econometrics 1 and 2

Knowledge of R (or some other matrix programming language) is useful.

After the course, the student should

  • Know the basic properties of the time series models and the related methods introduced
  • Be able to critically follow empirical research that employs them
  • Be able to apply them in empirical research
  • Have the basic knowledge for more advanced methodological and applied studies in time series econometrics

Annually in the third period

This course covers a number of models and methods employed in time series econometrics. The emphasis is on univariate models, but vector autoregressive models are also discussed. Specifically, the topics covered on the course include the following:

  • Basic time series concepts
  • Methods for stationary univariate data: ARMA models, ARCH models
  • Nonstationarity (unit roots, cointegration)
  • Vector autoregressive models

Lecture slides and other material assigned by the lecturer

All material related to the course is delivered through the Moodle area of the course, which also contains a discussion forum where students can discuss issues related to the course with each other and the teacher.

The grade on a scale from 0 (fail) to 5 is based on the points earned in the final exam. At least 40% of the homework assignments must be completed to take the exam.

The course consists of lectures (24 hours) and exercise sessions (8 hours), where solutions to the homework assignments are discussed. The lectures and exercise sessions are not mandatory. The course is completed by (i) a written final exam and (ii) homework assignments. The homework assignments consist of both analytical and empirical exercises.