Ausgewählte Themen in Finance and International Economics: Time Series Methods in Macroeconomics & International Finance
Name of module in english: Time Series Methods in Macroeconomics & International Finance
Exam number: 6862
Semester: from 1st semester
Duration of the module: One Semester
Form of the module (i.e. obligatory, elective etc.): Elective
Frequency of module offer: irregulary
Prerequisites: 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.
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, tutorial etc.) 30 h; self-study: 150 h
Contact hours (per week in semester): 3
Methods and duration of examination:
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. Deadlines will be announced during the course. 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.
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 email@example.com, with emails of all group members inserted on CC.
A final individual assignment (weight: 55 %). We will anounce the exact form of the final individual assignment later.
Most likely: Exam at the Viadrina
Maybe: Online Assignment but with tracking software installed on your devices.
Maybe: The FIA will be one additional group assignment
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 https://www.edx.org/course/macroeconometric-forecasting 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.
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.
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.
Registration in Moodle Viadrina required.