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Nr. LV-Typ(en) LV-Titel
5131 PI Macroeconometrics (Applied Track) Präsenz-Modus
Anmeldung über LPIS
vom 19.02.2024 15:00 bis 25.02.2024 23:59
Abmeldung über LPIS
vom 19.02.2024 15:00 bis 27.02.2024 23:59

LV-Leiter/in Dr. Thomas Zörner, BA, MSc (WU)
Planpunkte Master Macroeconometrics
Semesterstunden 2
Unterrichtssprache Englisch

Termine
Fr, 01.03.2024 09:00-11:00 Uhr D4.0.144 (Lageplan)
Fr, 08.03.2024 09:00-11:00 Uhr D4.0.133 (Lageplan)
Fr, 15.03.2024 09:00-11:00 Uhr TC.5.03 (Lageplan)
Fr, 22.03.2024 08:00-10:00 Uhr D4.0.144 (Lageplan)
Fr, 12.04.2024 09:00-11:00 Uhr D4.0.133 (Lageplan)
Fr, 19.04.2024 09:00-11:00 Uhr TC.4.02 (Lageplan)
Fr, 26.04.2024 09:00-11:00 Uhr D4.0.133 (Lageplan)
Fr, 03.05.2024 09:00-11:00 Uhr D4.0.144 (Lageplan)
Fr, 10.05.2024 09:00-11:00 Uhr D4.0.144 (Lageplan)
Fr, 17.05.2024 09:00-11:00 Uhr D4.0.144 (Lageplan)
Fr, 24.05.2024 09:00-11:00 Uhr D4.0.144 (Lageplan)
Fr, 31.05.2024 09:00-11:00 Uhr D4.0.144 (Lageplan)
Fr, 07.06.2024 09:00-11:00 Uhr D4.0.144 (Lageplan)
Fr, 14.06.2024 09:00-11:00 Uhr D4.0.144 (Lageplan)
Fr, 21.06.2024 09:00-11:00 Uhr D4.0.144 (Lageplan)
Fr, 28.06.2024 09:00-11:00 Uhr D4.0.144 (Lageplan)
Termindownload (ical) | Termine abonnieren

Weitere Informationen https://learn.wu.ac.at/vvz/24s/5131

Kontakt:
thomas.zoerner@wu.ac.at
Inhalte der LV:

This course deals with multivariate time series analysis from an applied perspective. After briefly refreshing the knowledge about univariate time series models (ARMA) we will continue with the analysis of the multivariate case (VARs) and its extensions to incorporate structural characteristics (SVAR). After discussing the estimation routines in more depth, we will tackle the problem of identifying the nature of the structural shocks (short- vs. long-run restrictions and sign restrictions) to derive some recommendations for policymakers based on an impulse response analysis. Moreover, this course provides a brief introduction to the Bayesian paradigm in econometrics and its advantages compared to the frequentist approach.

Lernergebnisse (Learning Outcomes):

The course will be helpful for students interested in working at research institutions or financial institutions. Rather than focus narrowly on the application of econometric tools in macroeconomics, we will try to convey a deeper understanding of the most important tools used in applied time series analysis, their proper use and their limitations, illustrated by applications to questions considered in macroeconomics. The discussed methods are used heavily in Central Banks and policy institutions and will be covered with a special emphasis on their applications and interpretations. Finally, the students will be enabled to conduct own small research projects applying time series analysis.

Regelung zur Anwesenheit:

Attendance is mandatory (however, two missed units are tolerated)

Lehr-/Lerndesign:

This lecture consists of two main blocks. While in the first block we are discussing the topics mentioned in the syllabus (slides, literature, and papers will be provided), the second block is dedicated to students' presentations of famous examples in the VAR literature.  The group presentation (max. 5 students) is dedicated to a famous example in the VAR literature. It is expected that the group scrutinizes the paper in depth (objective, relevant assumptions, model framework, and results) and provide (a) a detailed discussion as well as (b) comments/questions/suggestions to the authors.

Please make sure that you read the assigned literature PRIOR to the lecture.

Leistung(en) für eine Beurteilung:

The course grade will be based on the following components:

  • Final exam (40 points)
  • Paper presentation (30 points)
  • Exercises (30 points)

The final exam will consist of a mix of multiple-choice and open-ended questions, and will last for 90 minutes. It is currently planned to take place in person on campus.

A positive final test (50% threshold of total exam points) is required for passing the course.

Grading Key: <60Points: fail; >60Points: sufficient; >70Points: satisfactory; >80points: good; >90Points: very good.

Teilnahmevoraussetzung(en):

Students should have a sound knowledge of statistics (probability, random variables, expectations, joint/conditional distributions), mathematics (linear algebra, differential/integral calculus, algebra) and basic econometrics (OLS/ML estimation). moreover, it is expected that the students are familiar with univariate time series econometrics (if not, it is expected that students refresh their knowledge with "Applied Econometric Time Series" by Enders (CH1-4).)

Zuletzt bearbeitet: 15.01.2024 15:14

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