Advanced Econometrics 3: Macroeconometrics (5 cr)

Code:
ECOM-R321/DPE-9321
Field:
Econometrics
Targets:
Research Master's students PhD students
Organiser:
University of Helsinki - Economics
Instructor:
Mika Meitz
Period:
Period 3
Format:
Lecture
Method:
Online teaching
Remote:
Zoom link can be found in Moodle
Enrollment:

In case of conflicting information consider the Sisu/Course/Moodle pages the primary source of information.

Aalto and Hanken economics students can enroll in their home university’s SISU! Further instructions can be found on the How to enroll page, also for other students.

Before taking and completing the course make sure that the credits can be counted towards your degree at your home university by checking which courses are included in your curriculum or by contacting your home university’s student/learning services.

Please note that there is a different code for UH PhD students: DPE-9321

  • To access the Moodle course area, use all the features and participate in the activities (assignments, discussions), you must have successfully registered for the course in Sisu and logged in with your UH user ID.
  • For more information on how to activate your UH user ID and register for a Moodle course area, click here.

This course covers a number of models and methods employed in time series econometrics. The emphasis is on stationary univariate models, but vector autoregressive models and nonstationarity 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

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