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The course provides an introduction to the methods of modern applied macroeconometrics. The different approaches currently employed in applied work are reviewed, including the basics of empirical dynamic stochastic general equilibrium (DSGE) models, but the main emphasis is on the vector autoregressive model and its application in economics. In particular, we concentrate on the identification of economic shocks by various methods and the use of the structural vector autoregressive framework in policy analysis. Applications in other fields besides macroeconomics may also be discussed. The emphasis is on the practical application of the methods.

  • Completion method: hybrid teaching = contact and remote teaching
  • Schedule: can be found in Course 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

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

    • Code: no equivalent code

    • Target groups: MSc / rMSc / PhD

    • Credit points: 5

    • Credit transfer: apply for inclusion in Sisu

    Further instructions (link to be added here later)

    • Code: 26002

    • Target groups: MSc / rMSc / PhD

    • Credit points: 5

    • Credit transfer: apply for substitution in Sisu

    Further instructions (link to be added here later)

    • Code: ECOM-411 (rMSc) / DPE-9411 (PhD)

    • Target groups: MSc / rMSc / PhD

    • Credit points: 5

    • Please contact your supervisor/program director to be sure that the course credit can be counted towards your degree

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

    Further instructions (link to be added here later).Further instructions (link to be added here later).

After the course, the student should:

  • Be familiar with the main approaches to modelling macroeconomic data 
  • Know the basic properties of the linear vector autoregressive (VAR) model 
  • Know the basic properties of the linear vector autoregressive (VAR) model 
  • Understand the concept of the identification of economic shocks in structural VAR models, and be able to conduct structural analysis using short-run and long-run identification restrictions as well as methods of statistical identification in the VAR model
  • Be able to apply methods of classical statistical inference in reduced-form and structural VAR models
  • Be able to report empirical research results obtained using the methods covered