Banner Viadrina

Time Series Methods in Macroeconomics & International Finance

First version – Adjustments and exact dates will follow

Exam number: xxx

Semester: from 4th semester (Schwerpunktbildung)

Duration of the module: One semester

Form of the module (i.e. obligatory, elective etc.): Elective

Frequency of module offer: irregularly


The students should be able to analyse macroeconomic shocks in the IS-LM-model and the AS-AD-model in a verbal, graphical, and formal way. The students should be able to apply mathematical concepts such as the differential and Cramer's rule.

Furthermore, the students should have some background in statistics and should be able to construct and interpret confidence intervals, hypotheses tests and univariate regressions. 

All courses from the „orientation phase” should be completed.

Applicability of module for other study programmes:
Obligatory or elective in other study programmes. For further information check regulations of the study programme.

Person responsible for module: Prof. Dr. Georg Stadtmann

Name of the professor: Prof. Dr. Georg Stadtmann

Language of teaching: English

ECTS-Credits (based on the workload): 6

Workload and its composition (self-study, contact time):
Contact time (lecture, tutorials, seminar etc.) 30 h; self-study: 150 h

Contact hours (per week in semester): 3

Methods and duration of examination:

Part 1: Three group assignments (weight: 3 * 15 % = 45 %). The group work is spread over the semester. The group works are to be submitted by email. Afterwards a quiz will be held on Moodle to test the knowledge and results of the group work. Every student has to participate in the quiz. The individual answers determine the partial grade.

Form groups of 3 – 5 students.

 When turning in your first group assignment, please indicate full name and matriculation numbers of all group members (minimum 3, maximum 5 students). The submitted information from the first group assignment is retained and we know by then which student belongs to which group.
You SHOULD only inform us well ahead of the distribution of the first group assignment if you are not able to form a group, so that we can assist!

All students receive an E-Mail and a Moodle message with a set of assignment questions or case study.

You have about 7 – 14 days to complete the work. Students are thus required to form their group ahead of time, organize themselves and start working on the assignment as soon as assignments are distributed. 

ReceiveTurn in 11:59 AM (mid of the day)
Group assignment 1April 16thApril 23rd
Group assignment 2 May 3rdMay 14th
Group assignment 3May 17thMay 28th

 You turn in the assignment BEFORE (not after) the deadline via E-Mail. Even the minute counts! Only the group speaker sends an E-Mail to, with emails of all group members inserted on CC.

After the deadline, a Moodle multiple choice questionnaire opens up at 12:00.

Every student has to participate in this online assignment. You have about 30 minutes to complete the online assignment. More or less, you have to transfer the results of your group assignment by answering all the questions.

Since every student has to give an interpretation of the group work, we make sure that every students has participated in the group work. It should be impossible, that one students just says: “Yes, please, also put my name on the first page of the group assignment.”

In case that the Moodle system breaks down, because of server problems / internet problems: Please send an email directly (within the 30 minutes time period) to

Part 2: A final individual assignment (weight: 55 %). The individual assignment replaces the normally planned exam. For the individual assignment, the student has about 2 hours of processing time. Afterwards, the results are to be applied in a 30-minute Moodle Quiz. 

Right now, it is planned that the final assignment takes place on xxxday June xxx, 2021.

At xx:00 AM, all students get access to the assignments via E-Mail and/or Moodle. You have 2 hours to solve a problem set in a WORD or EXCEL or EVIEWS file.

In order to prevent cheating, it is planned to have slightly different versions of the problem set.

It is an “open book – open note” assignment, however cooperation between students is not allowed.

From 11:00 to 11:10 you have to save the WORD and/or EXCEL/EVIEWS files and turn them in via E-Mail:

From 11:15 to 11:45, a questionnaire survey in Moodle takes place. You have to answer questions which are to some extend related to the assignments which you previously solved in your WORD and/or EXCEL/EVIEWS files. Answers in the files and Moodle should be consistent.

In case that the Moodle system breaks down, you directly have to inform Mr. Saß via E-Mail.

Emphasis of the grade for the final grade: Please check regulations of the study programme

Aim of the module (expected learning outcomes and competencies to be acquired):
The purpose of the course is to introduce the students to some of the most widely used methods in time series econometrics. In addition, the students get hands-on experience analyzing economic data by using Excel and EVIEWS.

  • Evaluation of macroeconometric models
  • Stationarity of time series
  • Forecasting of uncertainty and forecasting for policy analysis
  • Properties of time series data and model design
  • Dynamic specification and the use of vector auto-regression models (VARs) and error correction models (VECMs)

A second goal of the course is to expose students to massive open online courses (MOOC). This should prepare students for their own life long learning process. We follow the course

Macroeconomic forecasting provided by the International Monetary Fund. The course content, slides are available and videos are recorded by external lecturers. In the online sessions at the Viadrina, we will discuss these lecturers, give additional examples. We will use EVIEWS as an econometric software.

The final grade results from the weighted average of the single graded parts. 

Emphasis of the grade for the final grade:

Aim of the module (expected learning outcomes and competencies to be acquired):

Contents of the module:

Module 1: EVIEWS Basics

Review of the main EVIEWS commands to manage data.

Module 2: Introduction to Forecasting with EVIEWS

Introduction to the EVIEWS model simulator to estimate and forecast multiple equation models.

Module 3: Statistical Properties of Times Series Data

The concept of stationarity is defined as well as how to test for it. Box-Jenkins (ARMA) methodology to study time series is introduced.

Module 4: Forecast Uncertainty and Model Evaluation

How best to choose between forecasts from competing models or sources. Participants will learn the main forecast evaluation statistics and how to calculate them in EViews.

Module 5: Vector Auto-Regressions (VARs)

Understand VARs, how they used for forecasting and structural analysis, and how to estimate a well-specified VAR and generate forecasts.

Module 6: Cointegration and Vector Error Correction Models (VECMs)

Define and understand the concept of cointegration among unit-root variables and its implications for forecasting. Learn how to test for cointegration using the Johansen method and how to estimate and forecast using a VECM.

Module 7: Evaluating Regressions Models

What does it mean to have a “good model” (model evaluation and key model assumptions) and the consequences for forecasting. Introduction to model testing and dealing with error irregularities and structural breaks.

Module 8: Final Assignment: Bringing It All Together

An overview of the techniques studied is provided using a case study focused on private saving-consumption behavior in the U.S. before and after the global financial crisis.

Students acquire the competence to manage work and master situations that are complex, unpredictable and require new solutions. This competence is practiced in 3 group assignments which should be solved in a group of 3-5 students. Group assignments train the competence to initiate and implement research activities within a professional cooperation and take on professional responsibility. The results of the weekly assignments are presented by one group of students to train the skills to present and communicate research based knowledge in a professional manner. Subsequent class discussions train the communication competencies of the group as well as their classmates.

In order to strengthen the competencies to independently take responsibility for own professional development and specialization an individual written assignment is also a part of the overall grade. This will also strengthen the skills to structure economic thinking and to communicate with professionals and non-specialists in a written form.

Exercise Class/Tutorial:

Review of some basics of statistics and linear OLS regression.
Discussion of problems relating to models of macroeconomics and international finance which are content of the lecture.
A discussion of the group assignments.

Teaching and learning methods:
Lecture with tutorials, self-studies

Literature (compulsory reading, recommended literature):

Will be listed on Moodle.

Further information:
Registration in Moodle Viadrina required.