Applied Macroeconometrics 1 (5 cr)

The course provides an introduction to the methods of modern applied macroeconometrics. The main emphasis is on the vector autoregressive (VAR) model, but other approaches employed in applied work are also briefly reviewed, and their relation to the structural VAR model is discussed. In particular, we concentrate on the identification of economic shocks by various methods and the use of the structural vector autoregressive framework in empirical research and policy analysis. Classical statistical inference in reduced-form and structural VAR models as well as tools of structural analysis are covered. The course starts with a review of the reduced-form VAR model, followed by tools of structural analysis in the VAR framework, including the impulse response function, forecast error variance decomposition, historical decomposition and counterfactual analysis. The identification of structural VAR models by short- and long-run identification restrictions as well as identification using statistical properties of the data is next covered. The structural VAR approach is contrasted with alternatives, including DSGE and dynamic simultaneous equations models. The emphasis is on practical application of the methods discussed in modelling macroeconomic and other data. Although various alternative approaches put forth in the previous economic literature are briefly reviewed, in this course, we concentrate on the linear VAR model, which is the most widely employed framework in applied research and policy work.

After the course, the student should

In order to reach the goals, the course consists of lectures, homework assignments and a term paper. The homework consists of both theoretical problems and empirical hands-on applications that involve actual economic data. The practical use of the methods is demonstrated using the R software, but any suitable software package can be used for homework assignments (although R is recommended).

Autopilot learning offers students the opportunity to learn course material (including video lectures and assignments / exercises) independently and start the course at any time. This provides a great deal of flexibility since courses are now available continuously instead of the traditional teaching format. The course begins by signing up for Sisu and sending an email to the course instructor (Henri Nyberg, henri.nyberg@utu.fi) to obtain the enrollment key for the course website on Moodle. The course implementation is then based on completing the "lecture rounds", including assignments, a term paper, and then taking the course exam (in this order). The course material is organized so that each step requires you to complete the previous steps (lecture rounds and assignments) first, and then the next step opens automatically. The course grade is based on assignments (returning the learning diary), a term paper, and an exam. The term paper must be submitted prior to the exam, which will be taken through Examination system. The total grade of the course is the weighted averaged of the exam, the homework assignments, and the term paper (details of grading will be here later on) Approved (grades 1-5) course exam, assignments (including learning diary) and the term paper are required to pass the course.