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

This course covers a number of models and methods employed in time series econometrics. The emphasis is on univariate models, but vector autoregressive modelsĀ 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
  • Completion method: remote teaching
  • Schedule: can be found in Courses Page and Sisu
  • Study materials: can be found in Moodle
    • A link and a Moodle course key will be sent by email before the course starts and/or they will be provided on the Courses page: you can view the information on this site without logging in or registering, but some of the content added by teachers to course pages may be available to course participants only, for example Moodle course enrolment key.
    • Log in with your UH username to be able to use all the features of the course workspace
  • Self study material to be studied before the course starts (link to be added here later)

Please register for the course in the UH Sisu with your UH username. Further instructions (link to be added here later).

    • Code: ECON-L4300

    • Target groups: PhD / rMSc / MSc

    • Credit points: 5

    • Credit transfer: apply for substitution in Sisu

    Further instructions (link to be added here later)

    • Code: 26055

    • Target groups: PhD / rMSc / MSc

    • Credit points: 5

    • Credit transfer: apply for substitution in Sisu

    Further instructions (link to be added here later)

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

    • Target groups: PhD / rMSc

    • Credit points: 5

    • 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 (link to be added here later).

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