040057 KU Macroeconometrics (MA) (2023S)
Prüfungsimmanente Lehrveranstaltung
Labels
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Mo 13.02.2023 09:00 bis Mi 22.02.2023 12:00
- Anmeldung von Mo 27.02.2023 09:00 bis Di 28.02.2023 12:00
- Abmeldung bis Fr 17.03.2023 23:59
Details
max. 50 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
Freitag
03.03.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
07.03.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
10.03.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
14.03.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
17.03.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
21.03.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
24.03.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
28.03.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
31.03.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
18.04.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
21.04.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
25.04.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
28.04.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
02.05.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
05.05.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
09.05.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
12.05.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
16.05.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
19.05.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
23.05.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
26.05.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
02.06.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
06.06.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
09.06.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
13.06.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
16.06.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
20.06.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
23.06.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Dienstag
27.06.
11:30 - 13:00
Hörsaal 9 Oskar-Morgenstern-Platz 1 1.Stock
Freitag
30.06.
13:15 - 14:45
Hörsaal 8 Oskar-Morgenstern-Platz 1 1.Stock
Information
Ziele, Inhalte und Methode der Lehrveranstaltung
Art der Leistungskontrolle und erlaubte Hilfsmittel
The evaluation consists of three components: midterm take-home exam (20%), final take-home exam (30%), and an empirical project (50%). The empirical project consists of writing a short paper (40%), presenting own results (10%) and discussing the results of fellow students. The take-home exams are open book, that is, students may use any materials or software if they are properly referenced. Each task must be handed in as a single PDF file. There will also be sporadic homework that may be solved at home and presented in class for bonus points.
Mindestanforderungen und Beurteilungsmaßstab
There are no "official" mandatory preliminary requirements for taking this class. It will be beneficial to have prior knowledge of linear algebra and probability & statistics, alongside classical econometrics and statistical software. We will, however, revisit all required concepts at the beginning of the semester. A positive grade requires 50% of the achievable points.
Prüfungsstoff
The course comprises 2 lectures of 1.5h per week covering both theory and empirical examples. Slides and computer code (software: R) are made accessible to participants. The relevant material for the exams is defined by what has been taught in the course. Students are asked to prepare an empirical project that is related to the course contents, and to present and discuss their results during the last weeks.
Literatur
The class materials will in part be based on the following books:– Chan, J., Koop, G., Poirier, D.J. and Tobias, J.L.: "Bayesian Econometric Methods" (Cambridge University Press).
– Hamilton, J.D.: "Time Series Analysis" (Princeton University Press).
– Kim, J.C and Nelson, C.R.: "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" (MIT Press).Relevant additional research papers or materials will be made available over the course of the lecture.
– Hamilton, J.D.: "Time Series Analysis" (Princeton University Press).
– Kim, J.C and Nelson, C.R.: "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" (MIT Press).Relevant additional research papers or materials will be made available over the course of the lecture.
Zuordnung im Vorlesungsverzeichnis
Letzte Änderung: Mo 08.05.2023 15:26
(1) Univariate time series
(2) Multivariate time series
(3) Introduction to Bayesian econometrics
(4) State-space models
(5) Structural and predictive inferenceThe course aims at deepening the understanding of econometric methods that are useful in the analysis of macroeconomic (time series) data. By the end of the course, students are expected to have acquired a good understanding of how to analyze univariate and multivariate time series and how to apply this knowledge to macroeconomic data.