For students:

Advanced Econometrics 3: Macroeconometrics (5 cr)

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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:
Remote teaching
Venue:
Economicum building
Remote:
Zoom link can be found in Moodle
Enrollment:
Sisu How to enroll?

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

Content

This course covers a number of models and methods employed in time series econometrics. The emphasis is on 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

Teaching

  • Completion method: remote teaching
  • Schedule: can be found in Course Page and Sisu
  • Study materials: can be found in Moodle
    • For some courses, it is enough to register in Sisu and you can access directly the Moodle area, please note, however, that it may take up to two hours after registration to enter the Moodle area.
    • Log in with your UH username to be able to use all the features of the course workspace
    • More tips for enrolling in Moodle can be found here

Please register for the course in the UH Sisu with your UH username. Further instructions can be found here.

University-specific instructions

Aalto University Students
  • Code: ECON-L4300
  • Target groups: PhD / rMSc
  • Credit points: 5
  • Credit transfer: apply for substitution in Sisu

Further information on credit transfer can be found here.

Hanken Students
  • Code: 26055
  • Target groups: PhD / rMSc
  • Credit points: 5
  • Credit transfer: apply for substitution in Sisu

Further instructions on credit transfer can be found here.

University of Helsinki Students

  • Code: COM-R321 (rMSc code) / DPE-9321 (PhD code)

  • Target groups: PhD / rMSc

  • Credit points: 5

FDPE Students Students

  • Target groups: PhD

  • Credit points: please check your curriculum

  • Credit transfer: please apply for credit transfer according to your home university's procedures

Further instructions can be found here.

Learning outcomes

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